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Significance and Use
5.1 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.
5.2 Data accrued, using the techniques included in this practice, provide the ability to monitor analytical measurement system precision and bias.
5.3 These data are useful for updating test methods as well as for indicating areas of potential measurement system improvement.
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 and the appropriate bias applied.
Note 2: For validation of univariate process stream analyzers, see also Practice .
Note 3: One or both of the analytical systems in 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.
1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
2. Referenced Documents (purchase separately) The documents listed below are referenced within the subject standard but are not provided as part of the standard.
D3764 Practice for Validation of the Performance of Process Stream Analyzer Systems
D4175 Terminology Relating to Petroleum Products, Liquid Fuels, and Lubricants
D5191 Test Method for Vapor Pressure of Petroleum Products (Mini Method)
D6300 Practice for Determination of Precision and Bias Data for Use in Test Methods for Petroleum Products and Lubricants
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 Management Systems in Petroleum Products, Liquid Fuels, 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
ICS Number Code 03.120.30 (Application of statistical methods)
|Link to Active (This link will always route to the current Active version of the standard.)|
ASTM D6299-18, Standard Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measurement System Performance, ASTM International, West Conshohocken, PA, 2018, www.astm.orgBack to Top