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GLOSSARY OF QUALITY ASSURANCE TERMS

GLOSSARY OF QUALITY ASSURANCE TERMS

Absolute method: a body of procedures and techniques for which measurement is
based entirely on physically defined, fundamental quantities.
Acceptable quality level: a limit above which quality is considered satisfactory and
below which it is not. In sampling inspection, the maximum percentage of defects
or failures that can be considered satisfactory as an average.
Acceptable quality range: the interval, between specified upper and lower limits of a
sequence of values, within which the values are considered to be satisfactory.
Acceptable value: an observed or corrected value that falls within the acceptable
range. See Corrected value and Observed value.
Acceptance criteria: specified limits placed on characteristics of an item, process, or
service which are defined in requirements documents. (ASQC Definitions)
Acceptance sampling: the procedure of drawing samples from a lot or population to
determine whether to accept or reject a sampled lot or population.
Accepted reference value: a numerical quantity that serves as an agreed-upon basis
for comparison, and which is derived as; 1) a theoretical or established quantity
based on scientific principles, 2) an assigned value, based on experimental work
of some recognized organization, or 3) a consensus quantity based on
collaborative experimental work under the auspices of a scientific or engineering
group.
Accreditation: a formal recognition that an organization (e.g., laboratory) is competent
to carry out specific tasks or specific types of tests. See also Certification.
The process by which an agency or organization evaluates and recognizes a
program of study or an institution as meeting certain predetermined qualifications
or standards, thereby accrediting the laboratory. In the context of the National
Environmental Laboratory Accreditation Program (NELAP), this process is a
voluntary one. (NELAC)
Accreditation criterion: a requirement that a laboratory must meet to receive
authorization and approval to perform a specified task.
Accredited laboratory: a laboratory which has been evaluated and given approval to
perform a specified measurement or task, usually for a specific property or
analyte and for a specified period of time.
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Accrediting Authority: the agency having responsibility and accountability for
environmental laboratory accreditation and who grants accreditation. For the
purposes of NELAC, this is EPA, other federal agencies, or the state.
Accuracy: the degree of agreement between an observed value and an accepted
reference value. Accuracy includes a combination of random error (precision) and
systematic error (bias) components which are due to sampling and analytical
operations; a data quality indicator. EPA recommends that this term not be used
and that precision and bias be used to convey the information usually associated
with accuracy. See Precision and Bias.
Action limit: see Control limit.
Adjusted value: the observed value after adjustment for values of a blank or bias of the
measurement system.
Aliquant: a subsample derived by a divisor that divides a sample into a number of
equal parts but leaves a remainder; a subsample resulting from such a divisor.
See Subsample.
Aliquot: a subsample derived by a divisor that divides a sample into a number of equal
parts and leaves no remainder; a subsample resulting from such a division. In
analytical chemistry the term aliquot is generally used to define any
representative portion of the sample.
Alpha error: see “Type I Error.”
Alternate method: any body of procedures and techniques of sample collection and/or
analysis for a characteristic of interest which is not a reference or approved
equivalent method but which has been demonstrated in specific cases to produce
results comparable to those obtained from a reference method.
Analysis (chemical): the determination of the qualitative and/or quantitative
composition of a substance.
Analysis duplicates: the subjection of two portions of the same prepared sample,
extract or digestate to the determinative step of an analytical method or a
measurement system to estimate that step s precision.
Analysis matrix spike: the subjection of a prepared sample, extract or digestate that
has been fortified (spiked) with a known amount of the analyte of interest, to the
determinative step of an analytical method to estimate the bias imparted by the
instrumental or determinative procedure.
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Analyte: the substance, a property of which is to be measured by chemical analysis.
Analytical batch: a group of samples, including quality control samples, which are
processed together using the same method, the same lots of reagents, and at the
same time or in continuous, sequential time periods. Samples in each batch
should be of similar composition and share common internal quality control
standards.
Analytical blank: see Reagent blank.
Analytical Detection Limit (LD): the smallest amount of an analyte that can be
distinguished in a sample by a given measurement procedure throughout a given
confidence interval (e.g., 0.95). See Method Detection Limit.
Analytical limit of discrimination: see Method detection limit.
Analytical Reagent (AR): the American Chemical Society’s designation for the highest
purity of certain chemical reagents and solvents. See Reagent grade.
Arithmetic mean: the sum of all the values of a set of measurements divided by the
number of values in the set, usually denoted by x; a measure of central tendency.
See Measure of central tendency.
Assessment: the evaluation process used to measure the performance or
effectiveness of a system and its elements, used to denote any of the following:
audit, performance evaluation, management systems review, peer review,
inspection, or surveillance. ANSI/ASQC E4-1994
Assignable cause: a factor or an experimental variable shown to significantly change
the quality of an effect or a result.
Audit: a systematic evaluation to determine the conformance to quantitative
specifications of some operational function or activity. See Audit of data quality,
Performance evaluation audit, and Technical systems audit, and also Review,
and Management systems review.
Audit of data quality (ADQ): a qualitative and quantitative evaluation of the
documentation and procedures associated with environmental measurements to
verify that the resulting data are of acceptable quality.
Audit sample: See Performance evaluation sample.
Average: see Arithmetic mean.
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Background level (environmental): the concentration of substance in a defined
control area during a fixed period of time before, during or after a data gathering
operation.
Batch: a quantity of material (e.g., samples) of the same or similar matrix, expected to
behave similarly with respect to the procedure(s) being employed and produced
or processed in one operation, considered to be a uniform discrete unit.
NELAC defines batch as follows: environmental samples which are prepared
and/or analyzed together with the same process and personnel, using the same
lot(s) of reagents. A preparation batch is composed of one to 20 environmental
samples of the same NELAC-defined matrix, meeting the above mentioned
criteria and with a maximum time between the start of processing of the first and
last sample in the batch to be 24 hours. An analytical batch is composed of
prepared environmental samples (extracts, digestates or concentrates) which are
analyzed together as a group. An analytical batch can include prepared samples
originating from various environmental matrices and can exceed 20 samples.
(Quality Systems)
Batch-lot: the samples collected under sufficiently uniform conditions to be processed
as a group. See Batch, Batch size.
Batch-sample: one of the samples drawn from a batch.
Batch-size: the number of samples in a batch-lot.
Beta error: see Type II Error.
Bias: the systematic or persistent distortion of a measurement process which deprives
the result of representativeness (i.e., the expected sample measurement is
different than the sample’s true value.) A data quality indicator.
Blank: a sample that has not been exposed to the analyzed sample stream in order to
monitor contamination during sampling, transport, storage or analysis. The blank
is subjected to the usual analytical and measurement process to establish a zero
baseline or background value and is sometimes used to adjust or correct routine
analytical results. (AS QC, Definitions of Environmental Quality Assurance Terms,
1996)
Blank sample: a clean sample or a sample of matrix processed so as to measure
artifacts in the measurement (sampling and analysis) process.
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Blind sample: a subsample submitted for analysis with a composition and identity
known to the submitter but unknown to the analyst and used to test the analyst’s
or laboratory’s proficiency in the execution of the measurement process. See
Double-blind sample.
Bulk sample: a sample taken from a larger quantity (lot) for analysis or recording
purposes.
Calibrant: see Calibration standard.
Calibrate: to determine, by measurement or comparison with a standard, the correct
value of each scale reading on a meter or other device, or the correct value for
each setting of a control knob. The levels of the calibration standards should
bracket the range of planned measurements. See Calibration curve.
Calibration-check: calibration material obtained from a source other than the one
supplying the (primary) calibration standard, used to assess (check) the
calibration of a measurement instrument; the act of assessing the calibration of a
measurement instrument utilizing calibration material from a secondary source.
See Span check. Mid-range check, and Zero check.
Calibration-check standard: see Calibration standard.
Calibration curve: the graphical relationship between the known values for a series of
calibration standards and instrument responses.
Calibration drift: the difference between the instrument response and a reference
value after a period of operation without recalibration.
Calibration standard: a substance or reference material used to calibrate an
instrument.
Calibration Standard: a solution prepared from the primary dilution standard solution
or stock standard solutions and the internal standards and surrogate analytes.
The Calibration solutions are used to calibrate the instrument response with
respect to analyte concentration.
Candidate method: a body of procedures and techniques of sample collection and!or
analysis that is submitted for approval as a reference method, an equivalent
method, or an alternative method.
Carrying-agent: any diluent or matrix used to entrain, dilute or to act as a vehicle for a
compound of interest.
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CAS#: Chemical Abstracts Service registry number of elements, chemical compounds,
and certain mixtures.
Cause-effect diagram: a graphical representation of an effect and possible causes. A
popular one is the Ishikawa “fish bone diagram.”
Central line: the line on a control chart that represents the expected value of the
control chart statistic; often the mean. See Control chart.
Certification: the process of testing and evaluation against specifications designed to
document, verify, and recognize the competence of a person, organization, or
other entity to perform a function or service usually for a specified time. See also
Accreditation.
Certification of Data Quality: the real-time attestation that the activities of an
environmental data collection operation’s individual elements (e.g., sampling
design, sampling, sample handling, chemical analysis, data reduction, etc.,) have
been carried out in accordance with the operation’s requirements and that the
results meet the defined quality criteria.
Certified Reference Material (CRM): a reference material that has one or more of its
property values established by a technically valid procedure and is accompanied
by or traceable to a certificate or other documentation issued by a certifying body.
See Certification and Reference material.
Certified value: the reported numerical quantity that appears on a certificate for a
property of a reference material.
Chain-of-custody: an unbroken trail of accountability that insures the physical security
of samples, data and records.
Chance cause: an unpredictable, random determinant of variation of a response in a
sampling or measurement operation.
Characteristic: see Property.
Check sample: an uncontaminated sample matrix spiked with known amounts of
analytes usually from the same source as the calibration standards. It is generally
used to establish the stability of the analytical system but may also be used to
assess the performance of all or a portion of the measurement system. See also
Quality control sample.
Check standard: a substance or reference material obtained from a source
independent from the source of the calibration standard; used to prepare check
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samples.
Chi-square test: a statistical test of the agreement between the observed frequency of
events and the frequency expected according to some hypothesis.
Clean sample: a sample of a natural or synthetic matrix containing no detectable
amount of the analyte of interest and no interfering material.
Coefficient of variation (CV): a measure of relative dispersion (precision.) It is equal to
the ratio of the standard deviation divided by the arithmetic mean. See also
Relative standard deviation.
Collaborative testing: the evaluation of an analytical method by typical or
representative laboratories using subsamples prepared from a homogeneous
standard sample.
Collocated sample: one of two or more independent samples collected so that each is
equally representative for a given variable at a common space and time.
Collocated samplers: two or more identical sample collection devices, located
together in space and operated simultaneously, to supply a series of duplicate or
replicate samples for estimating precision of the total measurement
system/process.
Comparability: the degree to which different methods, data sets and/or decisions
agree or can be represented as similar; a data quality indicator.
Compatibility: ability of entities to be used together under specific conditions to fulfil
relevant requirements. (ISO 8402)
Completeness: the amount of valid data obtained from a data collection project
compared to the planned amount needed to meet the data quality objectives.
Usually expressed as a percentage. A data quality indicator.
Component of variance: a part of the total variance associated with a specified source
of variation.
Composite sample: a sample prepared by physically combining two or more samples
having some specific relationship and processed to ensure homogeneity. See
Flow-proportioned sample and Time- proportioned sample.
Confidence coefficient: the probability statement that accompanies a confidence
interval and is equal to unity minus the associated type I error rate (false positive
rate). A confidence coefficient of 0.90 implies that 90% of the intervals resulting
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from repeated sampling of a population will include the unknown (true) population
parameter. See Confidence interval.
Confidence interval: the numerical interval constructed around a point estimate of a
population parameter, combined with a probability statement (the confidence
coefficient) linking it to the population’s true parameter value. If the same
confidence interval construction technique and assumptions are used to calculate
future intervals, they will include the unknown population parameter with the
same specified probability. See Confidence coefficient.
Confirmation: verification of the presence of a component through the use of an
analytical technique that differs from the original method. These may include:
Second column confirmation
Alternate wavelength
Derivatization
Mass spectral interpretation
Alternative detectors or
Additional cleanup procedures.
Conformity: fulfilment of specified requirements. (ISO 8402)
Control chart: a graph of some measurement plotted over time or sequence of
sampling, together with control limit(s) and, usually, a central line and warning
limit(s). See Central line, Control limit and limit.
Control limit: a specified boundary on a control chart that, if exceeded, indicates a
process is out of statistical control, and the process must be stopped, and
corrective action taken before proceeding (e.g., for a Shewhart chart the control
limits are the mean plus and minus three standard deviations, i.e., the 99.72%
confidence level on either side of the central line.)
Control sample: see quality control sample and Check sample.
Control standard: see Check standard.
Controlled variable: a variable that is set at a pre-selected level when a controlled
experiment is conducted.
Corrective action: an action taken to eliminate the causes of an existing
nonconformance, deficiency, or other undesirable situation in order to prevent
recurrence. (ISO 8402)
Correlation: a measure of association between two variables. See also Correlation
coefficient.
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Correlation coefficient: a number between -1 and 1 that indicates the degree of
linearity between two variables or sets of numbers. The closer to -1 or + 1, the
stronger the linear relationship between the two (i.e., the better the correlation.)
Values close to zero suggest no correlation between the two variables. The most
common correlation coefficient is the product-moment, a measure of the degree
of linear relationship between two variables.
Critical-toxicity range: the interval between the highest concentration at which all test
organisms survive and the lowest concentration at which all test organisms die
within the test period.
Customer: any individual or organization for whom items or services are furnished or
work performed in response to defined requirements and expectations.
- recipient of a product provided by the supplier. (ISO 8402) Daily standard:
synonym for Calibration standard.
Data: facts or figures from which conclusions can be inferred.
Data analysis: the comparison of suitably reduced data with a conceptual model (e.g.,
a dispersion model) and may include computation of summary statistics, standard
errors, confidence intervals, tests of hypotheses, and goodness-of-fit tests.
Data Audit: a qualitative and quantitative evaluation of the documentation and
procedures associated with environmental measurements to verify that the
resulting data are of acceptable quality (i.e., that they meet specified acceptance
criteria.
Data quality: the totality of features and characteristics of data that bears on their
ability to satisfy a given purpose; the sum of the degrees of excellence for factors
related to data.
Data Quality Assessment (DQA): the statistical evaluation of a data set to establish
the extent to which it meets user-defined application requirements (i.e., DQOs).
Data of Known Quality: data are of known quality when the qualitative and quantitative
components associated with their derivation are documented appropriately for
their intended use, and such documentation is verifiable and defensible.
Data quality indicators: quantitative statistics and qualitative descriptors that are used
to interpret the degree of acceptability or utility of data to the user. The principal
data quality indicators are bias, precision, accuracy (precision and bias are
preferred), comparability, completeness, and representativeness.
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Data Quality Objective (DQO): qualitative and quantitative statements of the overall
level of uncertainty that a decision-maker is willing to accept in results or in
decisions derived from environmental data. DQOs provide the statistical
framework for planning and managing environmental data operations consistent
with the data user’s needs.
Data Quality Objectives process: a systematic planning tool based on the scientific
method that identifies and defines the type, quality and quantity of data needed to
satisfy a specified use.
Data reduction: the process of transforming the number of data items by arithmetic or
statistical calculations, standard curves, concentration factors, etc., and collation
into a more useful form. Data reduction is irreversible and generally results in a
reduced data set and an associated loss of detail.
Data review: the systematic evaluation of achieved quality control results to establish if
the samples and/or measurements performed on them meet specified
acceptance criteria, for the purpose of determining whether or not the affected
results may or may not be used or should be qualified.
Data set: all the observed values for the samples in a test or study; a group of data
collected under similar conditions and which, therefore, can be analyzed as a
whole.
Data transformation: the conversion of individual data point values into related values
or symbols using formulae (reversible) or symbols (irreversible)
Data validation: See Data review/validation.
Datum: the singular of data. See Data and Value.
Decision error: applying incorrect or erroneous data in choosing between alternatives,
resulting in making the wrong selection..
Defect: nonfulfilment of an intended usage requirement or reasonable expectation.
(ISO 8402)
Defensible: the ability to withstand any reasonable challenge related to the veracity or
integrity of laboratory documents and derived data.
Defensible decision making: the systematic application of objective data or
information in selecting between alternatives.
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Degrees of freedom: the total number of items in a sample minus the number of
independent relationships existing among them; the divisor used to calculate a
variance term; in the simplest cases, it is one less than the number of
observations.
Dependability: collective term used to describe the availability performance and its
influencing factors: reliability performance, maintainability performance and
maintenance-supported performance. (ISO 8402)
Dependent variable: see Response variable.
Detection limit (DL): the lowest concentration or amount of the target analyte that can
be determined to be different from zero by a single measurement at a stated level
degree of confidence. See Method detection limit.
Determination: the complete analytical process of measuring the property of interest in
a sample, from selecting or measuring a test portion or subsample to the
reporting of results. See Test determination.
Diluent: a substance added to another to reduce the concentration and resulting in a
homogeneous end product without chemically altering the compound of interest.
Dilution factor: the numerical value obtained from dividing the new volume of a diluted
substance by its original volume.
Document control: the policies and procedures used by an organization to ensure that
its documents and their revisions are proposed, reviewed, approved for release,
inventoried, distributed, archived, stored, and retrieved in accordance with the
organization s s requirements.
Double-blind sample: a sample submitted to evaluate performance with concentration
and identity unknown to the analyst. See Blind sample.
Duplicate: an adjective describing the taking of a second sample or performance of a
second measurement or determination. Often incorrectly used as a noun and
substituted for “duplicate sample.” Replicate is to be used if there are more than
two items. See Replicate.
Duplicate analyses or measurements: the analyses or measurements of the variable
of interest performed identically on two subsamples of the same sample. The
results from duplicate analyses are used to evaluate analytical or measurement
precision but not the precision of sampling, preservation or storage internal to the
laboratory.
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Duplicate samples: two samples taken from and representative of the same population
and carried through all steps of the sampling and analytical procedures in an
identical manner. Duplicate samples are used to assess variance of the total
method including sampling and analysis. See Collocated sample.
Dynamic blank: a sample-collection material or device (e.g., filter or reagent solution)
that is not exposed to the material to be selectively captured, but is transported
and processed in the same manner as the sample. See Field blank, Instrumental
blank and Sampling equipment blank.
Dynamic calibration: standardization of both the measurement and collection systems
using a reference material similar to the unknown. For example, a series of airmixture
standards containing sulfur dioxide of known concentrations could be
used to calibrate a sulfur dioxide bubbler system.
Dynamic range: the extent over which a method can be calibrated for measuring a
variable of interest.
Entity: that which can be individually described and considered. (ISO 8402)
Environmental data: measurements or information that describes environmental
processes or conditions, or the performance of environmental technology.
Environmental data operations: work performed to obtain, use, or report information
pertaining to environmental processes and conditions.
Environmental Detection Limit (EDL): the smallest level at which a radionuclide in an
environmental medium can be unambiguously distinguished for a given
confidence interval using a particular combination of sampling and measurement
procedures, sample size, analytical detection limit, and processing procedure.
The EDL shall be specified for the 0.95 or greater confidence interval. The EDL
shall be established initially and verified annually for each method and sample
matrix. (NELAC)
Environmental sample: a sample of any material that is collected from an
environmental source.
Environmentally related measurement: any assessment of environmental concern
generated through or for field, laboratory, or modeling processes; the value
obtained from such an assessment.
Environmental technology: pollution control devices and systems, waste treatment
processes and storage facilities, and site remediation technologies and their
components that may be added to process discharges (e.g., emissions, effluents)
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or utilized in the ambient environment to remove pollutants or contaminants, or
prevent them from entering the environment. (ANSI/ASQC E4-1994)
Equivalent method: any method of sampling and/or analysis demonstrated to result in
data having a consistent and quantitatively known relationship to the results
obtained with a reference method under specified conditions, and formally
recognized by the EPA.
Error (measurement): the difference between an observed or corrected value of a
variable and a specified, theoretically correct, or true value.
Error function: the mathematical relationship of the results obtained from the
measurement of one or more properties and the error of the applied
measurement process. See Normal distribution.
Experimental variable: See Independent variable.
External quality control: the activities which are routinely initiated and performed by
persons outside of normal operations to assess the capability and performance of
a measurement process.
False negative decision: see Type II Error.
False negative result: estimating (incorrectly) that an analyte is not present when it
actually is present.
False positive decision: see Type I Error.
False positive result: estimating (incorrectly) that an analyte is present when it is
actually present.
Field blank: a clean sample (e.g., distilled water), carried to the sampling site, exposed
to sampling conditions (e.g., bottle caps removed, preservatives added) and
returned to the laboratory and treated as an environmental sample. Field blanks
are used to check for analytical artifacts and/or background introduces by
sampling and analytical procedures. See Dynamic blank and Sampling equipment
blank.
Field duplicates: see Duplicate sample.
Field (matrix) spike: a sample prepared at the sampling point (i.e., in the field) by
adding a known mass of target analyte to a specified amount of sample. Field
matrix spikes are used, for example, to determine the effect of the sample
preservation, shipment, storage and sample preparation on analyte recovery
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efficiency (analytical bias).
Field reagent blank: see Field blank.
Flag: to qualify or signal that an item does not meet specified requirements.
Flow rate: the quantity-per-unit time of a substance passing a point, plane, or space;
for example the volume or mass of gas or liquid emerging from an orifice, pump,
or turbine or moving through a point in a conduit or channel.
Field sample: see Sample.
Field split samples: two or more representative portions taken from the same sample
and submitted for analysis to different laboratories to estimate interlaboratory
precision.
Flag: to qualify or signal that an item does not meet specified requirements.
Flow-proportioned sample: a sample or subsample collected from a fluid system at a
rate that produces a constant ratio of sample accumulation to matrix flow rate.
Fortify: synonym for Spike.
Full-scale response: the maximum output of a measurement instrument in a given
range as displayed on a meter or scale.
Functional analysis: a mathematical evaluation of each component of the
measurement system (sampling and analysis) in order to quantitate the error for
each component. A functional analysis is usually performed prior to a ruggedness
test in order to determine those variables which should be studied experimentally.
Geometric mean: the antilogarithm of the mean of the logarithms of all the values in a
set.
Good laboratory practices (GLP): either general guidelines or formal regulations for
performing basic laboratory operations or activities that are known or believed to
influence the quality and integrity of the results.
Goodness-of-fit: the measure of agreement of the values in a data set and the
expected or hypothesized ones. the application of the chi-square distribution in
comparing the frequency distribution of a statistic observed in a sample with the
expected frequency distribution based on some theoretical model.
Grab sample: a single sample which is collected at one point in time and place.
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Grade: the category or rank given to entities having the same functional use but
different requirements for quality. (ISO 8402)
Graded approach: the processs of basing the level of application of managerial
controls applied to an item or work according to the intended use of the results
and the degree of confidence needed in the quality of the results ( See Data
Quality Objectives). (U.S. DOE Order 5700.6C, Quality Assurance).
Gross sample: see Bulk sample.
Guidance: suggested practice that is not mandatory, intended as an aid or example in
complying with a standard or requirement. (ASQC Definitions of Environmental
Quality Assurance Terms, 1996).
Holding time: the period a sample may be stored prior to its required analysis. While
exceeding the holding time does not necessarily negate the veracity of analytical
results, it causes the qualifying or flagging . of the data for not meeting all of the
specified acceptance criteria. The maximum times that samples may be held
prior to analysis and still be considered valid. (40 CFR Part 136).
Homogeneity: the degree of uniformity of structure or composition.
Hypothesis (statistical): a tentative statement about one or more parameters of a
population or group of populations
- an unproved theory, proposition, supposition, etc. tentatively accepted to
explain certain facts or to provide a basis for further investigation.
Hypothesis testing: the application of statistical tests to enable an informed decision
between the null - and the alternative hypothesis.
In-control: a condition indicating that performance of the quality control system is within
the specified control limits, i.e., that a stable system of chance is operating and
resulting in statistical control. See Control chart.
Independent variable: see Controlled variable.
Initial Demonstration of Analytical Capability: the procedure for establishing a
laboratory s ability to generate the measurement accuracy and precision required
by many of the EPA’s analytical methods. In general the procedure includes the
addition of a specified concentration of each analyte (using a QC check sample)
in each of four separate aliquots of laboratory pure water. These are carried
through the entire analytical procedure and the percentage recovery and the
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standard deviation are determined and compared to specified QC accetance
limits. (40 CFR Part 136).
Inspection criterion: the specification(s) and rationale for rejecting and accepting
samples in a particular sampling plan.
Instrument blank: a clean sample processed through the instrumental steps of the
measurement process; used to assess instrument contamination. See Dynamic
blank.
Interference: a positive or negative effect on a measurement caused by a variable
other than the one being investigated.
Interference equivalent: the mass or concentration of a foreign substance which gives
the same measurement response as one unit of mass or concentration of the
substance being measured.
Interlaboratory calibration: the process, procedures, and activities for standardizing a
given measurement system to ensure that laboratories participating in the same
program can produce comparable data.
Interlaboratory method validation study (IMVS): the formal study of a sampling
and/or analytical method, conducted with replicate, representative matrix
samples, following a specific study protocol and utilizing a specific written
method, by a minimum of seven laboratories, for the purpose of estimating
interlaboratory precision, bias and analytical interferences.
Interlaboratory precision: a measure of the variation, usually given as the standard
deviation, among the test results from independent laboratories participating in
the same test.
Interlaboratory test: a test performed by two or more laboratories on the same
material for the purpose of assessing the capabilities of an analytical method or
for comparing different methods.
Internal quality control: see Intralaboratory quality control.
Internal standard: aknown amount of a standard added to a test portion of a sample
and carried through the entire determination procedure as a reference for
calibrating and controlling the precision and bias of the applied analytical method.
Intralaboratory quality control: the routine activities and checks, such as periodic
calibrations, duplicate analyses and spiked samples, that are included in normal
internal procedures to control the accuracy and precision of measurements.
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Intralaboratory precision: a measure of the method/sample specific analytical
variation within a laboratory; usually given as the standard deviation estimated
from the results of duplicate/replicate analyses. See also Standard deviation and
Variance.
Laboratory accreditation: see Accredited laboratory and Accreditation.
Laboratory blank: see Reagent blank.
Laboratory control sample (however named, such as laboratory fortified blank, spiked
blank):an uncontaminated sample matrix spiked with known amounts of analytes
from a source independent of the calibration standards. It is generally used to
establish intra-laboratory or analyst specific precision and bias or to assess the
performance of all or a portion of the measurement system. (Glossary of Quality
Assurance Terms, QAMS, 8/3 1/92).
Laboratory duplicates: synonym for Duplicate analyses. Aliquots of a sample taken
from the same container under laboratory conditions and processed and analyzed
independently.
Laboratory performance check solution: a solution of method and surrogate analytes
and internal standards; used to evaluate the performance of the instrument
system against defined performance criteria.
Laboratory replicates: see Replicate analysis or measurement.
Laboratory spiked blank: see Spiked laboratory blank.
Laboratory spiked sample: see Spiked sample.
Laboratory splits or split samples: two or more representative portions taken from
the same sample and analyzed by different laboratories to estimate the
interlaboratory precision or variability and data comparability.
Laboratory sample: a subsample of a field, bulk or batch sample selected for
laboratory analysis.
Least squares method: a technique for estimating model coefficients which minimizes
the sum of the squares of the differences between each observed value and its
corresponding predicted value derived from the assumed model.
Limit of detection (LOD): The lowest concentration level that can be determined (by a
single analysis and with a defined level of confidence,) to be statistically different
QA Glossary December 10, 1997
18
from a blank. [Analytical Chemeistry, 55, p. 2217, December, 1983, modified] See
also Method Detection Limit.
Limit of quantification (LOQ): the concentration of analyte in a specific matrix for
which the probability of producing analytical values above the method detection
limit is 99 percent.
Linearity: the degree of agreement between the calibration curve of a method and a
straight line assumption.
Lot: a number of units of an article or a parcel of articles offered as one item;
commonly, one of the units, such as a sample of a substance under study. See
Batch.
Lot size: the number of units in a particular lot. See Batch lot and Batch size.
Lower control limit: see Control limit.
Lower warning limit: see Warning limit.
Management review: formal evaluation by top management of the status and
adequacy of the quality system in relation to quality policy and objectives.
(ISO 8402)
Management system: a structured nontechnical system describing the policies,
objectives, principles, organizational authority, responsibilities, accountability, and
implementation plan of an organization for conduction work and producing items
and services. (ANSI/ASQC E4-1994)
Management Systems Review (MSR): the qualitative assessment of a data collection
operation and/or organization(s) to establish whether the prevailing quality
management structure, practices, and procedures are adequate for ensuring that
the type and quality of data needed and expected are obtained. See Review and
Audit
Matrix: a specific subset of a medium (e.g., surface water, drinking water, kaolinite) in
which the analyte of interest may be contained. Matrices may be
defined/differentiated by their behavior: samples of the same or similar matrix are
expected to behave the same or similarly with respect to the procedure(s)
employed on them. See Medium.
For NELAC: The component or substrate which contains the analyte of interest. For
purposes of batch determination, the following matrix types shall be used:
- Aqueous: Any aqueous sample excluded from the definition of a
QA Glossary December 10, 1997
19
drinking water matrix or Saline/Estuarine source. Includes surface water,
groundwater and effluents.
- Drinking water: Any aqueous sample that has been designated a
potable or potential potable water source.
- Saline/Estuarine: Any aqueous sample from an ocean or estuary, or
other salt water source such as the Great Salt Lake.
- Non-aqueous liquid: Any organic liquid with <15%>15% settleable solids.
- Chemical Waste: A product or by-product of a industrial process
that results in a matrix not previously defined.
- Air Samples: Media used to retain the analyte of interest from an air
sample such as sorbent tubes or summa canisters. Each medium shall be
considered as a distinct matrix. (Quality Systems)
Matrix spike: see Spiked sample.
Matrix spike duplicate sample analysis: see Matrix, Duplicate analysis and Spiked
sample.
Maximum contaminant level: the highest permissible concentration of a pollutant that
may be delivered to any receptor.
Maximum holding time: the length of time a sample can be kept under specified
conditions without undergoing significant degradation of the analyte(s) or property
of interest.
May: permitted but not required. (TRADE)
Mean: see Arithmetic mean.
Measurement range: the range over which the precision and/or recovery of a
measurement method are regarded as acceptable. See Acceptable quality range.
Measurement standard: a standard added to the prepared test portion of a sample
(e.g. to the concentrated extract or the digestate) as a reference for calibrating
and controlling measurement or instrumental precision and bias.
Measurement system: those elements of a data collection project comprised of the
sampling process, the analytical method(s), the quality control and instrument
calibration requirements, and its data acquisition and management requirements.


Measure of central tendency: a statistic that describes the grouping of values in a
data set around some common value (e.g., the median, arithmetic mean, or
geometric mean.)
Measure of dispersion: a statistic that describes the variation of values in a data set
around some common value. See Coefficient of variation, Range, Variance and
Standard deviation.
Medium: a substance (e.g., air, water, soil) which serves as a carrier of the analytes of
interest. See Matrix.
Medium blank: see Field blank and/or Laboratory blank.
Median: the middle value for an ordered set of n values; represented by the central
value when n is odd or by the mean of the two most central values when n is
even.
Method: a body of procedures and techniques for performing a task (e.g., sampling,
characterization, quantification) systematically presented in the order in which
they are to be executed.
Method blank: a clean sample processed simultaneously with and under the same
conditions as samples containing an analyte of interest through all steps of the
analytical procedure.
Method check sample: see Spiked laboratory blank.
Method detection limit (MDL): the minimum concentration of an analyte that, in a given
matrix and with a specific method, has a 99% probability of being identified,
qualitatively or quantitatively measured, and reported to be greater than zero. See
Detection limit.
Method of least squares: see Least squares method.
Method performance study: see Interlaboratory method validation study.
Method quantification limit (MQL): see Limit of quantification and also Method
detection limit.
Mid-range check: a standard used to establish whether the middle of a measurement
method s calibrated range is still within specifications.
Minimum detectable level: see Method detection limit.
QA Glossary December 10, 1997
21
Mixedwaste: Hazardous waste material as defined by 40 CFR, Part 261 (RCRA) and
mixed with radioactive waste, subject to the requirements of the Atomic Energy
Act. (ANSI/ASQC E4-1 994)
Mode: the most frequent value or values in a data set.
Multipoint calibration: the determination of correct scale values by measuring or
comparing instrument responses at a series of standardized analyte
concentrations; used to define the range for generating quantitative data of
acceptable quality.
Must: denotes a requirement that must be met. (Random House College Dictionary)
Negative controls: measures taken to ensure that a test, its components, or the
environment do not cause undesired effects, or produce incorrect test results.
NELAC: National Environmental Laboratory Accreditation Conference. A voluntary
organization of state and federal environmental officials and interest groups
purposed primarily to establish mutually acceptable standards for accrediting
environmental laboratories. A subset of NELAP. (NELAC)
NELAP: the overall National Environmental Laboratory Accreditation Program of which
NELAC is a part.
Noise: the sum of random errors in the response of a measuring instrument.
Nonconformity: nonfulfillment of a specified requirement. (ISO 8402)
Normal distribution: an idealized probability density function that approximates the
distribution of many random variables associated with measurements of natural
phenomena and takes the form of a symmetric “bell-shaped curve.”
Objective evidence: information which can be proven true, based on facts obtained
through observation, measurement, test or other means. (ISO 8402)
Observation: a fact or occurrence that is recognized and recorded.
Observed value: the magnitude of a specific measurement; a variable; a unit of space,
time or quantity; a datum. The observed value is that reported before correction
for a blank value. See Corrected value.
Organization: company, corporation, firm enterprise or institution, or part thereof,
whether incorporated or not, public or private, that has its own functions and
QA Glossary December 10, 1997
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administration. (ISO 8402)
Organizational structure: responsibilities, authorities and relationships, arranged in a
pattern, through which an organization performs its functions. (ISO 8402)
Outlier: an observed value that appears to be discordant from the other observations in
a sample. One of a set of observations that appears to be discordant from the
others. The declaration of an outlier is dependent on the significance level of the
applied identification test. See also Significance level.
Parameter: any quantity such as a mean or a standard deviation characterizing a
population. Commonly misused for “variable”, “characteristic” or “property.”
Peer review: the documented critical evaluation of projects generally beyond the state
of the art or characterized by potential uncertainty, conducted to ensure that
activities are technically adequate, competently performed, properly documented,
and satisfy established technical and quality requirements. The peer review is
conducted by qualified individuals or organizations independent of, but
collectively equivalent to those who performed the original work.
Percentage standard deviation: synonym for Relative standard deviation.
Performance Based Measurement System (PBMS): a set of processes wherein the
data quality needs, mandates or limitations of a program or project are specified
and serve as criteria for selecting appropriate methods to meet those needs in a
cost-effective manner.
Performance evaluation audit: a type of audit in which the quantitative data generated
in a measurement system are obtained independently and compared with
routinely obtained data to evaluate the proficiency of an analyst or laboratory.
Performance evaluation sample (PE sample): a sample, the composition of which is
unknown to the analyst and is provided to test whether the analyst/laboratory can
produce analytical results within specified performance limits. See Blind sample
and Performance evaluation audit.
Population: all possible items or units which possess a variable of interest and from
which samples may be drawn.
- the totality of items or units of material under consideration. (ANSI/ASQC
Al-1978)
Positive controls: measures taken to ensure that a test and/or its components are
QA Glossary December 10, 1997
23
working properly and producing correct or expected results from positive test
subjects.
Precision: the degree to which a set of observations or measurements of the same
property, usually obtained under similar conditions, conform to themselves; a data
quality indicator. Precision is usually expressed as standard deviation, variance or
range, in either absolute or relative terms. See also Standard deviation and
Variance.
Preservation: refrigeration and or reagents added at the time of sample collection to
maintain the chemical and or biological integrity of the sample.
Preventative maintenance: an orderly program of activities designed to ensure against
equipment failure.
Primary reference standard: see Primary standard.
Primary standard: a substance or device, with a property or value that is
unquestionably accepted (within specified limits) in establishing the value of the
same or related property of another substance or device.
Probability: a number between zero and one inclusive, reflecting the limiting proportion
of the occurrence of an event in an increasingly large number of identical trials,
each of which results in either the occurrence or nonoccurrence of the event.
Probability sampling: sampling in which: (a) every member of the population has a
known probability of being included in the sample; (b) the sample is drawn by
some method of random selection consistent with these probabilities; and the
known probabilities of inclusion are used in forming estimates from the sample.
The probability of selection need not be equal for members of the population.
Procedure: a set of systematic instructions for performing an activity.
- specified way to perform an activity. (ISO 8402)
Process: set of inter-related resources and activities which transform inputs into
outputs. (ISO 8402)
Proficiency Test Sample (PT): a sample, the composition of which is unknown to the
analyst and is provided to test whether the analyst/laboratory can produce
analytical results within specified performance limits. (Glossary of Quality
Assurance Terms, QAMS, 8/31/92).
Proficiency Testing: Determination of the laboratory calibration or testing performance
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24
by means of interlaboratory comparisons. (ISO/IEC Guide 2 - 12.6, amended) A
systematic program in which one or more standardized samples is analyzed by
one or more laboratories to determine the capability of each participant.
Proficiency Testing Program: the aggregate of providing rigorously controlled and
standardized environmental samples to a laboratory for analysis, reporting of
results, statistical evaluation of the results in comparison to peer laboratories and
the collective demographics and results summary of all participating laboratories.
Property: a quality or trait belonging and peculiar to a thing; a response variable is a
measure of a property. Synonym for Characteristic.
Protocol: a detailed written procedure for a field and/or laboratory operation (e.g.,
sampling, analysis) which must be strictly adhered to.
Pure Reagent Water: shall be ASTM Type I or Type II water in which no target
analytes or interferences are detected as required by the analytical method.
Qualified: status given to an entity when toe capability of fulfilling specified
requirements has been demonstrated. (ISO 8402)
Qualitative (determination or analysis): the identification of a sample, material,
compound or element without any certainty as to its mass, volume or amount.
Qualitative results are generally expressed as the presence or absence of a
material and are usually not accompanied by confidence statements.
Quality: the sum of features and properties/characteristics of a product or service that
bear on its ability to satisfy stated or implied needs.
- The totality of characteristics of an entity that bear on its ability to satisfy
stated and implied needs. (ISO 8402)
- The consistent conformance of a product or service to a given set of
standards or expectations. (ISO-9000)
Quality (assurance) assessment: the evaluation of environmental data, comprised of
data validation/verification and data quality assessment, to establish whether they
meet the quality criteria needed for a specific application.
Quality assurance (QA): an integrated system of activities involving planning, quality
control, quality assessment, reporting and quality improvement to ensure that a
product or service meets defined standards of quality with a stated level of
confidence.
Quality Assurance Narrative Statement: a description of the quality assurance and
quality control activities to be followed for a research project.
QA Glossary December 10, 1997
25
Quality Assurance Objectives: the limits on bias, precision, comparability,
completeness and representativeness defining the minimal acceptable levels of
performance as determined by the data user’s acceptable error bounds.
Quality Assurance Project Plan (QAPP): a formal document describing the detailed
quality control procedures by which the quality requirements defined for the data
and decisions pertaining to a specific project are to be achieved.
Quality audit: systematic and independent examination to determine whether quality
activities and related results comply with planned arrangements and whether
these arrangements are implemented effectively and are suitable to achieve
objectives. (ISO 8402)
Quality Circle: a small group of individuals from an organization or unit who have
related interests and meet regularly to consider problems or other matters related
to the quality of the product or process.
Quality control (QC): the overall system of technical activities whose purpose is to
measure and control the quality of a product or service so that it meets the needs
of users. The aim is to provide quality that is satisfactory, adequate, dependable,
and economical.
- operational techniques and activities that are used to fulfil requirements for
quality. (ISO 8402)
Quality control chart: see Control chart.
Quality control check sample: see Calibration standard.
Quality control sample: an uncontaminated sample matrix spiked with known amounts
of analytes from a source independent from the calibration standards. It is
generally used to establish Intralaboratory or analyst specific precision and bias
or to assess the performance of all or a portion of the measurement system. See
also Check sample.
Quality improvement: actions taken throughout the organization to increase the
effectiveness and efficiency of activities and processes in order to provide added
benefits to both the organization and its customer. (ISO 8402)
Quality loop: conceptual model of interacting activities that influence quality at the
various stages ranging from the identification of needs to the assessment of
whether these needs have been satisfied. (ISO 8402)
QA Glossary December 10, 1997
26
Quality management: all activities of the overall management function that determine
the quality policy, objectives and responsibilities, and implement them by means
such as quality planning. quality control, quality assurance, and quality
improvement within the quality system. (ISO 8402)
Quality Management Plan (QMP): a formal document describing the management
policies, objectives, principles, organizational authority, responsibilities,
accountability, and implementation plan of an agency, organization or laboratory
for ensuring quality in its products and utility to its users.
Quality planning: activities that establish the objectives and requirements for quality
and for the application of quality system elements. (ISO 8402)
Quality policy: overall intentions and direction of an organization with regard to quality
as formally expressed by top management. (ISO 8402)
Quality system: a structured and documented management system describing the
policies, objectives, principles, organizational authority, responsibilities,
accountability, and implementation plan of an organization for ensuring quality in
its work processes, products (items), and services. The quality system provides
the framework for planning, implementing, and assessing work performed by the
organization and for carrying out required QA and QC.
- organizational structure, procedures, processes, and resources needed to
implement quality management. (ISO 8402)
Quantitation limits: the maximum or minimum levels or quantities of a target variable
that can be quantified with the confidence level required by the data user.
Quantitative (determination or analysis): the relatively accurate measurement of the
amounts or percentages of one or more components of a sample or material.
Depending on the QC operations performed in support of the analysis, qualitative
results may be reported with or without estimates of variability.
Random: lacking a definite plan, purpose or pattern; due to chance.
Random error: the deviation of an observed value from a true value, which behaves
like a variable in that any particular value occurs as though chosen at random
from a probability distribution of such errors. The distribution of random error is
generally assumed to be normal.
Random sample or subsample: a subset of a population or a subset of a sample,
selected according to the laws of chance with a randomization procedure.
QA Glossary December 10, 1997
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Random variable: a quantity which may take any of the values of a specified set with a
specified relative frequency or probability. It is defined by a set of possible values,
and by an associated probability function giving the relative frequency of
occurrence of each possible value.
Randomization: the arrangement of a set of objects in a random order; a set of
treatments applied to a set of experimental units is said to be randomized when
the treatment applied to any given unit is chosen at random from those available
and not already allocated.
Randomness: a basic statistical concept and property implying an absence of a plan,
purpose or pattern, or of any tendency to favor one outcome rather than another.
Range: the difference between the minimum and the maximum of a set of values.
Raw data: any original factual information from a measurement activity or study
recorded in laboratory worksheets, records, memoranda, notes, or exact copies
thereof and that are necessary for the reconstruction and evaluation of the report
of the activity or study. Raw data may include photographs, microfilm or
microfiche copies, computer printouts, magnetic media, including dictated
observations, and recorded data from automated instruments. If exact copies of
raw data have been prepared (e.g., tapes which have been transcribed verbatim,
dated, and verified accurate by signature), the exact copy or exact transcript may
be substituted.
Readiness review: a systematic, documented review of the readiness for start-up or
continued use of a facility , process, or activity. Readiness reviews are typically
conducted before proceeding beyond project milestones and prior to initiation of a
major phase of work. (ANSI/ASQC E4-94)
Reagent blank: a sample consisting of reagent(s), without the target analyte or sample
matrix, introduced into the analytical procedure at the appropriate point and
carried through all subsequent steps to determine the contribution of the reagents
and of the involved analytical steps to error in the observed value.
Reagent grade: the second highest purity designation for reagents which conform to
the current specifications of the American Chemical Society Committee on
Analytical Reagents.
Records system (or plan): a written, documented group of procedures describing
required records, steps for producing them, storage conditions, retention period
and circumstances for their destruction or other disposition.
Recovery efficiency: in an analytical method, the fraction or percentage of a target
QA Glossary December 10, 1997
28
analyte extracted from a sample containing a known amount of the analyte.
Reference material: a material or substance, one or more properties of which are
sufficiently well established to be used for the calibration of an apparatus, the
assessment of a measurement method, or assigning values to materials.
Reference method: a sampling and/or measurement method which has been officially
specified by an organization as meeting its data quality requirements.
Reference standard: a standard, generally of the highest metrological quality available
at a given location, from which measurements made at that location are derived.
(VIM - 6.08). See also Calibration standard.
Relative standard deviation: the standard deviation expressed as a percentage of the
mean recovery, i.e., the coefficient of variation multiplied by 100.
Reliability: the likelihood that an instrument or device will function under defined
conditions for a specified period of time.
Repeatability: the degree of agreement between mutually independent test results
produced by the same analyst using the same test method and equipment on
random aliquots of the same sample within a short period of time.
Replicability: see Repeatability.
Replicate: an adjective or verb referring to the taking of more than one sample or to the
performance of more than one analysis. Incorrectly used as a noun in place of
replicate analysis. Replicate is to be used when referring to more than two items.
See Duplicate.
Replicate analyses or measurements: the analyses or measurements of the variable
of interest performed identically on two or more subsamples of the same sample
within a short time interval. See Duplicate analyses or measurements.
Replicate samples: two or more samples representing the same population
characteristic, time, and place, which are independently carried through all steps
of the sampling and measurement process in an identical manner. Replicate
samples are used to assess total (sampling and analysis) method variance. Often
incorrectly used in place of the term “replicate analysis.” See Duplicate samples
and Replicate analysis.
Representative sample: a sample taken so as to reflect the variable(s) of interest in
the population as accurately and precisely as specified. To ensure
representativeness, the sample may be either completely random or stratified
QA Glossary December 10, 1997
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depending upon the conceptualized population and the sampling objective (i.e.,
upon the decision to be made.)
Representativeness: the degree to which data accurately and precisely represent the
frequency distribution of a specific variable in the population; a data quality
indicator.
Reproducibility: the extent to which a method, test or experiment yields the same or
similar results when performed on subsamples of the same sample by different
analysts or laboratories.
Requirement: a formal statement of a need and the expected manner in which it is to
be met. The translation of a need into a set of individual quantified or descriptive
specifications of the characteristics of an entity in order to enable its realization
and examination.
Requirements for quality: expressions of the needs or their translation into a set of
quantitatively or qualitatively stated requirements for the characteristics of an
entity to enable its realization and examination. (ISO 8402)
Response variable: a variable that is measured when a controlled experiment is
conducted.
Result: the product of a calculation, test method, test or experiment. The result may be
a value, data set, statistic, tested hypothesis or an estimated effect.
Review: the assessment of management/operational functions or activities to establish
their conformance to qualitative specifications or requirements. See Management
systems review and also, Audit.
Rework: action taken on a nonconforming product so that it will fulfil the specified
requirements. (ISO 8402)
Rinsate blank: the solvent used to rinse a container or sampling apparatus. Rinsate
blanks are generally subjected to analysis to determine whether a container or
sampler is free of contamination.
Risk: the probability or likelihood of an adverse effect.
Risk (statistical): the expected loss due to the use of a given decision procedure.
Robustness: (in)sensitivity of a statistical test method to departures from underlying
assumptions. See Ruggedness.
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Rounded number: a number, reduced to a specified number of significant digits or
decimal places using defined criteria.
Round-robin study: a method validation study involving an undefined number of
laboratories or analysts, all analyzing the same sample(s) by the same method. In
a round-robin study all results are compared and used to develop summary
statistics such as interlaboratory precision and method bias or recovery efficiency.
Routine method: a defined plan of procedures and techniques used regularly to
perform a specific task.
Ruggedness: the (in)sensitivity of an analytical test method to departures from
specified analytical or environmental conditions. See Robustness.
Ruggedness testing: the carefully ordered testing of an analytical method while
making slight variations in test conditions (as might be expected in routine use) to
determine how such 30 variations affect test results. If a variation affects the
results significantly, the method restrictions are tightened to minimize this
variability.
Sample: a part of a larger whole or a single item of a group; a finite part or subset of a
statistical population. A sample serves to provide data or information concerning
the properties of the whole group or population.
Sample data custody: see Chain-of-custody.
Sample variance (statistical): a measure of the dispersion of a set of values. The sum
of the squares of the difference between the individual values of a set and the
arithmetic mean of the set, divided by one less than the number of values in the
set. (The square of the sample standard deviation.) See also Measure of
dispersion.
Sampling: the process of obtaining a representative portion of the material of concern.
Sampling equipment blank: a clean sample that is collected in a sample container
with the sample-collection device and returned to the laboratory as a sample.
Sampling equipment blanks are used to check the cleanliness of sampling
devices. See Dynamic blank.
Sampling error: the difference between an estimate of a population value and its true
value. Sampling error is due to observing only a limited number of the total
possible values and is distinguished from errors due to imperfect selection, bias in
response, errors of observation, measurement or recording, etc. See also
Probability sampling.
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31
Scheduled maintenance: see Preventative maintenance.
Screening test: a quick test for coarsely assessing a variable of interest.
Secondary standard: a standard whose value is based upon comparison with a
primary standard.
Selectivity (analytical chemistry): the capability of a method or instrument to respond
to a target substance or constituent in the presence of nontarget substances.
Semiqualitative: the presence or absence of one or more members of a class or group
of substances, compounds, etc., all of which produce the same or similar
response from the detection/measurement system.
Semiquantitative: the relatively inaccurate (e.g., within one order of magnitude)
measurement or approximation of the amounts or percentages of one or more
components of a sample.
Sensitivity: the ability of a method or instrument to disriminating between minimally
different levels of a variable of interest by producing a noticeably different
measurement response.
Shall: denotes a requirement that is mandatory whenever the criterion for conformance
with the specification requires that there be no deviation. This does not prohibit
the use of alternative approaches or methods for implementing the specification
so long as the requirement is fulfilled. (Style Manual for Preparation of Proposed
American National Standards, American National Standards Institute, Eighth
Edition (March 1991).
Should: denotes a guideline or recommendation whenever noncompliance with the
specification is permissible. (Style Manual for Preparation of Proposed American
National Standards, American National Standards Institute, Eighth Edition (March
1991).
Significance level: the magnitude of the acceptable probability of rejecting a true null
hypothesis or of accepting a false null hypothesis; the difference between the
hypothetical value and the sample result.
Significant digit: any of the digits 0 through 9, excepting leading zeros and some
trailing zeros, which is used with its place value to denote a numerical quantity to
a desired rounded number. See Rounded number.
Significant figure: see Significant digit.
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Single operator precision: the degree of variation among the individual
measurements of a series of determinations by the same analyst or operator, all
other conditions being equal.
Site: the area within boundaries established for a defined activity.
Span check: a standard used to establish that a measurement method is not deviating
from its calibrated range.
Span-drift: the change in the output of a continuous monitoring instrument over a
stated time period during which the instrument is not recalibrated.
Span-gas: a gas of known concentration which is used routinely to calibrate the output
level of an analyzer. See Calibration check standard.
Specification: document stating requirements. (ISO 8402)
Specimen: see Sample.
Spike: a known mass of target analyte added to a blank sample or subsample; used to
determine recovery efficiency or for other quality control purposes.
Spiked laboratory blank: see Spiked reagent blank.
Spiked reagent blank: a specified amount of reagent blank fortified with a known mass
of the target analyte; usually used to determine the recovery efficiency of the
method.
Spiked sample: a sample prepared by adding a known mass of target analyte to a
specified amount of matrix sample for which an independent estimate of target
analyte concentration is available. Spiked samples are used, for example, to
determine the effect of the matrix on a method’s recovery efficiency.
Spiked sample duplicate analysis: see Duplicate analysis and Spiked sample.
Split samples: two or more representative portions taken from a sample or subsample
and analyzed by different analysts or laboratories. Split samples are used to
replicate the measurement of the variable(s) of interest.
Standard (measurement): a substance or material with a property quantified with
sufficient accuracy to permit its use to evaluate the same property in a similar
substance or material. Standards are generally prepared by placing a reference
material in a matrix. See Reference material.
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Standard addition: the procedure of adding known increments of the analyte of
interest to a sample to cause increases in detection response. The level of the
analyte of interest present in the original sample is subsequently established by
extrapolation of the plotted responses.
Standard curve: see Calibration curve.
Standard deviation: the most common measure of the dispersion or imprecision of
observed values expressed as the positive square root of the variance. See
Variance.
Standard material: see Standard (measurement), Reference material.
Standard method: an assemblage of techniques and procedures based on consensus
or other criteria, often evaluated for its reliability by collaborative testing and
receiving organizational approval.
Standard operating procedure (SOP): a written document which details the method of
an operation, analysis or action whose techniques and procedures are thoroughly
prescribed and which is accepted as the method for performing certain routine or
repetitive tasks.
Standard reference material (SRM): a certified reference material produced by the
U.S. National Institute of Standards and Technology and characterized for
absolute content independent of analytical method.
Standard reference sample: see Secondarv standard.
Standard solution: a solution containing a known concentration of analytes, prepared
and verified by a prescribed method or procedure and used routinely in an
analytical method.
Standardization: the process of establishing the quantitative relationship between a
known mass of target material (e.g., concentration) and the response variable
(e.g., the measurement system or instrument response.) See Calibration,
Calibration curve and Multipoint calibration.
Statistic: an estimate of a population characteristic calculated from a data set
(observed or corrected values), e.g., the mean or standard deviation.
Stratification: the division of a target population into subsets or strata which are
internally more homogeneous with respect to the characteristic to be studied than
the population as a whole.
QA Glossary December 10, 1997
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Stratified sampling: the sampling of a population that has been stratified, part of the
sample coming from each stratum. See Stratification.
Stock solution: a concentrated solution of analyte(s) or reagent(s) prepared and
verified by prescribed procedure(s), and used for preparing working standards or
standard solutions.
Subsample: a representative portion of a sample. A subsample may be taken from any
laboratory or a field sample. See Aliquant, Aliquot, Split sample and Test portion.
Supplier: organization that provides a product to the customer. (ISO 8402)
Surrogate analyte: a pure substance with properties that mimic the analyte of interest.
It is unlikely to be found in environmental samples and is added to them for
quality control purposes.
Surveillance: the act of maintaining supervision of or vigilance over a well-specified
portion of the environment so that detailed information is provided concerning the
state of that portion.
Synthetic sample: a manufactured sample. See Quality control sample.
Systematic error: a consistent deviation in the results of sampling and/or analytical
processes from the expected or known value. Such error is caused by human and
methodological bias.
Systems audit: see Technical systems audit.
Systems error: see Total systems error.
Target: the chosen object of investigation for which qualitative and/or quantitative data
or information is desired, e.g., the analyte of interest.
Technical systems audit: a thorough, systematic on-site, qualitative review of
facilities, equipment, personnel, training, procedures, record keeping, data
validation, data management, and reporting aspects of a total measurement
system.
Technique: a principle and/or the procedure of its application for performing an
operation.
Test: a procedure used to identify or characterize a substance or constituent. See
Method.
QA Glossary December 10, 1997
35
Test data: see Data.
Test determination: see Determination.
Test method: see Method.
Test portion: a subsample of the proper amount for analysis and measurement of the
property of interest. A test portion may be taken from the bulk sample directly, but
often preliminary operations, such as mixing or further reduction in particle size,
are necessary. See Subsample.
Test result: a product obtained from performing a test determination. See Test
determination.
Test sample: see Test portion.
Test specimen: see Test portion.
Test unit: see Test portion.
Time-proportioned sample: a composite sample produced by combining samples of a
specific size, collected at preselected, uniform time intervals.
Tolerance Chart: A chart in which the plotted quality control data is assessed via a
tolerance level (e.g. +/- 10% of a mean) based on the precision level judged
acceptable to meet overall quality/data use requirements instead of a statistical
acceptance criteria (e.g. +/- 3 sigma). (ANSI N42.23-1995, Measurement and
Associated Instrument Quality Assurance for Radioassay Laboratories)
Total Quality Management (TQM): the process whereby an entire organization, led by
senior management, commits to focusing on quality as a first priority in every
activity. TQM implementation creates a culture in which everyone in the
organization shares the responsibility for continuously improving the quality of
products and services, (i.e., for “doing the right thing, the right way, the first time,
on time.”) in order to satisfy the customer.
- management approach of an organization, centered on quality, based on
the participation of all its members and aiming at long-term success through
customer satisfaction, and benefits to all members of the organization and to
society. (ISO 8402)
Total measurement error: the sum of all the errors that occur from the taking of the
sample through the reporting of results; the difference between the reported result
QA Glossary December 10, 1997
36
and the true value of the population that was to have been sampled.
Traceability: an unbroken trail of accountability for verifying or validating the chain-ofcustody
of samples, data, the documentation of a procedure, or the values of a
standard.
The ability to trace the history, application or location of an entity by means of
recorded identifications. (ISO 8402)
The property of a result of a measurement whereby it can be related to
appropriate standards, generally international or national standards, through an
unbroken chain of comparisons. (VIM - 6.12)
Treatment (experimental): an experimental procedure whose effect is to be measured
and compared with the effect of other treatments.
Trip blank: a clean sample of matrix that is carried to the sampling site and transported
to the laboratory for analysis without having been exposed to sampling
procedures.
Tuning: the process of adjusting a measurement device or instrument, prior to its use,
to ensure that it works properly and meets established performance criteria.
Type I error, (alpha error): an (incorrect) decision resulting from the rejection of a true
hypothesis. (A false positive decision.)
Type II error, (beta error): an (incorrect) decision resulting from acceptance of a false
hypothesis. (A false negative decision.)
Uncertainty: a measure of the total variability associated with a process that includes
the two major error components: systematic error (bias) and random error
(imprecision).
Universe: see Population.
Upper control limit: see Control limit.
Upper warning limit: see Warning limit.
User check: an evaluation of a written procedure (e.g., chemical analysis method) for
clarity and accuracy in which an independent laboratory analyzes a small number
of spiked samples, following the procedure exactly.
Valid study: a study conducted in accordance with accepted scientific methodology,
QA Glossary December 10, 1997
37
the results of which satisfy predefined criteria.
Validated method: a method which has been determined to meet certain performance
criteria for sampling and/or measurement operations.
Validation: the process of substantiating specified performance criteria.
- confirmation by examination and provision of objective evidence that the
particular requirements for a specific intended use are fulfilled. (ISO 8402)
Value: the magnitude of a quantity. A single piece of factual information obtained by
observation or measurement and used as a basis of calculation.
Variable: an entity subject to variation or change.
Variance: see Sample variance.
Verifiable: the ability to be proven or substantiated.
Verification: Confirmation by examination and provision of objective evidence that
specified requirements have been fulfilled. In design and development, validation
concerns the process of examining a result of a given activity to determine
conformance to the stated requirements for that activity. (ANSI/ISO/ASQC
A8402-1994)
Warning limit: a specified boundary on a control chart that indicates a process may be
going out of statistical control and that certain precautions are required. For
example; for a Shewhart chart the warning limits are placed at plus and minus
two standard deviations of the mean (i.e., at the 95% confidence interval.)
Working standard: see Secondary standard.
Zero check: a standard, usually devoid of the analyte or variable of interest, used to
establish whether the ~zero~ point of a measurement method is still properly
calibrated.
Zero drift: the change in instrument output over a stated time period of nonrecalibrated,
continuous operation, when the initial input concentration is zero; usually
expressed as a percentage of the full scale response.
QA Glossary December 10, 1997
38
Acronyms
AAPCO American Association of Pest Control Officials (FIFRA)
ACS American Chemical Society
ADQ Audit of Data Quality
ANPRM Advanced Notice of Proposed Rule Making
AOAC Association of Official Analytical Chemists
AQCR Air Quality Control Region
ARAR Applicable or Relevant and Appropriate Standards, Limitations, Criteria,
and Requirements
ASTM American Society for Testing and Materials
BACT Best Available Control Technology
BDAT Best Demonstrated Available Technology
CA Cooperative Agreement
CAA Clean Air Act
CAIR Comprehensive Assessment Information Rule
CAR Corrective Action Report
CAS Chemical Abstract Service
CBI Compliance Biomonitoring Inspection
CEI Compliance Evaluation Inspection
CEPP Chemical Emergency Preparedness Program
CERCLA Comprehensive Environmental Responsibility, Compensation and
Liability Act
CFR Code of Federal Regulations
CGI Comprehensive Ground Water Inspection
QA Glossary December 10, 1997
39
CGME Comprehensive Ground-Water Monitoring Evaluation
CIS Compliance Inspection Strategy
CLP Contract Laboratory Program
CME Construction Management Evaluation
COE U. S. Army Corps of Engineers
CRM Certified Reference Material
CSI Compliance Sampling Inspection
CSO Combined Sewer Overflow
CV Coefficient Variation
CWA Clean Water Act
DL Detection Limit
D&R Demolition and Renovation
DMR-QA Discharge Monitoring Report - QA Program
DPO Deputy Project Officer
DQA Data Quality Assessment
DQO Data Quality Objectives
DU Decision Unit
EDCA Environmental Data Collection Activity
EDL Estimated Detection Level
EHMW Extra High Molecular Weight
EMAP Environmental Monitoring Assessment Program
EMS Enforcement Management System
EMPC Estimated Maximum (Protocol) Concentration
QA Glossary December 10, 1997
40
ERAMS Environmental Radiation Ambient Monitoring System
ERC Emergency Response Contractor
ERCS Emergency Response Cleanup Service
ERT Emergency Response Team
ESAT Environmental Service Assistant Team
ESP Electrostatic Precipitator
FDA Food and Drug Administration
FIFRA Federal Insecticide, Fungicide and Rodenticide Act
FISMP Field Inspection with Sampling
FIT Field Investigation Team
FR Food Register
FRDS Federal Reporting Data System
FS Feasibility Study
GLP Good Laboratory Practice
HDPE High Density Polyethylene
HRS Hazard Ranking System
HWDMS Hazardous Waste Data Management System
I/A Innovative/Alternative (Technology)
I&M Inspection and Maintenance
ICP Inductivity Coupled Atomic Emission Plasma Spectometry
ICR Information Collection Request
IFB Invitation for Bidders
IMR Immediate Removal
QA Glossary December 10, 1997
41
IMVS Interlaboratory Method Validation Study
IRM Initial Remedial Measure
ISS Interim Status Survey
IU Industrial User
LAER Lowest Achievable Emissions Rate
LOEC Lowest Observed Effect Concentration
LOIS Loss of Interim Status
LOQ Limit of Qualification
MCL Maximum Contaminant Level
MCLG Maximum Contaminant Level Goals
MCP Municipal Compliance Plan
MDL Method Detection Limit
MIT Mechanical Integrity Test
MPRSA Marine Protection, Research and Sanctuaries Act
MSR Management Systems Review
MSIS Model State Information System
MTR Minimum Technology Requirements
NAAQS National Ambient Air Quality Standards
NADB National Aerometric Data Bank
NAMS National Air Monitoring Stations
NBAR Non-binding Preliminary Allocation of Responsibility
NCLAN National Crop Loss Assessment Network
NCP National Contingency Plan
QA Glossary December 10, 1997
42
NEDS National Emissions Data Base
NEIC National Enforcement Investigations Center (OECM, Denver)
NESHAP National Emission Standards for Hazardous Air Pollutants
NHANES National Health and Nutrition Examination Study
NPDWR National Primary Drinking Water Regulations
NOISH National Institute of Occupational Safety and Health
NIST National Institute of Standards and Technology
NMP National Municipal Policy
NOD Notice of Deficiency
NOEC No-Observed Effect Concentration
NOPES Non-Occupational Pesticide Exposure Study
NPAP National Performance Audit Program
NPDES National Pollutant Discharge Elimination System
NDHAP National Pesticide Hazard Assessment Program
NPL National Priority List
NPO National Program Office
NPRM Notice of Proposed Rule Making
NRC National Resource Center
NSPS New Source Performance Standards
NSR New Source Review
NTIS National Technical Information Service
O&M Operation and Management
OSHA Occupational Safety and Health Administration
QA Glossary December 10, 1997
43
PA/SI Preliminary Assessment/Site Inspection
PA Preliminary Assessment
PARS Precision and Accuracy Reporting System
PCI Pretreatment Compliance Inspection
PCS Permit Compliance System
PE Performance Evaluation
PE Program Element
PI Principal Investigator
PMC Project Management Conference
PO Project Officer
POTW Publicly-Owned Treatment Works
PQL Practical Quantitation Limits
PRP Potential Responsible Party
PSD Prevention of Significant Deterioration
PTE Potential to Emit
PTI Permit to Install
PWSSP Public Water System Supervision Program
QA Quality Assurance
QAMS Quality Assurance Management Staff
QAPjP Quality Assurance Project Plan
QAPP Quality Assurance Program Plan
QC Quality Control
QNCR Quarterly Non-Compliance Report
QA Glossary December 10, 1997
44
RA Remedial Action
RACM Reasonably Available Control Measures
RACT Reasonably Available Control Technologies
RAS Routine Analytical Service (CLP)
RCRA Resource Conservation and Recovery Act
RD Remedial Design
RE Relative Error
REM RI/FS Contractors
RFA RCRA Facility Assessment (RCRA site version of PA/SI)
RFD Reference Doses
RFP Request for Proposals
RFP Reasonable Further Progress (toward attainment)
RI Reconnaissance Inspection
RI Remedial Investigation
RI/FS Remedial Investigation/Feasibility Study
RMCL Recommended Maximum Contaminant Level
ROD Record of Decision
RPM Remedial Project Manager
RSCC Regional Sample Control Center (CLP)
RSD Risk Specified Doses
SAP Sample Analysis Plan
SARA Superfund Amendments and Reauthorizations Act of 1986
SAROAD Storage and Retrieval of Aeromatic Data
QA Glossary December 10, 1997
45
SAS Special Analytical Service (CLP)
SBO Senior Budget Official
SCAP Superfund Comprehensive Accomplishment Plan
SDWA Safe Drinking Water Act
SI Site Inspection
SIF Site Inspection Follow-up
SIP State Implementation Plan
SLAM State Local Air Monitoring Stations
SNC Significant Non-Comliance
SNUR Significant New Use Rule (TSCA 5(e))
SOP Standard Operating Procedure
SRM Standard Reference Material
SS Site Survey
SSID Site/Spill Identification Designation
STC Special Terms and Conditions
TAT Technical Assistant Team
TCLP Toxicity Characteristic Leaching Procedure
TCM Traffic Control Measures
TDD Technical Direction Document
TEAM Total Exposure Assessment Methodology
TEGD Technical Enforcement Guidance Document
TMDL Total Maximum Daily Load
TOC Total Organic Carbon
QA Glossary December 10, 1997
46
TOX Total Organic Halides
TQM Total Quality Management
TSA Technical System Audit
TSCA Toxic Substances Control Act
TSD Temporary Storage and Disposal
TSDF Temporary Storage and Disposal Facility
TSP Total Suspended Particulates
TTO Total Toxic Organics (NPDES permits)
UIC Underground Injection Control
UST Underground Storage Tanks
VE Value Engineering
VE Visual Emissions
VOA Volatile Organics Analysis
VOC Volatile Organic Contaminants
VOC Volatile Organic Chemicals
WAM Work Assignment Manager
WAP Waste Analysis Plan
WENDB Water Enforcement National Data Base
WLA Waste Load Allocation
WQM Waste Quality Management

Now, '100 percent' vegetarian eggs

Now, '100 percent' vegetarian eggs
Erode (Tamil Nadu): Here's some good news for diehard vegetarians who may yet like to tuck in some eggs.

India's leading egg powder manufacturer and exporter will launch a "100 percent vegetarian egg" in the coming year.

"We will commercially launch the completely 100 percent vegetarian eggs both in the domestic market and also export them across the world in a couple of months from now," S Hariharan, general manager, operations of SKM Egg Products Ltd, told IANS.

The company is already exporting 100 percent vegetarian egg powder, egg yolk powder and egg albumen powder to as many as 27 countries in the world, including Europe and Japan.

So what is a vegetarian egg?

Chicks aged between zero and eight weeks are brought to poultry farms and bred till up to 72 weeks when they become "layers".

Normally, each layer lays about 300 eggs in poultry farms. However, these eggs are not totally vegetarian because the hens are fed fishmeal (dry fish powder) as a protein supplement.

However, SKM Egg Products Ltd, located aptly on the Gandhiji Road in Erode, claims all the "egg-laying birds" in its contract farms are not fed any "animal-based food".

Instead of fishmeal, soya powder is added to the poultry feed as the protein supplement.

"Hence, eggs produced in our contract farms are fully vegetarian," asserts Hariharan.

But this company, which buoyantly ended last fiscal (2006-07) with a Rs.845-million ($21.4 million) turnover, did not hit upon the vegetarian egg concept for the sheer sake of vegetarianism.

It was for commercial reasons to meet the strict stipulations of the export market.

The eggs laid by the hens fed on fishmeal contained antibiotic residues in excess of the limits (0.5 parts per billion) set by European countries. Hence, the company substituted soya for fish powder. Thus, the 100 percent vegetarian egg was born.

Recently, SKM, which exported 4,500 tonnes of egg powder last year, set up its own poultry farm with nearly 1.5 million chicks.

However, as of now, the company largely sources the "vegetarian eggs" from nearby Namakkal, which is southern India's "egg land".

With over 700 poultry farms, Namakkal produces 22.5 million eggs every day, which is 14 percent of the country's egg production.

"If milk is vegetarian, then all commercially produced eggs in our farms are vegetarian. Only, most of us use fish feed for the hens because soya feed is expensive," says Namakkal Poultry Feeds and Egg Producers Association president Nallathambi.

So the next time you gobble up an egg pastry, just don't feel guilty.

Source:IANS

Flextronics purchasing Solectron for $3.6 billion

Flextronics purchasing Solectron for $3.6 billion

Quality Management

Quality Management

A systematic set of activities to ensure that processes create products with maximum *Quality* at minimum *Cost of Quality*. The activities include *Quality Assurance*, *Quality Control*, and *Quality Improvement*.

Quality Assurance

Assurance

A planned and systematic set of activities to ensure that variances in processes are clearly identified, assessed and improving defined processes for fullfilling the requirements of customers and product or service makers.

A planned and systematic pattern of all actions necessary to provide adequate confidence that the product optimally fulfils customer's expectations.

A planned and systematic set of activities to ensure that requirements are clearly established and the defined process complies to these requirements.

"Work done to ensure that Quality is built into work products, rather than Defects." This is by (a) identifying what "quality" means in context; (b) specifying methods by which its presence can be ensured; and (c) specifying ways in which it can be measured to ensure conformance (see *Quality Control*, also *Quality*).

Quality

Quality

Quality is difficult to define, it's an abstract term, it requires continuous and dynamic adaptation of products and services to fulfill or exceed the requirements or expectations of all parties in the organization and the community as a whole.

----------------
'Quality means conformance to requirements' (Philip Crosby, 'Quality Is Free'). It does not matter whether or not the requirements are articulated or specified; if a product does not fully satisfy, it lacks quality in some respect. ('Quality is binary -- you've either got it, or you haven't' -- ibid. Note that both these quotes are 'top-of-the-head' and therefore approximate.)

The starting-point for a 'quality product', therefore, is precise determination of the requirements of its users. This may not be possible in practice, but should still be attempted as best possible (see *Acceptable Quality Level*).

Note that the 'quality' of a product is the sum of multiple separate *Quality Attributes*.

QS-9000

QS-9000

QS-9000 is a quality system standard that focuses on helping automotive suppliers ensure that they are meeting/exceeding automotive customer requirements. As mentioned before, it uses ISO 9000 as a core (document control, corrective action, auditing, etc.), but adds quite a few additional requirements.

QS-9000 is now being replaced by a newer related standard called ISO/TS 16949. TS 16949 contains all of ISO 9000, QS-9000, and many European standards.

TS is much more process-oriented than QS or ISO. It defines the business as a set of processes with inputs and outputs that need to be defined, controlled, improved/optimized, etc. In my view TS looks like someone who knew QS took Six Sigma/BB training and incorporated many of the SS/BB ideas.

All Qualit Key words

1-Sample Sign Test

2-Sample t Test

3P

5 Laws of Lean Six Sigma

5 Why's

5C

5S

5Z

6 Ms

6 Serving Men of Creativity

6W

7 QC Tools

7 Wastes Of Lean

8 D Process

8 Wastes of Lean



^ Top


A Acceptable Quality Level - AQL

Acceptance Number

Accessory Planning

Accountability

Accountable

Accuracy

Active Data

Activity Based Costing ABC

Affinity Diagram

Alias

Alpha Risk

Alternative Hypothesis Ha

Analysis Of Variance ANOVA

Analytical Modeling

Anderson-Darling Normality Test

Andon

ANOVA

Appraisal Cost

APQP

Arrow Diagrams

Artisan Process

A-square

Assignable Cause

Assurance

Attribute Data

Attribution Theory

Audit

Authority

Autocorrelation

Automated Process

Availability

Average Incoming Quality

Average Outgoing Quality



^ Top


B B10 life

Back-Date

Balanced Experiment

Balanced Scorecard

Baldrige, Malcolm

Bar Chart

Bartlett Test

Baseline

Baselining

BAU

Benchmarking

Best Practice

Beta Risk

BIA - Business Impact Analysis

Bias

Big 'Q'

Bimodal Distribution

Binomial Distribution

Binomial Random Variable

Black Belt

Black Noise

Blocking

Box-Cox Transformation

Boxplot

BPMS

Brainstorming

BRM

Buffer

Bug

Business Metric

Business Process Quality Management

Business Requirements

Business Value Added



^ Top


C Calibration

CAP

CAP

CAPA

Capability

Capability Analysis

Capacity

CAR Corrective Action Report

Cause

Cause

Cause and Effect Diagram

CBR

CCR

CCR

Center

Center Points

Central Limit Theorem

Central Tendency

Chaku Chaku

Champion

Change Agent

Change Management

Characteristic

Charter

Chi Square Test

Circumstance

C-Level

Cmk

CMM

COC

Coefficient of Variation

Common Cause

Common Cause Variation

Communication

Competitive Advantage

CONC

Concept Engineering

Concomitant Variable

Condition

Confidence Band Or Interval

Confidence Interval

Confirmation

Confounding

Consequential Metrics

Consumers Risk

Containment

Continuous

Continuous Data

Continuous Improvement CI

Control

Control Chart

Control Limits

Control Plan

Convert DPMO/Sigma To Cpk

Copc

COPIS

COPQ

COQ

Correction

Correction versus Corrective Action

Corrective Action

Corrective Action versus Preventive Action

Correlation

Correlation Coefficient r

Cost Model

Cost Of Conformance

Cost Of Non-Conformance

Cost of Poor Quality - COPQ

Cost Of Quality

Cost Target

Covariate

Cp

Cpk

Critical Element

Critical To Quality - CTQ

CRM

CSM

CTC

Current Reality Tree

Customer

Customer Focus

Customer Requirements

Cusum Chart

Cycle Time



^ Top


D Dashboard

Dashboard Examples

Data

Datsu Chaku

Datsu-Chaku

Decision Rights Owner

Defect

Defective

Defects %

Defects Per Million Opportunities - DPMO

Defects Per Unit - DPU

Definition of Quality

Degree of Freedom

Deming Cycle, PDCA

Dependent Variable

Descriptive statistics

Design For Manufacturing and Assembly DFMA

Design for Six Sigma - DFSS

Design of Experiments - DOE

Design Risk Assessment

Detectable Effect Size

DF degrees of freedom

DF Degrees of freedom

DFMEA

Directive

Discrete Data

Dispersion

Distribution

DMADV

D-MAGICS

DMAIC

DMEDI

Document

DOE

DPO

DPU

Drift

Dunnett's 1-way ANOVA

DVP&PV



^ Top


E ECO

ECR

Effect

Effectiveness

Efficacy

Efficacy

Efficiency

ELT

Empirical Rule

Empowerment

Encryption

Enlistment

Entitlement

Entry Criteria

ERP

Erroneous

Error

Error Type I

Error Type II

Error Cause Removal

Error Mode Effects Analysis

ESER

EWMA

Exit Criteria



^ Top


F F test

Facilitate

Factor

Factor of a Consequence

Fagan Style Software Inspection

Failure Modes and Effects Analysis FMEA

FAST

FCE

F-Chart

Fenwick-vanKoesveld Test

FIFO

Financial Metrics

First Time Yield - FTY

FISH

Fishbone

Fisher's 1-way ANOVA

Fits

Fitted value

Flowchart

FMEA

FMVSS

FOCUS - PDCA

Force Field Analysis

Form / Format

Fractional Factorial DOE

Frequency Plot

Full factorial DOE

F-value ANOVA



^ Top


G Gage R&R

Gantt Chart

Gap Analysis

Gating

GCI

Gemba

General Linear Model

Get Info on Loan from 14 Search Engines in 1

Global definition of 'Quality'

Globalization

Goal

Goodman-Kruskal Gamma

GQTS

Green Belt

GRPI

Gwilliam Motivational Model



^ Top


H Hanedashi

Hard Savings

Hawthorn Effect

Hidden Factory, The

Histogram

Homegeneity of variance

Horizontalization

Hoshin Kanri

Hoshin Kanri

House of Quality

Hyper Micro Process map

Hypothesis Testing



^ Top


I ICT

Ideation Brainstorming

IDOV

I-MR Chart

Includes/Excludes

Incoming Goods Inspection

In-Control

Independent Variable

Indirect Cost

Inferential Statistics

Inspection

Inspection Plan

Instant Pudding

Intangible benefits

Interaction

Interactional Data

Interquartile Range

Interrelationship digraph

I-P-O

IQR

Ishikawa, Ichiro

ISO 9000 Series of Standards

ISO 9001:2000

ITIL

I-TRIZ



^ Top


J Jack in the Box

Just In Time JIT Manufacturing



^ Top


K Kaikaku

Kaizen

Kaizen Blitz

Kaizen Event

Kaizen Event

Kanban

Kano Analysis

Kaplan-Meier

Kappa

KBC

KBI and KBR

Kirkpatricks 4 Levels of Evaluation

KISS

KJ

KPI

KPIV

KPOV

Kruskal-Wallis

Kurtosis



^ Top


L L1 Spreadsheet

L2 Spreadsheet

LCL

Lead Time

Lean Level of Buffering LLB

Lean Manufacturing

Leptokurtic Distribution

Level of Buffering

Levels

LIFO

Likert Scale

Linear Relationship

Linearity

Little's Law

Lot

Low Hanging Fruit

LSL

LTPD

Lurking Variable



^ Top


M Machine Capability Index

Main Effect

Malcolm Baldrige National Quality Award

Mallows Statistic C-p

Management

Management by Knowledge

Mann-Whitney

Master Black Belt

Matrix Diagram

Mazume

Mean

Measure of Central Tendency and Dispersion

Measurement System Analysis - MSA

Measures Of Variation

Median

MEDIC

Metricationist

Metrics

MGPP - Multi Generational Product Planning

Mid Range

Mid rank

Minford

MODAPTS

Mode

Moods Median

MPS

MRP

MSA

MTBF

MTTR

Muda

Multicolinearity

Multiple Regression

Multi-Vari Chart

MURA

MURI



^ Top


N Natural Tolerances

Noise

Nominal

Nominal Data

Nominal Group Technique

Non-Conformity

Non-Parametric

Non-parametric Test

Normal Distribution

Normal Probability

Normality test

Normsinv

Null Hypothesis Ho



^ Top


O O.C.T. - Operation Cost Target

O.E.E.

O.E.M.

Objective Evidence

O'Brien Effect

OCAP

OEE

One Piece Flow

Operational Cost

Operational Definition

Operations Process

Opportunity

Opportunity Creation

Optimization

Ordinal Data

Ordinal Data Type

OSHA

Outlier

Output

Ownership



^ Top


P P Value

Paired T Test

Pareto

Passion for Action - PFA

Passive Data

Paynter Chart

PDPC

PDSA

Pearson's Correlation

Percent of tolerance

PFMEA

Pi

Platykurtic Distribution

PMP

PMTS

Poisson Distribution

Poka Yoke

Pooled Standard Deviation

Population

Population Defect Rate

Positive Correlation

PPAP

Ppk

PPM

PPS

Practice

Precision

Prediction Band or Prediction Interval

Prevention cost

Preventive Action

Primary Metrics

Probability

Probability of Defect

Procedures

Process

Process Acceptance Certificate

Process Baseline

Process Capability

Process Capability Index

Process Control

Process Control Plan

Process Control Versus Process Capability

Process Cycle Efficiency PCE

Process Design Requirements

Process Entitlement

Process Indicator

Process Instance

Process Management

Process Map

Process Maturity

Process Measurables

Process Owner

Process Performance Management

Process Stability

Producers Risk

Product

Productivity

Productivity Target

Profession

Project Nomination

Project Process

Project Scope

Project Selection

PSO

PSW

PTC

Pugh Matrix

Pull System

P-Value



^ Top


Q Q1

Q3

QAS

QCM

QFD

QOS

QPR

QS-9000

Qualitative Data

Quality

Quality

Quality

Quality

Quality

QUALITY - DEFINITION

Quality Assurance

Quality Attribute

Quality Control

Quality Dictionary

Quality Function Deployment

Quality Gap

Quality Improvement

Quality Management

Quality Procrastination

Quality Record

Quality Target

Quantifiers

Quantitative data

Quantitative Variable

Queuing Theory

Quorum



^ Top


R R

Rabbit Chase

Radar Chart

Radian

Random Sample

Random Variation

Randomization

Range

Rational Subgroup

RBI

RBM

RCFA

Red X

Reengineering

Regression

REL

Reliability

Repeatability

Replicates

Replication

Reproducibility

Residual

Resolution

Response

Responsibility

Result Measurables

Rework

Robust

Robust Process

Robustness

Rolled Throughput Yield - RTY

RONA

Root Cause

Root Cause Analysis

RPN

RQL

R-Square

R-Square Adjusted

Run Chart

Runs Test



^ Top


S S.M.A.R.T.

S.M.A.R.T.E.R

Sample

Sample Size Calc.

Sampling

Saturated Design

SCAMPER

Scatter Plot

Scatterplot

Scope

Scorecard

SCOT analysis

Screening

Screening DOE

Segmentation

Sensitivity

S-hat Model

Ship Date

Short-Run SPC

Sigma

Sigma Level

Simple Linear Regression

SIPOC

Six Sigma

Six Sigma Strategy

Skewness

SMED

Soft Savings

Software Inspection

Software Inspection Plan

Span

Special Cause

Special Cause Variation

Specification

Spread

SREA

SS Process Report

SS Product Report

SSBOK

Stability

Stable Process

Stakeholder

Stakeholder Analysis

Standard Deviation

Standard Deviation

Standard Operating Sheet SOS

Standard Order

Statistic

Statistical Process Control SPC

Statistical Thinking

Statistics

Stem and Leaf Plot

Strategic Planning

Stratification

Sub-Group

Subgrouping

Subject Matter

Subject Matter Expert - SME

Subjective Rating and Ranking

Sufficiency

Supply Chain Management

SWOT Analysis

System Audit

System of Profound Knowledge - SoPK

Systems Engineering

Systems Thinking



^ Top


T t Statistic

t Test

Taguchi Method

Takt Time

TAT

TEAM

Team Capacity

Team Leader

Telecosm

Theory of constraints TOC

Thought Process Map - TMAP

Throughput

THULLA

Time Value Map

Tolerance Range

Tollgate

Total Observed Variation

Total Prob of Defect

Total Quality

Total Quality Management

TPM

TQM

Transfer Function Y=fX

Transformations

Tree Diagram

Trend Analysis

Trend Charts

Tribal Knowledge

Trimmed Mean

Trivial many

TRIZ

T-test

Tukey's 1-way ANOVA

TVM

Type I Error

Type II Error



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U U Chart

UCL

Unbiased Statistic

Unexplained Variation S

Unit

Univariate

USL



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V Value

Value Stream

Value Stream Mapping

Value-Added

Variable

Variable Data

Variance

Variance Inflation Factor

Variation

Variation Common Cause

Variation Special Cause

Variation Mode and Effect Analysis - VMEA

VEISA

Visual Controls

Vital Few

Voice Of the Business VOB

Voice Of the Customer VOC

Voice Of the Employee VOE

Voice Of The Process VOP

VQD



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W Warning Limits

Waste

WBT

Web Charttm

Whisker

White Noise

Wilcoxon Rank Sum Test

Work Cell

World-Class Quality



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X X

X Bar

X-Bar and R Charts

X-Matrix



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Y Y

Y=fX

Yellow Belt - YB

Yield



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Z Z

Z bench

Z lt

Z Score

Z Shift

Z st

Zadj

Zero Defects

LSL

A lower specification limit is a value above which performance of a product or process is acceptable. This is also known as a lower spec limit or LSL.

Lower Specific Limit: representing the minimum acceptable value of a variable (see also USL)

Lead Time

LIFO

Last In, First Out. A method of inventory rotation to ensure that the newest inventory (last in) is used first (first out).

Lead Time

Lead Time

The amount of time, defined by the supplier, that is required to meet a customer request or demand. (Note, Lead Time is not the same as Cycle Time).

Kanban

Kanban

Kanban: A Japanese term. The actual term means "signal". It is one of the primary tools of a Just in Time (JIT) manufacturing system. It signals a cycle of replenishment for production and materials. This can be considered as a “demand” for product from on step in the manufacturing or delivery process to the next. It maintains an orderly and efficient flow of materials throughout the entire manufacturing process with low inventory and work in process. It is usually a printed card that contains specific information such as part name, description, quantity, etc.

In a Kanban manufacturing environment, nothing is manufactured unless there is a “signal” to manufacture. This is in contrast to a push-manufacturing environment where production is continuous.

Kaizen

Kaizen

Japanese term that means continuous improvement, taken from words 'Kai' means continuous and 'zen' means improvement.

Some translate 'Kai' to mean change and 'zen' to mean good, or for the better.

The same japanese words Kaizen that pronounce as 'Gai San' in chinese mean:

Gai= The action to correct.

San= This word is more related to the Taoism or Buddhism Philosophy in which give the definition as the action that 'benefit' the society but not to one particular individual. The quality of benefit that involve here should be sustain forever, in other words the 'san' is and act that truely benefit the others.

Just In Time (JIT) Manufacturing

Just In Time (JIT) Manufacturing

A planning system for manufacturing processes that optimizes availability of material inventories at the manufacturing site to only what, when & how much is necessary.

Typically a JIT Mfg. avoids the conventional Conveyor Systems. JIT is a pull system where the product is pulled along to its finish, rather than the conventional mass production which is a push system. It is possible using various tools like KANBAN, ANDON & CELL LAYOUT.
Others tools include: shojinka, smed, jidoka, poka-yoka, and kaizen.

ISO 9000 Series of Standards

ISO 9000 Series of Standards

Series of standards established in the 1980s by countries of Western Europe as a basis for judging the adequacy of the quality control systems of companies.

Inspection Plan

Inspection Plan

What is an inspection plan:
a. check machine tool for accuracy
b. select the critical and important dimensions to inspect
c. select the measuring insturments
d. construct SPC charts for all dimensions

This is part of NIMS certification for H.S. machine shop teachers and I could use some help! Thanks Jim
----------------------

The general purposes of a Plan are these: To identify the goal(s) to be achieved; to specify the best route (methods, processes ...) for arriving at the goal(s); to catalogue resources (tools, time ...) needed to pursue the chosen route; to assign responsibilities for controlling and consuming those resources; and to secure agreement by relevant stakeholders. (This is *not* an exclusive list!)

See further under Software Inspection Plan.

Inspection

Inspection

See *Fagan-style Inspection*, *Software Inspection*

Note: 'Inspection' outside of the software field may have a different -- and negative -- connotation equivalent to software 'testing'. It was the latter type of inspection that Deming condemned when he wrote, 'We must cease dependence on mass inspection' as a quality management technique.

Incoming Goods Inspection

Incoming Goods Inspection

Incoming Goods Inspection (IGI)

A verification check if the product arrived in good condition at your warehouse before accepting them into your stock. In some cases additional measurements are required to verify if the product is according to the desired specification, but in general it means checking if the boxes are OK, the labels are there in the right place, the quantity is OK, etc., etc. The functionality is, or should be, guaranteed and proved with a measurement report from the vendor.

ICT

ICT

Information Communication Technology

Histogram

Histogram

A bar graph of a frequency distribution in which the widths of the bars are proportional to the classes into which the variable has been divided and the heights of the bars are proportional to the class frequencies.

A histogram is a basic graphing tool that displays the relative frequency or occurrence of continuous data values showing which values occur most and least frequently. A histogram illustrates the shape, centering, and spread of data distribution and indicates whether there are any outliers.

A graphic way to summarize data. Size is shown on the horizontal axis (in cells) and the frequency of each size is shown on the vertical axis as a bar graph. The length of the bars is proportional to the relative frequencies of the data falling into each cell and the width is the range of the cell. Data is variable measurements from a process.

Green Belt

Green Belt

An employee of an organization who has been trained on the improvement methodology of Six Sigma and will lead a process improvement or quality improvement team as *part* of their full time job. Their degree of knowledge and skills associated with Six Sigma is less than that of a Black Belt or Master Black Belt. Extensive product knowledge in their company is a must in their task of process improvement.
The green belt employee plays an important role in executing the Six Sigma process at an organization level.

Goal

Goal

1. A goal is a targeted value by a design team while building a quality process/product.

2. A goal can also be defined as a customer voice. What the customer is asking for or specifying.

The goal must be SMART: See S.M.A.R.T. in this dictionary.

A Goal is a targeted result of a process (design or currently running). In a service Industry, the goal can be satisfaction of the Customer. In layman language, the goal has to be achieved by doing an assignment, job, errand, etc. For example, achieving complimentry satisfaction from people eating food you have cooked. That is your goal.

Globalization

Globalization

Social, economical, environmetal and technological perspectives to the many cultures that exist in the world.

Failure Modes and Effects Analysis (FMEA)

Failure Modes and Effects Analysis (FMEA)

A procedure and tools that help to identify every possible failure mode of a process or product, to determine its effect on other sub-items and on the required function of the product or process. The FMEA is also used to rank & prioritize the possible causes of failures as well as develop and implement preventative actions, with responsible persons assigned to carry out these actions.

Failure modes and effects analysis (FMEA) is a disciplined approach used to identify possible failures of a product or service and then determine the frequency and impact of the failure.

First Time Yield - FTY

First Time Yield - FTY

First Time Yield (FTY) is simply the number of good units produced divided by the number of total units going into the process. For example:

You have a process of that is divided into four sub-processes - A, B, C and D. Assume that you have 100 units entering process A. To calculate FTY you would:

1. Calculate the yield (number out of step/number into step) of each step. 2. Multiply these together.

For Example:

100 units enter A and 90 leave. The FTY for process A is 90/100 = .9

90 units go into B and 80 units leave. The FTY for process B is 80/90 = .89

80 units go into C and 75 leave. The FTY for C is 75/80 = .94

75 units got into D and 70 leave. The FTY for D is 70/75 = .93

The total process yield is equal to FTYofA * FTYofB * FTYofC * FTYofD or .9*.89*.94*.93 = .70.


You can also get the total process yield for the entire process by simply dividing the number of good units produced by the number going in to the start of the process. In this case, 70/100 = .70 or 70 percent yield.

First Time Yield Or First "Pass" Yield Is A Tool For Mearsuring The Amount Of Rework In A Given Process. It Is An Excellent Cost Of Quality Metric.

FIFO

FIFO

First In, First Out. A method of inventory rotation to ensure that the oldest inventory (first in) is used first (first out).

F-Chart

F-Chart

An F-Chart is a chart that carries a significant amount of misleading information, rendering it unfit for the intended analysis. A good example of an F-Chart can be found in the boxplots output of the 2-Sample t-test, and One Way ANOVA in Minitab release 14. The presence of a line connecting the means of each subgroup serves no apparant purpose, and could potentially mislead the reader into thinking that a steep gradient indicates a significant difference. The "F" comes from the latin 'fuccant'.

ERP

ERP

Stands for Enterprise Resource Planning. ERP refers to software packages that attempt to consolidate all the information flowing through the company from finance to human resources. ERP allows companies to standardize their data, streamline their analysis process, and manage long term business planning with greater ease.

Empowerment

Empowerment

A series of actions designed to give employees greater control over their working lives. Businesses give employees empowerment to motivate them according to the theories of Abraham Maslow and Fredrick Herzberg.

To invest with power or give authority to complete. To empower employees.

Being allowed to make decisions and take actions on your own, apart from management.

A contract that involves the delegation of authority and commitment to an individual to act or authorize actions to be taken, in exchange for the acceptance of responsibility and accountability to fulfill a defined objective. Used to increase an organizations responsiveness, effectiveness and efficiency without increasing the budget.

Efficiency

Efficiency

A term denoting to the relationship between outputs and inputs. It requires generating higher outputs as related to inputs. It means enhancing productivity, i.e less rework, less errors and optimal use of resources.

A term indicating the optimization of productivity (measured outputs over measured inputs)typically stated on a 0-100% scale. To improve efficiency, the productivity ratio must be improved (the input to output ratio must be decreased). See definition of productivity.

Effectiveness

Effectiveness

ef·fec·tive Pronunciation Key (-fktv)
adj.

Having an intended or expected effect.
Producing a strong impression or response; striking: gave an effective performance as Othello.
Operative; in effect: The law is effective immediately.
Existing in fact; actual: a decline in the effective demand.
Prepared for use or action, especially in warfare.


Bridging the gap between the society's purposes and the organizational and workers objectives in the organization.

Process output satisfying customer CTQ.

ECR

ECR

Engineering Change Request: A request or suggestion to Engineering for an improvement in a process or procedure.

Eficient Consumer Response: A term used to describe a way of doing business in the grocery industry that involves trading partners.

ECO

ECO

Engineer Change Order...
Engineering changes in procedures that will be implemented in a new revision of a procedure.

Design of Experiments - DOE

Design of Experiments - DOE

A Design of Experiment (DOE) is a structured, organized method for determining the relationship between factors (Xs) affecting a process and the output of that process (Y).

Other Definitions:
1 - Conducting and analyzing controlled tests to evaluate the factors that control the value of a parameter or group of parameters.

2- "Design of Experiments" (DoE) refers to experimental methods used to quantify indeterminate measurements of factors and interactions between factors statistically through observance of forced changes made methodically as directed by mathematically systematic tables.

See DOE for further information.

Design For Manufacturing and Assembly (DFMA)

Design For Manufacturing and Assembly (DFMA)

A methodology and tool set used to determine how to simpilify a current or future product design and/or manufacturing process to achieve cost savings. DFMA allows for improved supply chain cost management, product quality and manufacturing, and communication between Design, Manufacturing, Purchasing and Management.

Deming Cycle, PDCA

Deming Cycle, PDCA

The Deming Cycle, or PDCA Cycle (also known as PDSA Cycle), is a continuous quality improvement model consisting out of a logical sequence of four repetitive steps for continuous improvement and learning: Plan, Do, Study (Check) and Act. The PDSA cycle (or PDCA) is also known as the Deming Cycle, the Deming wheel of continuous improvement spiral. Its origin can be traced back to the eminent statistics expert Mr. Walter A. Shewart, in the 1920’s. He introduced the concept of PLAN, DO and SEE. The late Total Quality Management (TQM) guru and renowned statistician Edward W. Deming modified the SHEWART cycle as: PLAN, DO, STUDY, and ACT.

Along with the other well-known American quality guru-J.M. Juran, Deming went to Japan as part of the occupation forces of the allies after World War II. Deming taught a lot of Quality Improvement methods to the Japanese, including the usage of statistics and the PLAN, DO, STUDY, ACT cycle.

The Deming cycle, or PDSA cycle:

PLAN: plan ahead for change. Analyze and predict the results.
DO: execute the plan, taking small steps in controlled circumstances.
STUDY: check, study the results.
ACT: take action to standardize or improve the process.

Benefits of the PDSA cycle:

- Daily routine management-for the individual and/or the team
- Problem-solving process
- Project management
- Continuous development
- Vendor development
- Human resources development
- New product development
- Process trials

Defects Per Unit - DPU

Defects Per Unit - DPU

DPU or Defects Per Unit is the average number of defects observed when sampling a population.
DPU = Total # of Defects / Total population

Consider 100 electronic assemblies going through a functional test. If 10 of these fail the first time around, we have a first pass yield of 90%. Let's say the 10 fails get reworked and re-tested and 5 pass the second time around; the 5 remaining fails pass on the third attempt. Feel free to work out how this would look as a rolling yield. (100 'passes'/115 tests).

DPU takes a fundamentally different approach to the traditional measurement of yield. It is simply a ratio of the number of defects over the number of units tested (don't worry about how many tests or how many opportunities for defects).

In the above example, the DPU is 15/100 or 0.15. There are 100 units which were found to have a cumulative total of 15 defects when tested.

One interesting feature of DPU is that if you have sequential test nodes, i.e. if the above 100 units had to go through 'Final Test' and threw up a DPU figure of 0.1 there, you simply add the DPU figures from both nodes to get the overall DPU of 0.25 (this is telling you that there were 25 defects in your 100 units). There are a few assumptions which must be realised for this statement to be wholly accurate, but there isn't really time to go there in a 'definition' space.

_________________
If out of the 100 loans applications there are 30 defects, the FTT yield is .70 or 70 percent. Further investigation finds that 10 of the 70 had to be reworked to achieve that yield so our Rolled Throughput Yield is 100-(30+10)/100 = .6 or 60 percent yield.

To consider the defects per unit in this process we divide the number of defects by the result of multiplying the sample by the number of opportunities in each item.

No.of defects/(no. of units)*(no. of opportunities for a defect)= 30/100*3 = 30/300 = .1 or we would say that there is a 10 percent chance for a defect to occur in this process.

Defects Per Million Opportunities - DPMO

Defects Per Million Opportunities - DPMO

Defects per million opportunities (DPMO) is the average number of defects per unit observed during an average production run divided by the number of opportunities to make a defect on the product under study during that run normalized to one million.

Defects Per Million Opportunities. Synonymous with PPM.

To convert DPU to DPMO, the calculation step is actually DPU/(opportunities/unit) * 1,000,000.

Defective

Defective

The word defective describes an entire unit that fails to meet acceptance criteria, regardless of the number of defects within the unit. A unit may be defective because of one or more defects.

Defect

Defect

Any type of undesired result is a defect.

A failure to meet one of the acceptance criteria of your customers. A defective unit may have one or more defects.

'A defect is a failure to conform to requirements' (Crosby, 'Quality Is Free'), whether or not those requirements have been articulated or specified.

The non-conformance to intended usage requirement.

Cycle Time

Cycle Time

Cycle time is the total time from the beginning to the end of your process, as defined by you and your customer. Cycle time includes process time, during which a unit is acted upon to bring it closer to an output, and delay time, during which a unit of work is spent waiting to take the next action.

In a nutshell - Cycle Time is the total elapsed time to move a unit of work from the beginning to the end of a physical process. (Note, Cycle Time is not the same as Lead Time).

Customer Requirements

Customer Requirements

The wants or voice-of-customer in Stated or ImpliedTerms.

Most of the times the customer is enabled to state the requirements precisely. (Like please bring me a glass of luke warm water to drink). However customer may not always be able to precisely state or equipped to realize the basic attributes of his requirements. It is therefore the responsibility of the supplier to reconsider the attributes of desired/ supplied product in terms of the 'implied or real' requirements. For example the hygiene of the environment in which food is cooked in a resturant.

Cpk

Cpk

Process Capability index ('equivalent') taking account of off-centredness: effectively the Cp for a centered process producing a similar level of defects - the ratio between permissible deviation, measured from the mean value to the nearest specific limit of acceptability, and the actual one-sided 3 x sigma spread of the process. As a formula, Cpk = either (USL-Mean)/(3 x sigma) or (Mean-LSL)/(3 x sigma) whichever is the smaller (i.e. depending on whether the shift is up or down). Note this ignores the vanishingly small probability of defects at the opposite end of the tolerance range. Cpk of at least 1.33 is desired.

Capability analysis indice.

Cp

Cp

Process Capability index: a measure of the ability of a process to produce consistent results - the ratio between the permissible spread and the actual spread of a process. Permissible spread is the difference between the upper and lower specific limits of acceptibility (a.k.a. total tolerance); actual spread is defined, arbitrarily, as the difference between upper and lower 3 x sigma deviations from the mean value (representing 99.7% of the normal distribution). As a formula, Cp = (USL-LSL)/(6 x sigma). Note this takes no account of how well the output is centered on the target (nominal) value. For that see Cpk.

You can think of the process capability index Cp in 3 ways:

1. Cp measures the capability of a process to meet its specification limits. It is the ratio between the required and actual variability.

2. More mathematically, the Cp is the ratio of the Spec difference (upper - lower) divided by 6-sigma, which is the spread of a normal curve. Minitab gives the following explanation: 'Capability statistics are basically a ratio between the allowable process spread (the width of the specification limits) and the actual process spread (6s)'

3. Graphically, think of positioning a normal curve centered between the specs. Now look at the tail areas that exceeds the specs. The smaller the area, the larger the Cp. In this sense it is equivalent to looking at the popular PPM measure (parts-per-million) which gives the area of the normal curve that exceeds the specs.

Correction versus Corrective Action

Correction versus Corrective Action

Correction is taken to rectify a known nonconformance; Corrective Action is taken to prevent recurrence of said nonconformance.

Control Chart

Control Chart

A graphical tool for monitoring changes that occur within a process, by distinguishing variation that is inherent in the process(common cause) from variation that yield a change to the process(special cause). This change may be a single point or a series of points in time - each is a signal that something is different from what was previously observed and measured.

Coefficient of Variation

Coefficient of Variation

Coefficient of variation is defined as the relative measure of dispersion it relates the mean and standard deviation by expressing the Std deviation as a % of mean. The benefit of standard deviation is a absolute measure which explains the dispersion in the same unit as original data.

CMM

CMM

The Capability Maturity Model for Software (also known as the CMM and SW-CMM) has been a model used by many organizations to identify best practices useful in helping them increase the maturity of their processes.

Also: Co-ordinate Measuring Machine is a CNC measuring machine capable of performing Reverse engineering and Dimentional inspection of Critical components.

Capability Analysis

Capability Analysis

Capability analysis is a graphical or statistical tool that visually or mathematically compares actual process performance to the performance standards established by the customer.

To analyze (plot or calculate) capability you need the mean and standard deviation associated with the required attribute in a sample of product (usually n=30), and customer requirements associated with that product.

See the tool Capability Analysis.

CAPA

CAPA

Acronym for Corrective and Preventive Action.

Corrective action:
Action taken to eliminate the cause of the existing non-conformity to prevent its recurrence.

Preventive action:
Action taken to eliminate the cause of potential non-conformity.

Both of these are prevention oriented.

The quick fix type actions are called as corrections

Calibration

Calibration

Calibration is simply the comparison of instrument performance to a standard of known accuracy. It may simply involve this determination of deviation from nominal or include correction (adjustment) to minimize the errors. Properly calibrated equipment provides confidence that your products/services meet their specifications. Calibration:

increases production yields,
optimizes resources,
assures consistency and
ensures measurements (and perhaps products) are compatible with those made elsewhere.

Business Process Quality Management

Business Process Quality Management

Also called Process Management or Reengineering. The concept of defining macro and micro processes, assigning ownership, and creating responsibilities of the owners.

Bias

Bias

Bias in a sample is the presence or influence of any factor that causes the population or process being sampled to appear different from what it actually is. Bias is introduced into a sample when data is collected without regard to key factors that may influence it. A one line description of bias might be: "It is the difference between the observed mean reading and reference value."

Benchmarking

Benchmarking

The concept of discovering what is the best performance being achieved, whether in your company, by a competitor, or by an entirely different industry.

Benchmarking is an improvement tool whereby a company measures its performance or process against other companies' best practices, determines how those companies achieved their performance levels, and uses the information to improve its own performance.

Benchmarking is a continuous process whereby an enterprise measures and compares all its functions, systems and practices against strong competitors, identifying quality gaps in the organization, and striving to achieve competitive advantage locally and globally.

Audit

Audit

A timely process or system, inspection to ensure that specifications conform to documented quality standards. An Audit also brings out discrepencies between the documented standards and the standards followed and also might show how well or how badly the documented standards support the processes currently followed.

Corrective, Preventive & Improvement Actions should be undertaken to mitigate the gap(s) between what is said (documented), what is done and what is required to comply with the appropriate quality standard. Audit is not only be used in accounting or something that relates to mathematics but also used in Information Technology.

APQP

APQP

Advanced Product Quality Planning

Phase 1 -
Plan & Define Programme - determining customer needs, requirements & expectations using tools such as QFD
review the entire quality planning process to enable the implementation of a quality programme how to define & set the inputs & the outputs.

Phase 2 -
Product Design & Development - review the inputs & execute the outputs, which include FMEA, DFMA, design verification, design reviews, material & engineering specifications.

Phase 3 -
Process Design & Development - addressing features for developing manufacturing systems & related control plans, these tasks are dependent on the successful completion of phases 1 & 2 execute the outputs.

Phase 4 -
Product & Process Validation - validation of the selected manufacturing process & its control mechanisms through production run evaluation outlining mandatory production conditions & requirements identifying the required outputs.

Phase 5 -
Launch, Feedback, Assessment & Corrective Action - focuses on reduced variation & continuous improvement identifying outputs & links to customer expectations & future product programmes.

Control Plan Methodology -
discusses use of control plan & relevant data required to construct & determine control plan parameters
stresses the importance of the control plan in the continuous improvement cycle.

Acceptable Quality Level - AQL

Acceptable Quality Level - AQL

Acceptable Quality Level. Also referred to as Assured Quality Level. The largest quantity of defectives in a certain sample size that can make the lot definitely acceptable; Customer will definitely prefer the zero defect products or services and will ultimately establish the acceptable level of quality. Competition however, will 'educate' the customer and establish the customer's values. There is only one ideal acceptable quality level - zero defects - all others are compromises based upon acceptable business, financial and safety levels.

7 QC Tools

7 QC Tools

Histograms
Cause and Effect Diagram
Check Sheets
Pareto Diagrams
Graphs
Control Charts
Scatter Diagrams

These are 7 QC tools also known as ISHIKAWAS 7QC tools which revolutionised the Japane & the World in Sixties & Seventies

5 Why's

The 5 why's typically refers to the practice of asking, five times, why the failure has occurred in order to get to the root cause/causes of the problem. There can be more than one cause to a problem as well. In an organizational context, generally root cause analysis is carried out by a team of persons related to the problem. No special technique is required.

An example is in order:
You are on your way home from work and your car stops:


Why did your car stop? Because it ran out of gas.


Why did it run out of gas? Because I didn't buy any gas on my way to work.


Why didn't you buy any gas this morning? Because I didn't have any money.


Why didn't you have any money? Because I lost it all last night in a poker game.

I hope you don't mind the silly example but it should illustrate the importance of digging down beneath the most proximate cause of the problem. Failure to determine the root cause assures that you will be treating the symptoms of the problem instead of its cause, in which case, the disease will return, that is, you will continue to have the same problems over and over again.

Also note that the actual numbers of why's is not important as long as you get to the root cause. One might well ask why did you lose all your money in the poker game last night?

_____
Here's another example. I learned the example using the Washington Monument used when demonstrating the use of the 5 Whys.

The Washington Monument was disintegrating
Why? Use of harsh chemicals
Why? To clean pigeon poop
Why so many pigeons? They eat spiders and there are a lot of spiders at monument
Why so many spiders? They eat gnats and lots of gnats at monument
Why so many gnats? They are attracted to the light at dusk.
Solution: Turn on the lights at a later time.

5S

5S

5S is the Japanese concept for House Keeping.

1.) Sort (Seiri)
2.) Straighten (Seiton)
3.) Shine (Seiso)
4.) Standardize (Seiketsu)
5.) Sustain (Shitsuke)
____________________________________________
I think the concept of 5S has been twisted and its real meaning and intention has been lost due to attempts to keep each element in English word to start with letter 'S', like the real Nippongo words (seiri, seiton, seiso, seiketsu, and shitsuke). Well, whoever deviced those equivalent English words did a good job,they're close, but the real interpretation is not exactly the correct one. For the benefit of the readers who would like to develop and establish their own understanding and applications, the following are the real meaning of each element in English:

Japanese - English Translations
-------- --------------------
Seiri - Put things in order
(remove what is not needed and keep what is needed)
Seiton - Proper Arrangement
(Place things in such a way that they can be easily reached whenever they are needed)
Seiso - Clean
(Keep things clean and polished; no trash or dirt in the workplace)
Seiketsu - Purity
(Maintain cleanliness after cleaning - perpetual cleaning)
Shitsuke - Commitment (Actually this is not a part of '4S', but a typical teaching and attitude towards any undertaking to inspire pride and adherence to standards established for the four components)
____________________________________________

Surface-mount technology

Surface mount technology (SMT) is a method for constructing electronic circuits in which the components are mounted directly onto the surface of printed circuit boards (PCBs). Electronic devices so made are called surface-mount devices or SMDs. In the industry it has largely replaced the previous construction method of fitting components with wire leads into holes in the circuit board (also called through-hole technology).

An SMT component is usually smaller than its leaded counterpart because it has no leads or smaller leads. It may have short pins or leads of various styles, flat contacts, a matrix of balls (BGAs), or terminations on the body of the component (passives).

Contents
1 History
2 Assembly techniques
3 Main advantages
4 Main disadvantages
5 Reworking defective surface mount components
6 Package sizes
7 Manufacturers
8 See also
9 External links



History
Surface-mount technology was developed in the 1960s and became widely used in the late 1980s. Much of the pioneering work in this technology was done at IBM. Components were mechanically redesigned to have small metal tabs or end caps that could be directly soldered to the surface of the PCB. Components became much smaller and component placement on both sides of the board became far more common with surface-mounting than through-hole mounting, allowing much higher circuit densities. Often, only the solder joints hold the parts to the board, although parts on the bottom or "second" side of the board are temporarily secured with a dot of adhesive as well. Surface-mounted devices (SMDs) are usually made physically small and lightweight for this reason. Surface mounting lends itself well to a high degree of automation, reducing labor cost and greatly increasing production rates. SMDs can be one-quarter to one-tenth the size and weight, and one-half to one-quarter the cost of through-hole parts.


Assembly techniques
Where components are to be placed, the printed circuit board has flat, usually tin-lead, silver or gold plated copper pads without holes, called solder pads. Solder paste, a sticky mixture of flux and tiny solder particles, is first applied to all the solder pads with a stainless steel stencil. If components are to be mounted on the second side, a numerically controlled (NC) machine places small liquid adhesive dots at the locations of all second-side components. The boards then proceed to the pick-and-place machines, where they are placed on a conveyor belt. Small SMDs are usually delivered to the production line on paper or plastic tapes wound on reels. Integrated circuits are typically delivered stacked in static-free plastic tubes or trays. NC pick-and-place machines remove the parts from the reels or tubes and place them on the PCB. Second-side components are placed first, and the adhesive dots are quickly cured with application of low heat or ultraviolet radiation. The boards are flipped over and first-side components are placed by additional NC machines.

The boards are then conveyed into the reflow soldering oven. They first enter a pre-heat zone, where the temperature of the board and all the components is gradually, uniformly raised. This helps minimize thermal stresses when the assemblies cool down after soldering. The boards then enter a zone where the temperature is high enough to melt the solder particles in the solder paste, bonding the component leads to the pads on the circuit board. The surface tension of the molten solder helps keep the components in place, and if the solder pad geometries are correctly designed, surface tension automatically aligns the components on their pads. There are a number of techniques for reflowing solder. One is to use infrared lamps; this is called infrared reflow. Another is to use a hot gas. At one time special fluorocarbon liquids with high boiling points were used, a method called vapor phase reflow. Due to environmental concerns, this method is falling out of favor. Today, it is more common to use nitrogen gas or nitrogen gas enriched air in a convection oven. Each method has its advantages and disadvantages. With infrared reflow, the board designer must lay the board out so that short components don't fall into the shadows of tall components. Component location is less restricted if the designer knows that vapor phase reflow or convection soldering will be used in production. Following reflow soldering, certain irregular or heat-sensitive components may be installed and soldered by hand, or in large scale automation, by focused infrared beam (FIB) equipment.

After soldering, the boards are washed to remove flux residue and any stray solder balls that could short out closely spaced component leads. Rosin flux is removed with fluorocarbon solvents, high flash point hydrocarbon solvents, or limonene, derived from orange peels. Water soluble fluxes are removed with deionized water and detergent, followed by an air blast to quickly remove residual water. When aesthetics are unimportant and the flux doesn't cause shorting or corrosion, flux residues are sometimes left on the boards, saving the cost of cleaning and eliminating the waste disposal.

Finally, the boards are visually inspected for missing or misaligned components and solder bridging. If needed, they are sent to a rework station where a human operator corrects any errors. They are then sent to the testing stations to verify that they work correctly.


Main advantages
The main advantages of SMT over the older through-hole technique are:

smaller, lighter components
fewer holes need to be drilled through abrasive boards
simpler automated assembly
small errors in component placement are corrected automatically (the surface tension of the molten solder pulls the component into alignment with the solder pads)
components can be fitted to both sides of the circuit board
lower lead resistance and inductance (leading to better performance for high frequency parts)
better mechanical performance under shake and vibration conditions.
SMT parts generally cost less than through-hole parts

Main disadvantages
The one major disadvantage of SMT is the difficulty in manual handling due to the very small sizes and lead spacings of SMDs, making component-level repair of devices using it extremely difficult, and often uneconomical.


Reworking defective surface mount components
Defective surface mount components can be repaired by using a rework system. A rework process usually undoes some type of error, either human or machine-generated, and includes the following steps:

Melt solder and component removal
Residual solder removal
Printing of solder paste on PCB, direct component printing or dispensing
Placement and reflow of new component
Sometimes hundreds or thousands of the same part need to be repaired. Such errors, if due to assembly, are often caught during the process. But a whole new level of rework arises when: component failure is discovered too late, design defects go unnoticed until the end user experiences them, high-value products require revisions re-engineering change orders can revive a once-obsolete product, or firmware updates require the change of only a single die to reuse a product. These tasks require a rework operation specifically designed to repair/replace components in volume.

Package sizes
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It may be using the words or ideas of other publications in its text, without citing the source(s) of the information.
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MLP package 28-pin chip
32-pin MQFP chip being manually soldered for prototyping purposes
Various SMD chips, desoldered
SMD capacitors (left side), along with two through-hole capacitors (right side)Surface-mount components are usually much smaller than their leaded counterparts, and are designed to be handled by machines rather than by humans. The electronics industry has defined a collection of standard package shapes and sizes (the leading standardisation body is JEDEC). These include:

Two terminals packages
Rectangular passive components (mostly resistors and capacitors):
01005 - 0.016" × 0.008" (0.4 mm × 0.2 mm)
0201 - 0.024" × 0.012" (0.6 mm × 0.3 mm)
0402 - 0.04" × 0.02" (1.0 mm × 0.5 mm)
0603 - 0.063" × 0.031" (1.6 mm × 0.8 mm)
0805 - 0.08" × 0.05" (2.0 mm × 1.25 mm)
1206 - 0.126" × 0.063" (3.2 mm × 1.6 mm)
1812 - 0.18" × 0.12" (4.6 mm × 3.0 mm)
2512 - 0.25" × 0.12" (6.3 mm × 3.0 mm)
Tantalum capacitors:
Size A (EIA 3216-18): 3.2 mm × 1.6 mm × 1.6 mm
Size B (EIA 3528-21): 3.5 mm × 2.8 mm × 1.9 mm
Size C (EIA 6032-28): 6.0 mm × 3.2 mm × 2.2 mm
Size D (EIA 7343-31): 7.3 mm × 4.3 mm × 2.4 mm
Size E (EIA 7343-43): 7.3 mm × 4.3 mm × 4.1 mm
SOD - Small outline diode [1]
SOD-323: 1.7 × 1.25 × 0.95 mm
SOD-123: 3.68 × 1.17 × 1.60 mm
SOD-80C: 3.50mm × 1.50mm × More info [2]
MELF—Metal ELectrical Face - (mostly resistors and diodes): Barrel shaped components, dimensions do not match those of rectangular references for identical codes.
Size 0201: L:2.2mm D:1.1mm (solder pad fits rectangular 0805)
Size 0204: L:3.6mm D:1.4mm (solder pad fits rectangular 1206)
Size 0207: L:5.8mm D:2.2mm
Three terminals packages
SOT - small-outline transistor, with three terminals [3]
SOT-23 - 3 mm × 1.75 mm × 1.3 mm body - three terminals for a transistor, or up to eight terminals for an integrated circuit
SOT-223 - 6.7 mm × 3.7 mm × 1.8 mm body - four terminals, one of which is a large heat-transfer pad
DPAK (TO-252) - discrete packaging. Developed by Motorola to house higher powered devices. Comes in three- or five-terminal versions [4]
D2PAK (TO-263) - bigger than the DPAK; basically a surface mount equivalent of the TO220 through-hole package. Comes in 3, 5, 6, 7, or 8-terminal versions [5]
D3PAK (TO-268) - even larger than D2PAK [6]
Packages with four or more terminals (drawings of most of the following packages can be found on [7])
Dual-in-line
Small-Outline Integrated Circuit (SOIC) - small-outline integrated circuit, dual-in-line, 8 or more pins, gull-wing lead form, pin spacing 1.27 mm
TSOP - thin small-outline package, thinner than SOIC with smaller pin spacing of 0.5 mm
SSOP - shrink small-outline package, pin spacing of 0.635 mm or in some cases 0.8mm
TSSOP - thin shrink small-outline package.
QSOP - quarter-size small-outline package, with pin spacing of 0.635 mm
VSOP - even smaller than QSOP; 0.4, 0.5 mm or 0.65 mm pin spacing
Quad-in-line
PLCC - plastic leaded chip carrier, square, J-lead, pin spacing 1.27 mm
QFP - Quad Flat Package, various sizes, with pins on all four sides
LQFP - Low-profile Quad Flat Package, 1.4 mm high, varying sized and pins on all four sides
PQFP - plastic quad flat-pack, a square with pins on all four sides, 44 or more pins
CQFP - ceramic quad flat-pack, similar to PQFP
MQFP - Metric Quad Flat Pack, a QFP package with metric pin distribution
TQFP - thin quad flat pack, a thinner version of PQFP
QFN - quad flat pack, no-leads, smaller footprint than leaded equivalent
MLP - Leadframe package with a 0.5 mm contact pitch, no leads [8]
PQFN - power quad flat-pack, no-leads, with exposed die-pad[s] for heatsinking
Grid arrays
BGA - ball grid array, with a square or rectangular array of solder balls on one surface, ball spacing typically 1.27 mm
LFBGA - low profile fine pitch ball grid array, with a square or rectangular array of solder balls on one surface, ball spacing typically 0.8 mm
CGA - column grid array, circuit package in which the input and output points are high temperature solder cylinders or columns arranged in a grid pattern.
CCGA - ceramic column grid array, circuit package in which the input and output points are high temperature solder cylinders or columns arranged in a grid pattern. The body of the component is ceramic.
μBGA - micro-BGA, with ball spacing less than 1 mm
LLP - Lead Less Package, a package with metric pin distribution (0.5 mm pitch).
Non-packaged devices (although surface mount, these devices require specific process for assembly):
COB - chip-on-board; a bare silicon chip, that is usually an integrated circuit, is supplied without a package (usually a lead frame overmolded with epoxy) and is attached, often with epoxy, directly to a circuit board. The chip is then wire bonded and protected from mechanical damage and contamination by an epoxy "glob-top".
COF - chip-on-flex; a variation of COB, where a chip is mounted directly to a flex circuit.
COG - chip-on-glass; a variation of COB, where a chip is mounted directly to a piece of glass - typically an LCD display.

There are often subtle variations in package details from manufacturer to manufacturer, and even though standard designations are used, designers need to confirm dimensions when laying out printed circuit boards.


Manufacturers
Companies producing SMT based printed circuit boards include:

Celestica
Flextronics
Solectron

ISO 14001 2004

ISO 14001 2004
ENVIRONMENTAL MANAGEMENT STANDARD
TRANSLATED INTO PLAIN ENGLISH


ISO 14001 2004 is an environmental management standard. It specifies
a set of environmental management requirements for environmental
management systems. The purpose of this standard is to help all
types of organizations to protect the environment, to prevent
pollution, and to improve their environmental performance.

OTHER PLAIN ENGLISH STANDARDS
NEW ISO 22000 Food Safety Management Standard NEW

ISO 9001 2000 Quality Management System Standard

ISO 13485 2003 Medical Device Management Standard

ISO 17799 Information Security Management Standard

ISO 27001 Information Security Management Standard

ISO 90003 Software Quality Management Standard

NFPA 1600 Business Continuity Management Standard




This page presents a detailed preview of the ISO 14001 2004 standard.
However, it does not present the entire standard. If you need a detailed
and complete interpretation of the ISO 14001 2004 environmental
management standard, please consider purchasing our
Title 50: ISO 14001 2004 Translated into Plain English.

ISO 14001 presents environmental management requirements in
section 4. Therefore, the following material begins with section 4.

ISO 14001 ENVIRONMENTAL MANAGEMENT REQUIREMENTS


4.1 Systemic requirements
Establish an environmental management system
that complies with the ISO 14001 2004 standard.

Document your environmental management system
in accordance with the ISO 14001 2004 standard.

Implement your environmental management system
in accordance with the ISO 14001 2004 standard.

Maintain your environmental management system
in accordance with the ISO 14001 2004 standard.

Continually improve your environmental management
system in accordance with the ISO 14001 2004 standard.




4.2 Policy requirements
Establish your organization’s environmental policy.

Define your organization’s environmental policy.

Document your organization’s environmental policy.

Implement your organization’s environmental policy.

Maintain your organization’s environmental policy.

Communicate your organization’s environmental policy.




4.3 Planning requirements
4.3.1 Identify your environmental aspects.

Establish procedures to identify the environmental
aspects of your activities, products, and services.

Implement procedures to identify the environmental
aspects of your activities, products, and services.

Document the environmental aspects of your
organization’s activities, products, and services.

Maintain procedures to identify the environmental
aspects of your activities, products, and services.

4.3.2 Clarify legal and other requirements.

Establish procedures to identify and clarify
the legal and other requirements that apply
to your organization’s environmental aspects.

Implement procedures to identify and clarify the legal and other requirements that apply to your organization’s environmental aspects.

Maintain procedures to identify and clarify the legal and other requirements that apply to your organization’s environmental aspects.

4.3.3 Establish objectives and programs.

Establish environmental objectives and targets.

Implement environmental objectives and targets.

Maintain environmental objectives and targets.

Establish programs to achieve your organization's
environmental objectives and targets.

Implement programs to achieve your
environmental objectives and targets.

Maintain programs to achieve your
environmental objectives and targets.




4.4 Operational requirements
4.4.1 Provide resources and establish jobs.

Provide the resources needed to support your
organization’s environmental management system.

Provide the resources needed to establish
your environmental management system.

Provide the resources needed to implement
your environmental management system.

Provide the resources needed to maintain
your environmental management system.

Provide the resources needed to improve
your environmental management system.

Establish environmental management
roles, responsibilities, and authorities.

Define your environmental management
roles, responsibilities, and authorities.

Document your environmental management
roles, responsibilities, and authorities.

Communicate your environmental management
roles, responsibilities, and authorities.

Appoint someone to assume the role
of management representative.

4.4.2 Deliver training and awareness programs.

Make sure that people, who perform tasks that could potentially
have a significant environmental impact, are in fact competent.

Establish your environmental training programs.

Identify your organization’s
environmental training needs.

Deliver training programs that meet
your environmental training needs.

Maintain a record of your organization’s
environmental training activities.

Establish a procedure to make people aware
of your environmental management system.

Implement your environmental awareness procedure.

Maintain your environmental awareness procedure.

4.4.3 Establish communication procedures.

Establish a procedure to control your organization’s
internal environmental communications.

Implement your organization’s internal
environmental communications procedure.

Maintain your organization’s internal
environmental communications procedure.

Establish a procedure to control your organization’s
external environmental communications.

Implement your organization’s external
environmental communications procedure.

Maintain your organization’s external
environmental communications procedure.

4.4.4 Document your environmental management system.

Document your organization’s environmental policy.

Document your organization’s environmental objectives.

Document your organization’s environmental targets.

Document the scope of environmental management system.

Document the main parts of environmental management system.

Describe how the parts of your organization's
environmental management system interact.

4.4.5 Control environmental management documents.

Control documents required
by the ISO 14001 2004 standard.

Control documents required by your
environmental management system.

Control your environmental
management system records.

4.4.6 Control environmentally significant operations.

Identify those operations that are associated with your
organization’s significant environmental aspects.

Establish procedures to manage and control operational
situations that could have significant environmental impacts.

Document your environmental
operational control procedures.

Implement your environmental
operational control procedures.

Maintain your environmental
operational control procedures.

Establish procedures to control the significant
environmental aspects of the goods and services
provided by your suppliers and contractors.

Implement your environmental supplier
and contractor control procedures.

Maintain your environmental supplier
and contractor control procedures.

4.4.7 Establish an emergency management process.

Prepare for emergency situations and accidents that
could have a significant impact on the environment.

Establish procedures to identify potential emergency situations
and accidents that could have an impact on the environment.

Implement procedures to identify potential emergency situations and accidents that could have an impact.

Maintain procedures to identify potential emergency
situations and accidents that could have an impact
on the environment.

Establish procedures to respond to actual emergency situations
and accidents that have an impact on the environment.

Implement procedures to respond to actual emergency situations and accidents that have an impact.

Maintain procedures to respond to actual emergency
situations and accidents that have an impact on the environment.

Test your environmental emergency response procedures.

Respond to actual environmental emergencies and accidents.

Prevent or mitigate the adverse environmental impacts
that emergencies and accidents can and do cause.

Review and revise your environmental emergency
preparedness and response procedures.




4.5 Checking requirements
4.5.1 Establish monitoring and measurement capabilities.

Establish procedures to monitor and measure
the operational characteristics that could have
a significant impact on the environment.

Implement your organization's environmental
monitoring and measuring procedures.

Maintain your organization's environmental
monitoring and measuring procedures.

Use calibrated or verified environmental
monitoring and measuring equipment.

Maintain your organization’s environmental
monitoring and measuring equipment.

Keep a record of your environmental
monitoring and measuring activities.

4.5.2 Evaluate legal and other compliance.

4.5.2.1 Evaluate compliance with legal requirements.

Establish a procedure to periodically evaluate
how well your organization complies with all
relevant legal environmental requirements.

Implement a procedure to periodically evaluate
how well your organization complies with all relevant legal environmental requirements.

Maintain a procedure to periodically evaluate
how well your organization complies with all
relevant legal environmental requirements.

Record the results of your organization's
legal environmental compliance evaluations.

4.5.2.2 Evaluate compliance with other requirements.

Establish a procedure to periodically evaluate how well your
organization complies with other environmental requirements.

Implement a procedure to periodically evaluate
how well your organization complies with other
environmental requirements.

Maintain a procedure to periodically evaluate
how well your organization complies with other
environmental requirements.

Record the results of your organization's other
environmental compliance evaluations.

4.5.3 Deal with your nonconformities.

Establish nonconformance management procedures.

Implement nonconformance management procedures.

Maintain nonconformance management procedures.

Change documents when nonconformities make it necessary.

4.5.4 Control your environmental records.

Establish environmental records for your organization.

Establish procedures to control your environmental records.

Implement procedures to control environmental records.

Maintain procedures to control environmental records.

4.5.5 Perform internal environmental management audits.

Plan the development of an internal
environmental management audit program.

Establish your environmental management audit program.

Implement your internal environmental
management audit program.

Maintain your internal environmental
management audit program.

Establish an environmental management audit procedure.

Implement your internal environmental
management audit procedure.

Maintain your internal environmental
management audit procedure.

Conduct internal audits of environmental management system.

Report internal audit results to your organization’s management.




4.6 Review requirements
Perform environmental management reviews.

Review the suitability, adequacy, and effectiveness
of your environmental management system.

Assess opportunities for improvement.

Assess whether or not your environmental
management system should be changed.

Assess whether or not your organization’s
environmental policy should be changed.

Assess whether or not your organization’s
environmental objectives should be changed.

Assess whether or not your organization’s
environmental targets should be changed.

Keep a record of your environmental reviews.

Carry out reviews by examining your inputs.

Generate environmental review outputs.

ISO 9001 2000

ISO 9001 2000
TRANSLATED INTO PLAIN ENGLISH

ISO/ANSI/ASQ/CSA 9001 2000 QUALITY STANDARD

PAGE 1 OF 2 GO TO PAGE 2


ISO 9001 applies to all types of organizations. It doesn't matter
what size they are or what they do. It can help both product and
service oriented organizations achieve standards of quality
that are recognized and respected throughout the world.

ISO 9001 2000 has replaced the old ISO 9001 1994 standard.
In addition, the old ISO 9002 1994 and ISO 9003 1994 quality
standards have been discontinued. They are now obsolete!

If you're now ISO 9001 1994 certified, you're going to have
to update your quality management system in order to meet
the new ISO 9001 2000 requirements. And if you're now
ISO 9002 or ISO 9003 certified, you're going to have
to become ISO 9001 2000 certified !

OTHER PLAIN ENGLISH STANDARDS
NEW ISO 22000 Food Safety Management Standard NEW

ISO 13485 2003 Medical Device Management Standard

ISO 14001 2004 Environmental Management Standard

ISO 17799 Information Security Management Standard

ISO 27001 Information Security Management Standard

ISO 90003 Software Quality Management Standard

NFPA 1600 Business Continuity Management Standard


These web pages present a detailed introduction to the final version of
ISO 9001 2000. However, they do not present the entire detailed standard.
If you need a detailed and complete interpretation of ISO 9001 2000, please
consider purchasing Title 20: ISO 9001 2000 Translated into Plain English.
Or contact Praxiom Research Group Limited for more information.

Please note that ISO presents requirements in sections 4 to 8 of ISO 9001:2000.
Therefore, the following material begins with section 4. Sections 1 to 3 cover
a variety of introductory and legalistic topics. These additional topics are
discussed in our Title 20: ISO 9001 2000 Translated into Plain English.


--------------------------------------------------------------------------------



ISO 9001 2000




--------------------------------------------------------------------------------

ISO 9001 2000 QUALITY MANAGEMENT STANDARD IN PLAIN ENGLISH
ISO 9001: 4 Systemic Requirements
4.1
Establish
your quality management system (QMS)


Develop your quality management system

Identify the processes that make up your quality system.

Describe your quality management processes.


Implement your quality management system

Use quality system processes.

Manage process performance.


Improve your quality management system

Monitor process performance.

Improve process performance.


4.2
Document
your quality management system (QMS)


4.2.1 Develop quality system documents

Develop documents to implement your quality system.

Develop documents that reflect what your organization does.


4.2.2 Prepare quality system manual

Document your procedures.

Describe how your processes interact.

Define the scope of your quality system.


4.2.3 Control quality system documents

Approve documents before you distribute them.

Provide the correct version of documents at points of use.

Review and re-approve documents whenever you update them.

Specify the current revision status of your documents.

Monitor documents that come from external sources.

Prevent the accidental use of obsolete documents.

Preserve the usability of your quality documents.


4.2.4 Maintain quality system records

Use your records to prove that requirements have been met.

Develop a procedure to control your records.

Ensure that your records are useable.





--------------------------------------------------------------------------------

ISO 9001 2000 QUALITY MANAGEMENT STANDARD IN PLAIN ENGLISH
ISO 9001: 5 Management Requirements
5.1
Support
quality
Promote the importance of quality

Promote the need to meet customer requirements.

Promote the need to meet regulatory requirements.

Promote the need to meet statutory requirements.



Develop a quality management system

Support the development of a quality system.

Formulate your organization's quality policy.

Set your organization's quality objectives.

Provide quality resources.


Implement your quality management system

Provide resources to implement your quality system.

Encourage personnel to meet quality system requirements.



Improve your quality management system

Perform quality management reviews.

Provide resources to improve the quality system.


5.2
Satisfy your customers
Identify customer requirements

Expect your organization to identify customer requirements.



Meet your customers' requirements

Expect your organization to meet customer requirements.



Enhance customer satisfaction

Expect your organization to enhance customer satisfaction.


5.3
Establish a quality policy
Define your organization's quality policy

Ensure that it serves your organization's purpose.

Ensure that it emphasizes the need to meet requirements.

Ensure that it facilitates the development of quality objectives.

Ensure that it makes a commitment to continual improvement.



Manage your organization's quality policy

Communicate your policy to your organization.

Review your policy to ensure that it is still suitable.


5.4
Carry out quality planning
5.4.1 Formulate your quality objectives

Ensure that objectives are set for functional areas.

Ensure that objectives are set at organizational levels.

Ensure that objectives facilitate product realization.

Ensure that objectives support the quality policy.

Ensure that objectives are measurable.



5.4.2 Plan your quality management system

Plan the development of your quality management system.

Plan the implementation of your quality management system.

Plan the improvement of your quality management system.

Plan the modification of your quality management system.


5.5
Control your quality system
5.5.1 Define responsibilities and authorities

Clarify responsibilities and authorities.

Communicate responsibilities and authorities.



5.5.2 Appoint management representative

Oversee your quality management system.

Report on the status of your quality management system.

Support the improvement of your quality management system.



5.5.3 Support internal communications

Ensure that internal communication processes are established.

Ensure that communication occurs throughout the organization.


5.6
Perform management reviews
5.6.1 Review quality management system

Evaluate the performance of your quality system.

Evaluate whether your quality system should be improved.



5.6.2 Examine management review inputs

Examine audit results.

Examine product conformity data.

Examine opportunities to improve.

Examine feedback from customers.

Examine process performance information.

Examine corrective and preventive actions.

Examine changes that might affect your system.

Examine previous quality management reviews.



5.6.3 Generate management review outputs

Generate actions to improve your quality system.

Generate actions to improve your products.

Generate actions to address resource needs.





--------------------------------------------------------------------------------

ISO 9001 2000 QUALITY MANAGEMENT STANDARD IN PLAIN ENGLISH
ISO 9001: 6 Resource Requirements
6.1
Provide quality resources
Identify quality resource requirements

Identify resources needed to support the quality system.

Identify resources needed to improve customer satisfaction.



Provide quality system resources

Provide resources needed to support the quality system.

Provide resources needed to improve customer satisfaction.


6.2
Provide quality personnel
6.2.1 Use competent personnel

Ensure that your personnel have the right experience.

Ensure that your personnel have the right education.

Ensure that your personnel have the right training.

Ensure that your personnel have the right skills.



6.2.2 Support competence

Define acceptable levels of competence.

Identify training and awareness needs.

Deliver training and awareness programs.

Evaluate effectiveness of training and awareness.

Maintain a record of competence.


6.3
Provide quality infrastructure
Identify infrastructure needs

Identify building needs.

Identify workspace needs.

Identify hardware needs.

Identify software needs.

Identify utility needs.

Identify equipment needs.

Identify support service needs.



Provide needed infrastructure

Provide needed buildings.

Provide needed workspaces.

Provide needed hardware.

Provide needed software.

Provide needed utilities.

Provide needed equipment.

Provide needed support services.



Maintain your infrastructure

Maintain your buildings.

Maintain your workspaces.

Maintain your hardware.

Maintain your software.

Maintain your utilities.

Maintain your equipment.

Maintain your support services.


6.4
Provide quality environment
Identify needed work environment

Identify factors needed to ensure products meet requirements.



Manage needed work environment

Manage factors needed to ensure products meet requirements.

Corrective Action and 8_D process

1.1 The eight disciplines are:
1.1.1 D0 – Awareness of the Problem . Customer (at the site or in the field) concern or internal (process, product or system) concern.
1.1.2 D1 – Establish the Team. The team is cross-functional, assuring the right knowledge, skills and experience is represented. All perspectives of the problem are represented (the stakeholders). The team size should be manageable to effectively allow decision making and solutions to be implemented in a timely manner. The characteristics of an effective team should include leadership; commitment; clearly defined goals; objectives & responsibilities; trust and respect; authority; effective listening; time management & effective communication skills.
1.1.3 D2 – Describe the Problem. This is a definitive documented statement of the issue. Steps used to document the problem are collecting facts through the “who, what, when, where, why, how and how many” questioning. This part of the process is factual and describes the gap between what “is” and what should be. It is imperative that the true problem is identified to solve it instead of addressing symptoms.
1.1.4 D3 – Initiate Containment. Immediate actions are taken to identify and contain the product to prevent building and shipping additional products. Verification that the potential actions are capable of containing the problem is required. This part of the evaluation process must include analyzing how far reaching the containment actions need to be (ie internal, customer site, in the field, etc.)
1.1.5 D4 – Identify Root Cause. This is the most difficult and critical part of the 8-D process. The inaccurate identification of the root cause will allow the problem to recur. Common tools used to determine root cause are Fishbone Diagrams, Brainstorming (used for formulating ideas of root cause), Experimentation and Process Flow Analysis. Using the “5 Why?” questioning technique, along with visual observation of the process are important factors in this step.
1.1.6 D5 – Identify and Implement Corrective Action. The action(s) taken to eliminate the cause and to prevent recurrence. The corrective actions must align with the identified root causes, at minimum. The last part of this process is to assure a definitive plan for implementing the actions.
1.1.7 D6 – Verify Corrective Action Effectiveness. The team establishes the verification plan to measure the effectiveness of the implemented actions. This is a data driven process.
1.1.8 D7 – Identify and Implement Action(s) to Prevent Recurrence. This step in the process is the preventive action taken to prevent the problem from recurring again within the workcell, across lines or products in other sites, or globally. Corrective action is a reactive activity while preventive action is a proactive activity. Preventive opportunities are in the updating of Design & Process FMEA’s, Control Plans and Design for Manufacturability. Leveraging and sharing lessons learned within workcells, sites and products and across the globe are where the most benefit is realized.
1.1.9 D8 – Recognize the Team. The efforts and accomplishments are recognized. The CAR is officially closed out.