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Delivery: <= 7 days. True-PDF full-copy in English will be manually translated and delivered via email. GB/T 17989.5-2022: Statistical method of quality control in production process - Control charts - Part 5: Specialized control charts Status: Valid
Basic dataStandard ID: GB/T 17989.5-2022 (GB/T17989.5-2022)Description (Translated English): Statistical method of quality control in production process - Control charts - Part 5: Specialized control charts Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: A41 Word Count Estimation: 53,535 Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration GB/T 17989.5-2022: Statistical method of quality control in production process - Control charts - Part 5: Specialized control charts---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. Statistical method of quality control in production process - Control charts - Part 5.Specialized control charts ICS 03.120.30 CCSA41 National Standards of People's Republic of China Production process quality control statistical method control chart Part 5.Special Control Charts Published on 2022-03-09 2022-10-01 Implementation State Administration for Market Regulation Released by the National Standardization Administration directory Preface III Introduction V 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Symbols and Abbreviations 3 4.1 Symbol 3 4.2 Abbreviations 4 5 Special Control Diagram 4 6 Moving Average and Moving Range Control Chart 5 6.1 Overview 5 6.2 Control Limits 5 6.3 Explanation 5 6.4 Advantage 5 6.5 less than 5 6.6 Example 6 7 Z Figure 8 7.1 Overview 8 7.2 Control limits 8 7.3 Advantage 8 7.4 Less than 8 7.5 Example 8 8 Group-Based Control Charts 10 8.1 Overview 10 8.2 Control limits 10 8.3 Advantages 11 8.4 Less than 11 8.5 Example 11 9 Extreme value control chart 14 9.1 Overview 14 9.2 Control limits 14 9.3 Interpretation 15 9.4 Advantages 15 9.5 less than 15 9.6 Example 15 10 Trend Control Chart 17 10.1 Overview 17 10.2 Control limits 17 10.3 Advantages 18 10.4 Less than 18 10.5 Example 18 11 Coefficient of Variation Control Chart 20 11.1 Overview 20 11.2 Control limits 21 11.3 Advantages 21 11.4 Less than 21 11.5 Example 21 12 Non-normal data control chart 23 12.1 Overview 23 12.2 Control Limits 23 12.3 Example 24 13 Normalized p control chart 30 13.1 Overview 30 13.2 Control Limits 30 13.3 Strengths and weaknesses 30 13.4 Example 30 14 Disadvantages Control Chart 32 14.1 Overview 32 14.2 Criteria for the selection of disadvantage weights 32 14.3 Example of weighting textile product shortcomings 33 14.4 Control Limits 33 14.5 Interpretation 34 14.6 Advantages 34 14.7 less than 34 14.8 Example 34 15 Gauge Inspection Control Chart 38 15.1 Overview 38 15.2 Lower and upper limits 38 15.3 Initial steps 38 15.4 Quantity and control limits 39 15.5 Drawing 39 15.6 Interpretation 40 15.7 Advantages 40 15.8 less than 40 15.9 Estimation of the Process Mean and Process Variation 40 15.10 Example 40 Appendix A (Informative) Parameters for Calculating Control Limits 44 Reference 46 forewordThis document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules of Standardization Documents" drafted. This document is part 5 of GB/T 17989.GB/T 17989 has released the following parts. --- Control Charts Part 1.General Guidelines; --- Control Charts Part 2.General Control Charts; --- Control Charts Part 3.Acceptance Control Charts; --- Control Charts Part 4.Cumulative and Control Charts; --- Statistical method control charts for quality control in production processes - Part 5.Special control charts; --- Statistical method control charts for quality control in production processes Part 6.Exponentially weighted moving average control charts --- Statistical method control chart for quality control in production process Part 7.Multivariate control chart; --- Statistical method control chart for quality control in production process Part 8.Control method for short cycle and small batch; --- Statistical methods for quality control of production process control charts Part 9.Stationary process control charts. This document is modified and adopted ISO 7870-5.2014 "Control Charts - Part 5.Special Control Charts". The structural differences between this document and ISO 7870-5.2014 and their reasons are as follows. --- Increase the chapter number of the suspension section in Chapters 6 to 15, and adjust the number of other chapters to meet the requirements of national standards. The technical differences between this document and ISO 7870-5.2014 and their reasons are as follows. --- Added "7.5.2 Explanation From Figure 2, it can be seen that the points corresponding to the 11th, 24th, 26th, and 27th subgroups fall outside the control limits, and further investigations are required. The reason for the out-of-control process", the original text lacks explanation; ---Added the description that the data does not obey the normal distribution (see 12.1), "If the data does not obey the normal distribution, you should first find out that the data does not obey the normal distribution. If it is confirmed that the data obeys some other distribution, the upper and lower bounds are constructed according to its distribution”, the original description unclear; --- Added Figure 7 (see 12.3.1) to test the normality of the data, indicating that it does not obey the normal distribution. state test; --- Added "Fig. 13 Mean Range Chart" (see 15.10.2), the original text lacks a diagram. The following editorial changes have been made to this document. --- Change the standard name to "Production Process Quality Control Statistical Methods Control Chart Part 5.Special Control Chart"; ---In 10.5.3 "x= i=1 xi 25 = 49.440 25 = 1.9776 " to "x= i=1 xi 25 = 49.440 25 = 1.9776 "; --- Change "variation coefficient ν" in Chapter 11 to "variation coefficient CV"; ---Change "UCL=x 99.865percentile×saverage" in 12.2.3.3 to "UCL=x z99.865×saverage", "LCL= x 0.135percentile×saverage” is changed to “LCL=x z0.135×saverage”; ---Change "B3=0.0284" in 12.3.2.1 to "B3=0.284"; --- The original z column data in Table 9 in 13.4.1 is incorrectly calculated, and all should be revised; --- Put "ci=∑ in 14.4 j=1 cij " to "ci=∑ j=1 cij "; --- Replace "UCL=d 3 ∑ in 14.8.1 i=1 w2ici Nnj 1/2 =1.203 4250×177 1/2 4.02 3.25=7.45” changed to "UCL=d 3 i=1 w2ici Nn =4.203 4250×177 =4.20 3.25=7.45"; --- Delete "these values of a and b are used to calculate the upper and lower measurement limits" in the original 15.1; --- Modify the data "20.47" of the 18th subgroup of the average column of Table 12 in 15.10.1 to "20.32", the 18th of the range column The data "2.49" of the subgroup is modified to "2.96". Please note that some content of this document may be patented. The issuing agency of this document assumes no responsibility for identifying patents. This document is proposed and managed by the National Standardization Technical Committee on the Application of Statistical Methods (SAC/TC21). This document was drafted by. Qingdao University, China National Institute of Standardization, Zhongtong Bus Co., Ltd., Anhui Agricultural University, Jiangsu Science and Technology the University. The main drafters of this document. Li Lili, Zhang Xuan, Zhang Fan, Zhu Feng, Wu Guangyu, Zhao Jing, Cheng Jing.IntroductionControl charts are commonly used statistical tools in process control to monitor deviations in the process and keep the process stable. GB/T 17989 control Figure series standards are divided into the following 9 parts. --- Control Charts Part 1.General Guidelines. The purpose is to give the basic terms, principles and classification of control charts, as well as the selection of control charts. guide. --- Control charts Part 2.General control charts. The purpose is to establish guidelines for process control using conventional control charts. --- Control charts Part 3.Acceptance control charts. The purpose is to establish guidelines for the use of acceptance control charts for process control, and to specify General procedure for determining subgroup sample sizes, action limits, and decision criteria. --- Control Charts Part 4.Cumulative and Control Charts. The purpose is to establish the application of cumulative sum techniques for process monitoring, control and retrospective Statistical methods of analysis. --- Statistical methods for quality control of production process control charts Part 5.Special control charts. The purpose is to establish the understanding and application of special A guide to statistical process control with control charts. --- Production process quality control statistical methods control charts Part 6.Exponentially weighted moving average control charts. The purpose is to establish A guide to solving and applying exponentially weighted moving average (EWMA) control charts for statistical process control. --- Statistical methods for quality control of production process control charts Part 7.Multivariate control charts. The purpose is to establish the construction and application of diversity Control charts are guidelines for statistical process control and establish routines for the use and understanding of multivariate control charts for measurement data. --- Statistical methods of production process quality control control chart Part 8.Control methods for short cycle and small batches. The purpose is to establish When the group size is 1, the conventional metrology control chart is used to detect the method of short cycle and small batch production process. --- Statistical methods for quality control of production process control charts Part 9.Stationary process control charts. The purpose is to establish the construction and application Control charts are guidelines for controlling stationary processes. Conventional control charts given in GB/T 17989.2 can help monitor unnatural patterns of process-induced data variation and provide judgment Criteria for whether the interrupt process is in statistical control. However, for metrological data, there are some special cases where using conventional control charts to Unnatural patterns of process variation have problems of undetectable or low detection efficiency, as described in the following situations. a) It takes a considerable amount of time to produce a product, and the time interval for sample acquisition is large; b) There are multiple production processes to produce a product, and these production processes have approximately the same productivity, process average and process ability; c) the process average varies systematically; d) The sample size is large and the order of production is irrelevant; e) The process does not have a constant target value. In the above situations, special control charts can be used. Likewise, some special cases may be encountered when dealing with count data. In some cases, it may be desirable to focus on subgroups of Severity, but different disqualifications have different degrees of severity. Therefore, all types of nonconformities cannot be treated equally. According to unqualified It is necessary to give different weights to each type of unqualified, and calculate the corresponding defect score accordingly. Calculate control limits based on defect scores, and Draw the corresponding control chart to control the process. When controlling the positional and shape parameters of process measurable characteristics, in some cases, for practical reasons, there are counts A situation in which inspection is preferred over metrological inspection (eg, inspection by means of a gauge). It may also be possible to obtain assembly operations below the lower specification limit (no Pass gauge) and information on the quantity of product above the upper specification limit (pass gauge). In this case, an a,b chart can be used. There may also be situations where the data do not follow a normal distribution. Except for special processes in the manufacturing industry, non-normal data in the service industry also often encountered. In such cases, control charts for nonnormal data can be used. The primary purpose of this document is to provide guidance on how to apply special control charts to process controls that address the typical special situations described above. Production process quality control statistical method control chart Part 5.Special Control Charts1 ScopeThis document describes guidelines for understanding and applying special control charts for statistical process control. This document is suitable for situations where conventional control charts cannot detect unnatural patterns of process variation or are less efficient at detecting them. For metrology data, the special control charts included in this document are. a) moving average and moving range charts; b) Z diagram; c) group-based control charts; d) extreme value control chart; e) trend control chart; f) Coefficient of variation control chart; g) Control charts for nonnormal data. For count data, the special control charts included in this document are. a) normalized p control chart; b) Defect control chart; c) Gauge inspection control chart. The guidance given in this document also includes the conditions of use, control limits, advantages and disadvantages, and examples of each type of control chart.2 Normative referencesThe contents of the following documents constitute essential provisions of this document through normative references in the text. Among them, dated citations documents, only the version corresponding to that date applies to this document; for undated references, the latest edition (including all amendments) applies to this document. GB/T 3358.2 Statistical vocabulary and symbols - Part 2.Applied statistics (GB/T 3358.2-2009, ISO 3534-2.2006, IDT)3 Terms and DefinitionsThe terms and definitions defined in GB/T 3358.2 and the following apply to this document. 3.1 control chart A graph plotting a sequence of sample statistic values in a specific order to monitor, control, and reduce process variation. Note 1.The specific order usually refers to the chronological order or the order in which the samples were obtained. NOTE 2 Control charts are most effective when used to monitor characteristics about the final product or service. [Source. GB/T 3358.2-2009, 2.3.1] ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 17989.5-2022_English be delivered?Answer: Upon your order, we will start to translate GB/T 17989.5-2022_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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