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GB/T 40681.4-2021: Statistical methods in monitoring process capability and performance - Part 4: Process capability estimates and performance measures
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Statistical methods in monitoring process capability and performance - Part 4: Process capability estimates and performance measures
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GB/T 40681.4-2021
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Basic data | Standard ID | GB/T 40681.4-2021 (GB/T40681.4-2021) | | Description (Translated English) | Statistical methods in monitoring process capability and performance - Part 4: Process capability estimates and performance measures | | Sector / Industry | National Standard (Recommended) | | Classification of Chinese Standard | A41 | | Word Count Estimation | 42,439 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GB/T 40681.4-2021: Statistical methods in monitoring process capability and performance - Part 4: Process capability estimates and performance measures
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Statistical methods in monitoring process capability and performance - Part 4.Process capability estimates and performance measures
ICS 03.120.30
A41
National Standards of People's Republic of China
Statistical methods for production process capability and performance monitoring
Part 4.Process capability estimation and performance measurement
(ISO 22514-4.2016,Statisticalmethodsinprocessmanagement-
Released on 2021-10-11
2022-05-01 implementation
State Administration for Market Regulation
Issued by the National Standardization Management Committee
Table of contents
Foreword Ⅲ
Introduction Ⅴ
1 Scope 1
2 Symbols and abbreviations 1
2.1 Symbol 1
2.2 Abbreviations 2
3 Basic concepts of process capability and performance 2
3.1 Position 2
3.2 Degree of dispersion 2
3.3 Mean square error 3
3.4 Reference limit 3
3.5 Reference interval 3
4 Ability 3
4.1 General Principle 3
4.2 Process Capability 4
4.3 Process location 6
4.4 Process capability index of measurement data 6
4.5 Process capability index of measured data (in the case of non-normal distribution) 8
4.6 Alternative methods for describing and calculating process capability assessment 9
4.7 Other ability measures for continuous data 10
4.8 Evaluation of the proportion exceeding the specification limit (normal distribution case) 11
5 Performance 13
5.1 General 13
5.2 Process performance index of measured data (normal distribution case) 13
5.3 Process performance index of measured data (non-normal distribution case) 14
5.4 Other performance indexes of measured data 15
5.5 Evaluation of the proportion exceeding the specification limit in the case of a normal distribution 15
6 Report format of process capability index and process performance index 15
Appendix A (informative appendix) Estimated standard deviation 17
A.1 General 17
A.2 Inherent standard deviation 17
A.3 Estimate of the total standard deviation 18
Appendix B (informative appendix) Steps and examples of using the Pearson curve to estimate process capability and performance metrics 19
B.1 Record specification limit 19
B.2 Recording process statistics 19
B.3 Find the standardized 0.135% quantile 19
B.4 Find the standardized 99.865% quantile 19
B.5 Look up the standardized median of table B.3 19
B.6 Calculate the estimated value of the 0.135% quantile 19
B.7 Calculate the estimated value of the 99.865% quantile 19
B.8 Calculate the estimated value of the median 20
B.9 Calculating Process Capability Index 20
Appendix C (Informative Appendix) Distribution Identification 30
C.1 General 30
C.2 Normal distribution 30
C.3 Lognormal distribution 30
C.4 Rayleigh distribution 32
C.5 Weibull distribution 32
C.6 Folded Half Normal Distribution 32
C.7 Other distribution 33
Appendix D (informative appendix) Confidence interval 34
D.1 Normal distribution 34
D.2 Other confidence intervals 35
Reference 36
Foreword
The plan of GB/T 40681 "Statistical Methods for Monitoring Production Process Capability and Performance" is divided into the following 8 parts.
---Part 1.General principles and concepts;
---Part 2.Process capability and performance of time-dependent process models;
---Part 3.Research on machine performance of discrete product measurement data;
---Part 4.Process capability estimation and performance measurement;
---Part 5.Process capability and performance estimation of counting characteristics;
---Part 6.Multivariate normal process capability analysis;
---Part 7.Measuring process capability;
---Part 8.Equipment performance analysis of multi-state production process.
This part is Part 4 of GB/T 40681.
This section was drafted in accordance with the rules given in GB/T 1.1-2009.
This part uses the redrafting method to modify and adopt ISO 22514-4.2016 "Statistical Methods Capability and Performance in Process Management No. 4
Part. Process Capability Estimation and Performance Measurement.
Compared with ISO 22514-4.2016, this part has made the following structural adjustments.
---The 3.1 of ISO 22514-4.2016 is deleted, and the "assessment and measurement methods involved in this part" in 3.1 are only applicable to metrological
Data is not applicable to attribute data. For relevant content of attribute data, please refer to ISO 22514-5" to adjust to Chapter 1, and revise
Changed to "This section applies to the process capability and performance evaluation of measurement data in the common production process, and does not apply to attribute characteristics
Process capability and performance evaluation. "
The technical differences between this part and ISO 22514-4.2016 and the reasons are as follows.
--- Delete "P0.135%. 0.135% quantile", "P99.865%. 99.865% quantile", "π. geometric constant" and "e. Euler constant" in 2.1
In addition, the reason is that the definition is repeated;
--- Modify the "Pα.α quantile" in 2.1 to "Pα standardized Pearson curve α quantile" to be more accurate;
--- Replace "σt" in 2.1 and the full text with "σt. total standard deviation of the process";
--- Delete "Y1, Y2" in 2.1 and the full text. The meanings are different in different figures, and they have been explained in the text without symbol explanation;
---Modify the expression "CpkL =0.86, CpkU =0.91" involving numerical calculation in 4.8 to the estimated form "CpkL =0.86,
CpkU=0.91", modified the incorrectly used estimated value symbol;
--- Estimate the parameters of μ and σ2 in C.3.1 "μ=X=
N∑
i=1
Xi" and "σ2=
N-1∑
i=1
(Xi-X)2", amended to
"Μ=logX=
N∑
i=1
logXi" and "σ2=
N-1∑
i=1
(logXi-logX)2";
--- Modify "Xα=Y-ξ(-log(1-α))-β" in C.5 to "Xα=Y ξ[-log(1-α)]
β".
This section has made the following editorial changes.
---Modified the standard name;
--- Modified the non-standard expression of the data index in Table 3;
--- Modify "Kl0.95" in D.1.3 to "Kl";
--- Modify "Ku0.95" in D.1.3 to "Ku;
---The full text formula adds the serial number;
---Revised references.
This part is proposed and managed by the National Standardization Technical Committee for the Application of Statistical Methods (SAC/TC21).
Drafting organizations of this section. Beijing University of Aeronautics and Astronautics, China National Institute of Standardization, Inner Mongolia Mengniu Dairy (Group) Co., Ltd.,
Huzhou Rongke Building Material Technology Co., Ltd., Shanxi Aerospace Tsinghua Equipment Co., Ltd., Huzhou Mingfeng Enterprise Management Consulting Co., Ltd., Beijing
Electronic Engineering General Research Institute, the 12th Research Institute of China Electronics Technology Group Corporation, Liaocheng Zhuoqun Auto Parts Co., Ltd.
The main drafters of this section. Yang Jun, Huang Shuo, Li Qi, Zhao Jing, Ma Wenli, Ma Lijun, Ding Lihui, Qian Xinhui, Kong Xuefeng, Meng Fanbing, Cui Yanhe,
Li Lei, Zhang Yuehong, Chen Yanwei, Ding Wenxing, Xu Yanfeng.
Introduction
Many organizations have already embarked on a continuous process improvement strategy. In order to comply with the strategy, any organization needs to evaluate the performance of its key processes.
Capability and performance. The methods given in this section are intended to help carry out this aspect of management. Managers need to continue to pay attention to these assessments in order to
Carry out continuous improvement activities when needed.
Recently, this part has been greatly developed. The most fundamental change is to conceptualize the capability conditions and performance conditions named in this section.
The fundamental difference lies in whether the process characteristics are in a statistically controlled state (in a statistically controlled state, it is called capability, otherwise it is called performance). therefore,
Two sets of indicators corresponding to capabilities and performance are given in the relevant clauses. Because it has been found in the industry that due to improper calculation and publication
Some companies are misled in terms of their true capabilities, so it is increasingly necessary to make a strict distinction between capabilities and performance.
The progress of this part lies in the transition from general conditions to specific conditions, and this improvement makes the generalized formula present a more specific form of expression.
A large number of existing documents describe the importance of understanding the work process in any organization, for example, the production process or the information processing process.
With the intensification of sales competition between enterprises, in addition to the sales price of important products or services, during the use of products or services, purchase
The expenses that buyers will bear are also becoming more and more important. The goal of each supplier is no longer to just meet the specifications, but to continue to reduce
Mutations.
In a world where competition continues to increase, continuous improvement can reduce the loss of product failure and the cost of survival. Because as the variation decreases,
The cost of evaluation will decrease, the demand for testing products may disappear or the sampling frequency may be reduced.
In order for an organization to be able to evaluate the capabilities and performance of its suppliers, process capability and performance evaluation is necessary. These organizations will find the package
The indicators contained in this section are useful in this regard.
Quantifying the variation of a process can make judgments about its suitability and ability to meet certain given requirements. The following paragraph
And clauses provide philosophical principles that need to be understood to determine the capabilities or performance of a process.
All processes have inherent variability. This section does not specifically explain the meaning, reason, source and how of inherent variation
The process is based on the premise of the stable existence of inherent variation.
Process owners need to work hard to understand the source of their process variation. Will draw process flow diagrams, identify process input and output methods, and factors
Fruit diagrams (fishbone diagrams) are used together reasonably to help identify these process variations.
The distinction between short-term variation and long-term variation is very important for the use of this section.
Process capabilities determined by long-term variability may vary greatly.
When considering short-term variation, it can only be carried out based on the shortest-term variation, sometimes called machine research, which is described in ISO 22514-3.
The methods needed to carry out such studies are beyond the scope of this section; it should be pointed out that these studies are important and useful.
It should be pointed out that this section only provides the point estimate of the process capability index. In view of the actual demand, it is recommended to calculate the position of these indexes as much as possible.
Confidence interval.
Statistical methods for production process capability and performance monitoring
Part 4.Process capability estimation and performance measurement
1 Scope
This part of GB/T 40681 gives the commonly used process capability and performance for the two types of normal distribution and non-normal distribution.
Metrics provide an evaluation method of process capability and performance.
This section applies to the process capability and performance evaluation of metrological data in common production processes, and does not apply to the process capability of quantitative data.
Force and performance evaluation.
2 Symbols and abbreviations
2.1 Symbols
The following symbols apply to this document. In addition to the following symbols, some symbols are defined when used in the text.
α fraction or ratio
β Weibull distribution shape parameter
β2 kurtosis coefficient
c4 constant related to subgroup size n
Cp Process Capability Index
Cpk minimum process capability index
Process Capability Index under CpkL
Process Capability Index on CpkU
Cpm Taguchi Process Capability Index
CR Process Capability Reciprocal (PCF)
d2 Constant related to the subgroup size n
Φ Distribution function of standard normal distribution
γ Weibull distribution location parameter
γ1 skewness coefficient
m number of subgroups
Kl, Ku Coefficients used to estimate the confidence limit of the process capability index
LSL lower specification limit
N total sample size
n subgroup size
Pα standardized Pearson curve α quantile
Failure rate under pL
Pp process performance index
Ppk minimum process performance index
Process performance index under PpkL
Process performance index on PpkU
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