ASTM D 6122 : 2013
Superseded
A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.
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Standard Practice for Validation of the Performance of Multivariate Online, At-Line, and Laboratory Infrared Spectrophotometer Based Analyzer Systems
Hardcopy , PDF
11-11-2014
English
01-05-2013
Committee |
D 02
|
DocumentType |
Standard Practice
|
Pages |
30
|
PublisherName |
American Society for Testing and Materials
|
Status |
Superseded
|
SupersededBy | |
Supersedes |
1.1This 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 liquid petroleum products. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification of equivalence between the result calculated from the infrared measurements and the result produced by the primary test method used for the development of the calibration model. When there is adequate variation in property level, the statistical methodology of Practice D6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.
1.2Performance Validation is conducted by calculating the precision and bias of the differences between results from the analyzer system (or subsystem) produced by application of the multivariate model, (such results are herein referred to as Predicted Primary Test Method Results (PPTMRs)), versus the Primary Test Method Results (PTMRs) for the same sample set. Results used in the calculation are for samples that are not used in the development of the multivariate model. The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.
1.2.1For analyzers used in product release or product quality certification applications, the precision and bias requirement for the degree of agreement are typically based on the site or published precision of the Primary Test Method.
1.2.2This practice does not describe procedures for establishing precision and bias requirements for analyzer system applications. Such requirements must be based on the criticality of the results to the intended business application and on contractual and regulatory requirements. The user must establish precision and bias requirements prior to initiating the validation procedures described herein.
1.3This practice does not cover procedures for establishing the calibration model (correlation) used by the analyzer. Calibration procedures are covered in Practices E1655 and references therein.
1.4This practice is intended as a review for experienced persons. For novices, this practice will serve as an overview of techniques used to verify instrument performance, to verify model applicability to the spectrum of the sample under test, and to verify equivalence between the parameters calculated from the infrared measurement and the results of the primary test method measurement.
1.5This practice teaches and recommends appropriate statistical tools, outlier detection methods, for determining whether the spectrum of the sample under test is a member of the population of spectra used for the analyzer calibration. The statistical tools are used to determine if the infrared measurement results in a valid property or parameter estimate.
1.6The outlier detection methods do not define criteria to determine whether the sample or the instrument is the cause of an outlier measurement. Thus, the operator who is measuring samples on a routine basis will find criteria to determine that a spectral measurement lies outside the calibration, but will not have specific information on the cause of the outlier. This practice does suggest methods by which instrument performance tests can be used to indicate if the outlier methods are responding to changes in the instrument response.
1.7This practice is not intended as a quantitative performance standard for the comparison of analyzers of different design.
ASTM E 2898 : 2014 | Standard Guide for Risk-Based Validation of Analytical Methods for PAT Applications |
ASTM E 1655 : 2017 | Standard Practices for Infrared Multivariate Quantitative Analysis |
ASTM D 7453 : 2018 | Standard Practice for Sampling of Petroleum Products for Analysis by Process Stream Analyzers and for Process Stream Analyzer System Validation |
ASTM D 7235 : 2016 | Standard Guide for Establishing a Linear Correlation Relationship Between Analyzer and Primary Test Method Results Using Relevant ASTM Standard Practices |
ASTM D 7166 : 2010 : R2015 | Standard Practice for Total Sulfur Analyzer Based On-line/At-line for Sulfur Content of Gaseous Fuels |
ASTM D 7808 : 2018 | Standard Practice for Determining the Site Precision of a Process Stream Analyzer on Process Stream Material |
ASTM D 7164 : 2010 : R2015 | Standard Practice for On-line/At-line Heating Value Determination of Gaseous Fuels by Gas Chromatography |
ASTM D 7278 : 2016 | Standard Guide for Prediction of Analyzer Sample System Lag Times |
ASTM D 6621 : 2000 : R2017 | Standard Practice for Performance Testing of Process Analyzers for Aromatic Hydrocarbon Materials |
ASTM D 7314 : 2010 : R2015 | Standard Practice for Determination of the Heating Value of Gaseous Fuels using Calorimetry and On-line/At-line Sampling |
ASTM D 7165 : 2010 : R2015 | Standard Practice for Gas Chromatograph Based On-line/At-line Analysis for Sulfur Content of Gaseous Fuels |
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