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Basic dataStandard ID: GB/T 27430-2022 (GB/T27430-2022)Description (Translated English): Role of measurement uncertainty in conformity assessment Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: A50 Classification of International Standard: 17.020 Word Count Estimation: 50,528 Date of Issue: 2022-12-30 Date of Implementation: 2022-12-30 Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration GB/T 27430-2022: Role of measurement uncertainty in conformity assessment---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.ICS 17.020 CCSA50 National Standards of People's Republic of China The Function of Measurement Uncertainty in Conformity Assessment Posted on 2022-12-30 2022-12-30 implementation State Administration for Market Regulation Released by the National Standardization Management Committee table of contentsPreface III Introduction IV 1 Scope 1 2 Normative references 1 3 Terms and Definitions 2 4 Conventions and notation 6 5 Tolerance limits and tolerance intervals 7 5.1 Measurement activities in conformity assessment7 5.2 Permissible and non-permissible values. tolerance interval 7 5.3 Examples of tolerance limits 8 6 Measured knowledge 8 6.1 Probability and information 8 6.2 Bayes' theorem 9 6.3 General information 9 6.3.1 Best estimate and standard uncertainty9 6.3.2 Inclusion interval 10 7 Probability of passing the specified requirements10 7.1 General principles for calculating pass probability10 7.2 Eligibility probability for normal probability density functions 11 7.3 One-sided tolerance intervals for normal probability density functions 11 7.3.1 Single lower allowable limit 11 7.3.2 Single tolerable upper limit12 7.3.3 General calculation method with single tolerance limit13 7.4 Two-sided admissible intervals for the normal probability density function 13 7.5 Eligibility probabilities and inclusion intervals 14 7.6 Measuring capability index Cm 15 7.7 Measuring capability index and pass probability 16 8 Accept interval 17 8.1 Acceptance limits17 8.2 Decision rules based on simple acceptance 17 8.3 Judgment rules based on guard bands 18 8.3.1 Basic considerations 18 8.3.2 Protected acceptance 18 8.3.3 Protected rejection 19 9 Consumer and producer risks 20 9.1 General 20 9.2 Probability density functions for production processes and measurement systems 20 9.3 Tests using binary decision rules measure possible outcomes 21 9.4 The joint probability density function of Y and Ym 21 9.5 Global risk calculation 22 9.5.1 Historical background 22 9.5.2 General formula 22 9.5.3 Special case. binary decision rule 23 9.5.4 Setting acceptance limits 24 9.5.5 General Graphical Method 27 9.5.6 Significance of reducing measurement uncertainty 28 Appendix A (Informative) Basic Symbol Collection 29 Appendix B (informative) Prior knowledge of the measurand 31 B.1 Statistical process control 31 B.2 Select random items from the sample of items to be tested 31 B.3 Positive properties near physical boundaries 33 Appendix C (informative) Normal distribution 35 C.1 Normal distribution probability density function 35 C.2 Integrals of normal probability density functions 35 C.3 Inclusion probability of the normal probability density function 35 C.4 Normal process and measuring probability density 36 C.4.1 The prior probability density function g0(η) of the measurand Y 36 C.4.2 The probability density function h(ηm|η) of Ym when Y=η is given 36 C.4.3 Marginal probability density function h0(ηm) of Ym 36 C.4.4 Posteriori (after measurement) probability density function g(η|ηm) of Y 37 C.5 Risk Calculations Using Normal Probability Density Functions and Binary Decision Rules 37 Reference 39forewordThis document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules for Standardization Documents" drafting. This document is modified to adopt ISO /IEC Guide 98-4.2012 "Uncertainty of Measurement - Part 4.Uncertainty of Measurement in Conformity Assessment The role of ", the file type is adjusted from the ISO guide to the national standard of our country. Compared with ISO /IEC Guide 98-4.2012, this document has made the following structural adjustments. --- Deleted the suspension paragraph of Chapter 4 and the article number of A.4.1.1 in ISO /IEC Guide 98-4.2012; ---Changed the order of appendices, Appendix A corresponds to Appendix C in ISO /IEC Guide 98-4.2012, and Appendix C corresponds to ISO /IEC Guide Appendix A of 98-4.2012. The following editorial changes have been made to this document. ---Changed the name of the standard to "The Role of Measurement Uncertainty in Conformity Assessment" to coordinate with existing standardization documents; --- Deleted JCGM102.2011 in the chapter on normative references, the document is only in the introduction of ISO /IEC Guide 98-4.2012 and It is cited in the informative appendix, but not cited in this document; --- ISO 3650 was replaced by GB/T 6093 (see introduction), and ISO /IEC 17025 was replaced by GB/T 27025-2019. 2005 (see introduction, source of term 3.3.12), replaced JCGM100.2008 (GUM) with GB/T 27418-2017 (see Chapter 3 Introduction, 4.1, 6.3.2.4, B.1.1, C.4.2.2, C.4.4.3), replace JCGM101 with GB/T 27419-2018. 2008 (see Chapter 3 Guidance, 6.3.2.3 and 7.2.3), replaced JCGM200.2012 with ISO /IEC Guide99.2007 (See the introduction in Chapter 3), the cited technical content is consistent, which is convenient for the application of this document; --- Deleted the informative appendix ZZ in ISO /IEC Guide 98-4.2012, which has nothing to do with my country's technical conditions and applications. This document is proposed and managed by the National Certification and Accreditation Standardization Technical Committee (SAC/TC261). This document is drafted by. China National Accreditation Center for Conformity Assessment, China Institute of Testing Technology, Zhejiang Institute of Metrology, Beijing University of Science and Technology, China Institute of Metrology, CTI Testing and Certification Group Co., Ltd., China Academy of Railway Sciences Group Co., Ltd. Institute of Standards and Metrology, Suzhou Electrical Apparatus Research Institute Co., Ltd. The main drafters of this document. Anping, Liu Haofeng, Wang Yang, Lin Zhiguo, Wu Yusun, Liu Maomao, Shen Yijiu, Chen Lingfeng, Wang Chunyan, Zhao Yuning, Wang Yanchun, He Xiuming.IntroductionConformity assessment (see 3.3.1), broadly speaking, refers to the determination, directly or indirectly, whether a product, process, system, person or organization meets the requirements of relevant any activity performed as required by standards and regulations (see 3.3.3). GB/T 27000-2006 "Conformity Assessment Vocabulary and General Principles" gives General terms and definitions related to conformity assessment, including accreditation of conformity assessment bodies and the use of conformity assessment in facilitating trade. In certain types of conformity assessment (sometimes called inspection, see 3.3.2), the determination of whether a product fulfills specified requirements relies on measuring the Primary source of information. ISO 10576-1.2003 [22] provides an inclusive interval for the results of a measurement of a quantity (see 3.2.1) (see 3.2.7, called "uncertainty interval" in ISO 10576-1.2003) is compared with the tolerance interval (see 3.3.5) to check compliance with Guidance on setting limit values. This document extends this approach to include explicit risk considerations and formulate judgments based on measurements (see 3.2.5). A general procedure for determining compliance, recognizing the central role of probability distributions (see 3.1.1) in the expression of uncertainty and incomplete information. GB/T 27418-2017 "Assessment and Expression of Uncertainty in Measurement", GB/T 27419-2018 "Assessment and Expression of Uncertainty in Measurement" Supplementary Document 1.Distribution Propagation Based on Monte Carlo Method" and JCGM103[3] provide an understanding of the technical issue of measurement uncertainty assessment solution. This document assumes that the quantity of interest, the measurand (see 3.2.4), is measured and that the measurement results are expressed in a manner consistent with The principles stated in GB/T 27418-2017.In particular, it is assumed that all identified significant systematic effects have been corrected for. In conformity assessment, measurement results are used to determine whether the article of interest conforms to specified requirements. Items of interest can be based on The gauge block calibrated according to GB/T 27025-2019 [23] or tested according to GB/T 6093 [24] can also be a sample of industrial wastewater. Meet the requirements The usual form is one or two tolerance limits (see 3.3.4) to define the allowable value interval of the measurable property of the item, called the tolerance interval (see 3.3.5). Examples of these attributes include gauge block length, voltmeter reading error, and mass concentration of mercury in a wastewater sample. if testable If the true value of the quantity attribute is within the allowable interval, it is called conformity, otherwise it does not conform. Note. The term "tolerance interval" used in conformity assessment has a different meaning from the "tolerance interval" used in statistics. In general, determining whether an item is qualified depends on multiple measured attributes, and there may be one or more attributes associated with each attribute. allowable range. Given the measurement results, there may be more than one possible conclusion considering each attribute. For example, after measuring a certain value, the human We may decide to accept the item, reject the item, take another measurement, etc. Items discussed in this document have a single scalar attribute The specified requirements are given by one or two tolerance limits, and the judgment result is a binary conclusion, that is, there are only two possible states of the item (qualified and unqualified). case) and two possible corresponding decisions (accept or reject). The concepts presented in this paper can be extended to more general decision problems. In the evaluation of measured data, the probability density function (see 3.1.3) or a numerical approximation of such a function is usually used to express and transfer the measurand. Information about energy value. This knowledge is usually summarized as best estimates (considered as measured quantities, see 3.2.6), and their associated measured degree of certainty, or the inclusion interval that includes the value of the measurand with a specified probability of inclusion (see 3.2.8). Therefore, the evaluation based on the information after carrying out the measurement is Compliance with specified requirements is a matter of probability. In typical measurement activities, the underlying truth value of the measurand of interest is unknown. For example, the length of a steel gauge block cannot be directly observed, but can be Observe the micrometer reading where the anvil is in contact with the end of the gauge block. This indication is obtained by means of measurements including influencing quantities such as thermal expansion and micrometer calibration. The gauge model conveys information about the length of the gauge block. Accept/reject decisions in conformity assessment are based on observable data from which the measurand Possible values of potential truth values [37]. Due to the uncertainty of measurement, judging whether an item meets the specified requirements based on the measured value of the property of the item usually has the risk of misjudgment. this There are generally two kinds of misjudgments. the accepted qualified items may actually be unqualified, and the rejected unqualified items may actually be acceptable. grid. By defining an acceptance interval (see 3.3.9) that allows the measured value of the measurand to be measured, it is possible to balance false acceptance/rejection with respect to measurement uncertainty risk and minimize the cost of misjudgment. This document addresses the issue of calculating the probability density function (PDF) of the measurand, tolerance limits, and acceptance limits. Calculation of pass probability (see 3.3.7) and two kinds of technical problems of misjudgment probability. The specific acceptance interval and its relationship with the corresponding allowable interval are shown in Figure 1. It is stipulated that the true value of the measurable property (measurand) of the item lies within the allowable interval defined by (TL,TU). If the measured value of the attribute lies within the acceptance limits (see 3.3.8) Within the interval defined by (AL, AU), it is accepted as a qualified item, otherwise it is rejected as an unqualified item. Figure 1 Binary conformity assessment based on measured values Selection of tolerance and acceptance limits is a business decision based on the consequences of deviations from expected product quality. Generic treatment of such decisions approach is beyond the scope of this document. See references [14,15,34,35,36,44]. The Function of Measurement Uncertainty in Conformity Assessment1 ScopeThis document provides guidance and procedures for evaluating the conformity of an article (entity, object or system) with the requirements of the specification. The item can be (Example) Gauge blocks, grocery scales, or blood samples. The following procedures can be used in the following situations. a) The item under test is distinguished by a single scalar quantity (measurable property, see 3.2.1) defined by a detailed procedure sufficient to A truth-value representation; Note. GB/T 27418-2017 provides reasons for not using the term "true", but this document will still use this term, otherwise there may be ambiguity or confusing situation. b) the permissible value interval for the attribute is bounded by one or two tolerance limits; c) The attribute can be measured, and the measurement results (see 3.2.5) are expressed in the manner in GB/T 27418-2017, so that the attribute Knowledge of values can be achieved through. 1) Probability density function (PDF, see 3.1.3); 2) distribution function (see 3.1.2); 3) Numerical approximations of these functions; 4) Reasonably described with the inclusion interval and the best estimated value of the corresponding inclusion probability. The procedures presented in this document are applied to yield intervals of allowable measured values for the attribute of interest, called acceptance intervals. may reasonably choose to accept Limits effectively balance the risk of accepting nonconforming items (consumer risk) or rejecting conforming items (producer risk). This document addresses two conformity assessment issues. The first is to set the acceptance limit to ensure that the expected pass probability of a single tested item is achieved; the second The second is to set acceptance limits to ensure that multiple items (of the same nominal name) are measured with an acceptable average confidence level. This document provides solutions to guide. This document contains examples to illustrate the above guidelines. The concepts presented in this paper can be extended to more measurands based on measuring a set of scalar Common conformity assessment questions. Some documents, such as Refs. [13,19], cover industry-specific conformity assessment issues. This document is applicable to quality managers, members of standards development organizations and accreditation bodies, as well as testing and calibration laboratories, inspection bodies, certification bodies It is used as a reference by personnel of institutions, regulatory authorities, colleges and research institutes.2 Normative referencesThe contents of the following documents constitute the essential provisions of this document through normative references in the text. Among them, dated references For documents, only the version corresponding to the date is applicable to this document; for undated reference documents, the latest version (including all amendments) is applicable to this document. GB/T 3358.1-2009 Statistical vocabulary and symbols - Part 1.General statistical terms and terms used in probability (ISO 3534-1. 2006, IDT) GB/T 3358.2-2009 Statistics Vocabulary and Symbols Part 2.Applied Statistics (ISO 3534-2.2006, IDT) GB/T 27000-2006 Conformity Assessment Vocabulary and General Principles (ISO /IEC 17000.2004, IDT) GB/T 27418-2017 Evaluation and Expression of Measurement Uncertainty GB/T 27419-2018 Measurement Uncertainty Assessment and Representation Supplementary Document 1.Distribution Propagation Based on Monte Carlo Method ISO /IEC Guide99.2007 Basic and common concepts and related terms of international metrology vocabulary [International ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 27430-2022_English be delivered?Answer: Upon your order, we will start to translate GB/T 27430-2022_English as soon as possible, and keep you informed of the progress. The lead time is typically 4 ~ 7 working days. 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