Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance

SIGNIFICANCE AND USE
This practice can be used to continuously demonstrate the proficiency of analytical measurement systems that are used for establishing and ensuring the quality of petroleum and petroleum products.
Data accrued, using the techniques included in this practice, provide the ability to monitor analytical measurement system precision and bias.
These data are useful for updating test methods as well as for indicating areas of potential measurement system improvement.
SCOPE
1.1 This practice covers information for the design and operation of a program to monitor and control ongoing stability and precision and bias performance of selected analytical measurement systems using a collection of generally accepted statistical quality control (SQC) procedures and tools.  
Note 1—A complete list of criteria for selecting measurement systems to which this practice should be applied and for determining the frequency at which it should be applied is beyond the scope of this practice. However, some factors to be considered include (1) frequency of use of the analytical measurement system, (2) criticality of the parameter being measured, (3) system stability and precision performance based on historical data, (4) business economics, and (5) regulatory, contractual, or test method requirements.
1.2 This practice is applicable to stable analytical measurement systems that produce results on a continuous numerical scale.  
1.3 This practice is applicable to laboratory test methods.
1.4 This practice is applicable to validated process stream analyzers.
1.5 This practice is applicable to monitoring the differences between two analytical measurement systems that purport to measure the same property provided that both systems have been assessed in accordance with the statistical methodology in Practice D6708 and the appropriate bias applied.
Note 2—For validation of univariate process stream analyzers, see also Practice D3764.
Note 3—One or both of the analytical systems in 1.5 can be laboratory test methods or validated process stream analyzers.
1.6 This practice assumes that the normal (Gaussian) model is adequate for the description and prediction of measurement system behavior when it is in a state of statistical control.
Note 4—For non-Gaussian processes, transformations of test results may permit proper application of these tools. Consult a statistician for further guidance and information.

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Publication Date
28-Feb-2010
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NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
Contact ASTM International (www.astm.org) for the latest information
An American National Standard
Designation:D6299–10
Standard Practice for
Applying Statistical Quality Assurance and Control Charting
Techniques to Evaluate Analytical Measurement System
1
Performance
This standard is issued under the fixed designation D6299; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope 2. Referenced Documents
2
1.1 This practice covers information for the design and 2.1 ASTM Standards:
operationofaprogramtomonitorandcontrolongoingstability D3764 Practice for Validation of the Performance of Pro-
and precision and bias performance of selected analytical cess Stream Analyzer Systems
measurement systems using a collection of generally accepted D5191 Test Method for Vapor Pressure of Petroleum Prod-
statistical quality control (SQC) procedures and tools. ucts (Mini Method)
D6708 PracticeforStatisticalAssessmentandImprovement
NOTE 1—Acomplete list of criteria for selecting measurement systems
of Expected Agreement Between Two Test Methods that
towhichthispracticeshouldbeappliedandfordeterminingthefrequency
Purport to Measure the Same Property of a Material
at which it should be applied is beyond the scope of this practice.
D6792 Practice for Quality System in Petroleum Products
However, some factors to be considered include (1) frequency of use of
the analytical measurement system, (2) criticality of the parameter being
and Lubricants Testing Laboratories
measured, (3) system stability and precision performance based on
D7372 Guide forAnalysis and Interpretation of Proficiency
historical data, (4) business economics, and (5) regulatory, contractual, or
Test Program Results
test method requirements.
E177 Practice for Use of the Terms Precision and Bias in
1.2 This practice is applicable to stable analytical measure-
ASTM Test Methods
ment systems that produce results on a continuous numerical
E178 Practice for Dealing With Outlying Observations
scale.
E456 Terminology Relating to Quality and Statistics
1.3 This practice is applicable to laboratory test methods.
E691 Practice for Conducting an Interlaboratory Study to
1.4 This practice is applicable to validated process stream
Determine the Precision of a Test Method
analyzers.
3. Terminology
1.5 This practice is applicable to monitoring the differences
between two analytical measurement systems that purport to
3.1 Definitions:
measure the same property provided that both systems have
3.1.1 accepted reference value, n—a value that serves as an
beenassessedinaccordancewiththestatisticalmethodologyin
agreed-uponreferenceforcomparisonandthatisderivedas(1)
Practice D6708 and the appropriate bias applied.
atheoreticalorestablishedvalue,basedonscientificprinciples,
(2) an assigned value, based on experimental work of some
NOTE 2—Forvalidationofunivariateprocessstreamanalyzers,seealso
national or international organization, such as the U.S. Na-
Practice D3764.
tional Institute of Standards and Technology (NIST), or (3)a
NOTE 3—One or both of the analytical systems in 1.5 can be laboratory
test methods or validated process stream analyzers.
consensus value, based on collaborative experimental work
under the auspices of a scientific or engineering group.
1.6 This practice assumes that the normal (Gaussian) model
E177, E456
is adequate for the description and prediction of measurement
3.1.2 accuracy, n—the closeness of agreement between an
system behavior when it is in a state of statistical control.
observed value and an accepted reference value. E177, E456
NOTE 4—For non-Gaussian processes, transformations of test results
3.1.3 assignable cause, n—a factor that contributes to
may permit proper application of these tools. Consult a statistician for
variation and that is feasible to detect and identify. E456
further guidance and information.
3.1.4 bias, n—a systematic error that contributes to the
difference between a population mean of the measurements or
1
This practice is under the jurisdiction ofASTM Committee D02 on Petroleum
Products and Lubricants and is the direct responsibility of Subcommittee D02.94 on
2
Coordinating Subcommittee on Quality Assurance and Statistics. For referenced ASTM standards, visit the ASTM website, www.astm.org, or
Current edition approved March 1, 2010. Published June 2010. Originally contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
approved in 1998. Last previous edition approved in 2009 as D6299–09. DOI: Standards volume information, refer to the standard’s Document Summary page on
10.1520/D6299-10. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C7
...

This document is not anASTM standard and is intended only to provide the user of anASTM standard an indication of what changes have been made to the previous version. Because
it may not be technically possible to adequately depict all changes accurately, ASTM recommends that users consult prior editions as appropriate. In all cases only the current version
of the standard as published by ASTM is to be considered the official document.
An American National Standard
Designation:D6299–09 Designation:D6299–10
Standard Practice for
Applying Statistical Quality Assurance and Control Charting
Techniques to Evaluate Analytical Measurement System
1
Performance
This standard is issued under the fixed designation D6299; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope
1.1 This practice covers information for the design and operation of a program to monitor and control ongoing stability and
precision and bias performance of selected analytical measurement systems using a collection of generally accepted statistical
quality control (SQC) procedures and tools.
NOTE 1—A complete list of criteria for selecting measurement systems to which this practice should be applied and for determining the frequency at
which it should be applied is beyond the scope of this practice. However, some factors to be considered include (1) frequency of use of the analytical
measurement system, (2) criticality of the parameter being measured, (3) system stability and precision performance based on historical data, (4) business
economics, and (5) regulatory, contractual, or test method requirements.
1.2 This practice is applicable to stable analytical measurement systems that produce results on a continuous numerical scale.
1.3 This practice is applicable to laboratory test methods.
1.4 This practice is applicable to validated process stream analyzers.
1.5 This practice is applicable to monitoring the differences between two analytical measurement systems that purport to
measure the same property provided that both systems have been assessed in accordance with the statistical methodology in
Practice D6708 and the appropriate bias applied.
NOTE 2—For validation of univariate process stream analyzers, see also Practice D3764.
NOTE 3—One or both of the analytical systems in 1.5 can be laboratory test methods or validated process stream analyzers.
1.6 This practice assumes that the normal (Gaussian) model is adequate for the description and prediction of measurement
system behavior when it is in a state of statistical control.
NOTE 4—For non-Gaussian processes, transformations of test results may permit proper application of these tools. Consult a statistician for further
guidance and information.
2. Referenced Documents
2
2.1 ASTM Standards:
D3764 Practice for Validation of the Performance of Process Stream Analyzer Systems
D5191 Test Method for Vapor Pressure of Petroleum Products (Mini Method)
D6708 Practice for Statistical Assessment and Improvement of Expected Agreement Between Two Test Methods that Purport
to Measure the Same Property of a Material
D6792 Practice for Quality System in Petroleum Products and Lubricants Testing Laboratories
D7372 Guide for Analysis and Interpretation of Proficiency Test Program Results
E177 Practice for Use of the Terms Precision and Bias in ASTM Test Methods
E178 Practice for Dealing With Outlying Observations
E456 Terminology Relating to Quality and Statistics
E691 Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method
3. Terminology
3.1 Definitions:
1
This practice is under the jurisdiction of ASTM Committee D02 on Petroleum Products and Lubricants and is the direct responsibility of Subcommittee D02.94 on
Coordinating Subcommittee on Quality Assurance and Statistics.
Current edition approved Nov.March 1, 2009.2010. Published FebruaryJune 2010. Originally approved in 1998. Last previous edition approved in 20082009 as
D6299–08.D6299–09. DOI: 10.1520/D6299-109.
2
For referencedASTM standards, visit theASTM website, www.astm.org, or contactASTM Customer Service at service@astm.org. For Annual Book ofASTM Standards
volume information, refer to the standard’s Document Summary page on the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.
1

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D6299–10
3.1.1 accepted reference value, n—a value that serves as an agreed-upon reference for comparison and that is derived as (1)a
theoretical or established value, based on scientific principles, (2) an assigned value, based on experimental work of some national
or international organization, such as the U.S. National Institute of Standards and
...

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