ASTM D6122-2015 red 3767 Standard Practice for Validation of the Performance of Multivariate Online At-Line and Laboratory Infrared Spectrophotometer Based Analyzer Systems《多变量联机和实.pdf

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1、Designation: D6122 13D6122 15Standard Practice forValidation of the Performance of Multivariate Online, At-Line, and Laboratory Infrared Spectrophotometer BasedAnalyzer Systems1This standard is issued under the fixed designation D6122; the number immediately following the designation indicates the y

2、ear oforiginal adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.INTRODUCTIONOperation of a laboratory or process stream analyzer

3、system typically involves four sequentialactivities. (1) Analyzer CalibrationWhen an analyzer is initially installed, or after majormaintenance has been performed, diagnostic testing is performed to demonstrate that the analyzermeets the manufacturers specifications and historical performance standa

4、rds. These diagnostic testsmay require that the analyzer be adjusted so as to provide predetermined output levels for certainreference materials. (2)(2a) CorrelationCorrelation, where analyzer and Primary Test Method(PTM) measure the same materialOnce the diagnostic testing is completed, process str

5、eamsamples are analyzed using both the analyzer system and the corresponding primary test method(PTM). PTM. A mathematical function is derived that relates the analyzer output to the primary testmethod (PTM). PTM. The application of this mathematical function to an analyzer output producesa predicte

6、d primary test method result (PPTMR). Predicted Primary Test Method Result (PPTMR) forthe same material. (2b) Correlation, where analyzer measures a material which is subjected totreatment before being measured by the PTMOnce the diagnostic testing is completed, theprocess stream samples are analyze

7、d by the analyzer system. The same samples are subjected to aconsistent treatment, and the treated samples are analyzed by the PTM. A mathematical function isderived that related the analyzer output for the untreated sample to the Primary Test Method Result(PTMR) for the treated material. The applic

8、ation of the mathematical function to the analyzer outputfor the untreated material produces a PPTMR for the treated material. (3) Probationary ValidationOnce the relationship between the analyzer output and PTMRs has been established, a probationaryvalidation is performed using an independent but l

9、imited set of materials that were not part of thecorrelation activity. This probationary validation is intended to demonstrate that the PPTMRs agreewith the PTMRs to within user-specified requirements for the analyzer system application. (4) Gen-eral and Continual ValidationAfter an adequate number

10、of PPTMRs and PTMRs have beenaccrued on materials that were not part of the correlation activity, a comprehensive statisticalassessment is performed to demonstrate that the PPTMRs agree with the PTMRs to withinuser-specified requirements. Subsequent to a successful general validation, quality assura

11、nce controlchart monitoring of the differences between PPTMR and PTMR is conducted during normal operationof the process analyzer system to demonstrate that the agreement between the PPTMRs and thePTMRs established during the General Validation is maintained. This practice deals with the third andfo

12、urth of these activities.“Correlation where analyzer measures a material which is subjected to treatment before beingmeasured by the PTM” as outlined in this practice is intended primarily to be applied to biofuels wherethe biofuel material is added at a terminal or other facility and not included i

13、n the process streammaterial sampled by the analyzer at the basestock manufacturing facility. The “treatment” shall be aconstant percentage addition of the biofuels material to the basestock material.1 This practice is under the jurisdiction of ASTM Committee D02 on Petroleum Products, Liquid Fuels,

14、 and Lubricants and is the direct responsibility of SubcommitteeD02.25 on Performance Assessment and Validation of Process Stream Analyzer Systems.Current edition approved May 1, 2013June 1, 2015. Published June 2013February 2016. Originally approved in 1997. Last previous edition approved in 2010 a

15、sD6122 10.D6122 13. DOI: 10.1520/D6122-13.10.1520/D6122-15.This document is not an ASTM standard and is intended only to provide the user of an ASTM standard an indication of what changes have been made to the previous version. Becauseit may not be technically possible to adequately depict all chang

16、es accurately, ASTM recommends that users consult prior editions as appropriate. In all cases only the current versionof the standard as published by ASTM is to be considered the official document.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. Uni

17、ted States11. Scope*1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near-or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquidpetroleum produc

18、ts. products and fuels. The properties are calculated from spectroscopic data using multivariate modelingmethods. The requirements include verification of adequate instrument performance, verification of the applicability of thecalibration model to the spectrum of the sample under test, and verifica

19、tion of equivalencethat the degree of agreement betweenthe resultresults calculated from the infrared measurements and the resultresults produced by the primary test method PTM usedfor the development of the calibration model. model meets user-specified requirements. When there is adequate variation

20、 inproperty level, the statistical methodology of Practice D6708 is used to provide general validation of this equivalence over thecomplete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specificvalidation is used.1.1.1 For some applica

21、tions, the analyzer and PTM are applied to the same material. The application of the multivariate modelto the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. ThePPTMRs are compared to the PTMRs measured on the same materials to determin

22、e the degree of agreement.1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent treatment prior to beinganalyzed by the PTM. The application of the multivariate model to the analyzer output (spectrum) produces a PPTMR for thetreated material. The PPT

23、MRs based on the analyzer outputs are compared to the PTMRs measured on the treated materials todetermine the degree of agreement.1.2 Performance Validation is conducted by calculating the precision and bias of the differences between results from theanalyzer system (or subsystem) produced by applic

24、ation of the multivariate model, (such results are herein referred to as PredictedPrimary Test Method Results (PPTMRs), versus the Primary Test Method Results (PTMRs) PPTMRs), versus the PTMRs for thesame sample set. Results used in the calculation are for samples that are not used in the developmen

25、t of the multivariate model.The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.1.2.1 For analyzers used in product release or product quality certification applications, the precision and bias requirement forthe degree of a

26、greement are typically based on the site or published precision of the Primary Test Method.PTM.NOTE 1In most applications of this type, the PTM is the specification-cited test method.1.2.2 This practice does not describe procedures for establishing precision and bias requirements for analyzer system

27、applications. Such requirements must be based on the criticality of the results to the intended business application and oncontractual and regulatory requirements. The user must establish precision and bias requirements prior to initiating the validationprocedures described herein.1.3 This practice

28、does not cover procedures for establishing the calibration model (correlation) used by the analyzer. Calibrationprocedures are covered in Practices E1655 and references therein.1.4 This practice is intended as a review for experienced persons. For novices, this practice will serve as an overview oft

29、echniques used to verify instrument performance, to verify model applicability to the spectrum of the sample under test, and toverify equivalence between the parameters calculated from the infrared measurement and the results of the primary test methodmeasurement.1.5 This practice teaches and recomm

30、ends appropriate statistical tools, outlier detection methods, for determining whether thespectrum of the sample under test is a member of the population of spectra used for the analyzer calibration. The statistical toolsare used to determine if the infrared measurement results in a valid property o

31、r parameter estimate.1.6 The outlier detection methods do not define criteria to determine whether the sample or the instrument is the cause of anoutlier measurement. Thus, the operator who is measuring samples on a routine basis will find criteria to determine that a spectralmeasurement lies outsid

32、e the calibration, but will not have specific information on the cause of the outlier. This practice doessuggest methods by which instrument performance tests can be used to indicate if the outlier methods are responding to changesin the instrument response.1.7 This practice is not intended as a qua

33、ntitative performance standard for the comparison of analyzers of different design.1.8 Although this practice deals primarily with validation of infrared analyzers, the procedures and statistical tests describedherein are also applicable to other types of analyzers which employ multivariate models.1

34、.9 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibilityof the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatorylimitations prior to use.D6122 1522. Refere

35、nced Documents2.1 ASTM Standards:2D1265 Practice for Sampling Liquefied Petroleum (LP) Gases, Manual MethodD3764 Practice for Validation of the Performance of Process Stream Analyzer SystemsD4057 Practice for Manual Sampling of Petroleum and Petroleum ProductsD4177 Practice for Automatic Sampling of

36、 Petroleum and Petroleum ProductsD6299 Practice for Applying Statistical Quality Assurance and Control Charting Techniques to Evaluate Analytical Measure-ment System PerformanceD6708 Practice for Statistical Assessment and Improvement of Expected Agreement Between Two Test Methods that Purportto Mea

37、sure the Same Property of a MaterialD7278 Guide for Prediction of Analyzer Sample System Lag TimesD7453 Practice for Sampling of Petroleum Products forAnalysis by Process StreamAnalyzers and for Process StreamAnalyzerSystem ValidationD7808 Practice for Determining the Site Precision of a Process Str

38、eam Analyzer on Process Stream MaterialD7717 Practice for Preparing Volumetric Blends of Denatured Fuel Ethanol and Gasoline Blendstocks for Laboratory AnalysisE131 Terminology Relating to Molecular SpectroscopyE275 Practice for Describing and Measuring Performance of Ultraviolet and Visible Spectro

39、photometersE456 Terminology Relating to Quality and StatisticsE932 Practice for Describing and Measuring Performance of Dispersive Infrared SpectrometersE1421 Practice for Describing and Measuring Performance of Fourier Transform Mid-Infrared (FT-MIR) Spectrometers: LevelZero and Level One TestsE165

40、5 Practices for Infrared Multivariate Quantitative AnalysisE1866 Guide for Establishing Spectrophotometer Performance TestsE1944 Practice for Describing and Measuring Performance of Laboratory Fourier Transform Near-Infrared (FT-NIR)Spectrometers: Level Zero and Level One Tests3. Terminology3.1 Defi

41、nitions:3.1.1 For definitions of terms and symbols relating to IR spectroscopy, refer to Terminology E131.3.1.2 For definitions of terms and symbols relating to multivariate calibration, refer to Practices E1655.3.1.3 For definitions of terms relating to statistical quality control, refer to Practic

42、e D6299 and Terminology E456.3.1.4 between-method reproducibility (RXY), na quantitative expression of the random error associated with the differencebetween two results obtained by different operators using different apparatus and applying the two methods X and Y, respectively,each obtaining a sing

43、le result on an identical test sample, when the methods have been assessed and an appropriate bias-correctionhas been applied in accordance with this practice; it is defined as the 95 % confidence limit for the difference between two suchsingle and independent results. D67083.1.5 control limits, nli

44、mits on a control chart which are used as criteria for signaling the need for action, or for judgingwhether a set of data does or does not indicate a state of statistical control. E4563.2 Definitions of Terms Specific to This Standard:3.2.1 action limit, nthe limiting value from an instrument perfor

45、mance test, beyond which the analyzer is expected to producepotentially invalid results.3.2.2 analyzer, nall piping, hardware, computer, software, instrumentation and calibration model required to automaticallyperform analysis of a process or product stream.3.2.3 analyzer calibration, nsee multivari

46、ate calibration.3.2.4 analyzer site precision, na statistical measure of the expected long-term variability of analyzer results for samples whosespectra are neither outliers, nor nearest neighbor inliers.3.2.5 analyzer model, nsee multivariate model.3.2.6 analyzer repeatability, na statistical measu

47、re of the expected short-term variability of results produced by the analyzerfor samples whose spectra are neither outliers nor nearest neighbor inliers.3.2.7 analyzer result, nthe numerical estimate of a physical, chemical, or quality parameter produced by applying thecalibration model to the spect

48、ral data collected by the analyzer.3.2.8 analyzer validation test, nsee validation test.2 For referencedASTM standards, visit theASTM website, www.astm.org, or contactASTM Customer Service at serviceastm.org. For Annual Book of ASTM Standardsvolume information, refer to the standards Document Summar

49、y page on the ASTM website.D6122 1533.2.9 calibration transfer, na method of applying a multivariate calibration developed on one analyzer to a different analyzerby mathematically modifying the calibration model or by instrument standardization.3.2.10 check sample, na single, pure liquid hydrocarbon compound or a known, reproducible mixture of liquid hydrocarboncompounds whose spectrum is constant over time such that it can be used in a performance test.3.2.11 exponentially weighted moving average control chart, na control chart based on the exponentially