以改进为目的的基于MSA属性研究数据集的检验误差分析过程:第二部分-结果与讨论

K. Knop
{"title":"以改进为目的的基于MSA属性研究数据集的检验误差分析过程:第二部分-结果与讨论","authors":"K. Knop","doi":"10.2478/cqpi-2020-0018","DOIUrl":null,"url":null,"abstract":"Abstract In the first article in this series, the research methodology concerning the analysis of inspection errors based on MSA attribute study data set for the improvement purposes was presented. In the final article in the series, applying the methodology in practice step by step was presented. Instructions for correct performance of the analysis, in compliance with the author’s procedure, were determined. Both advantages and disadvantages of the developed approach were underlined.","PeriodicalId":166707,"journal":{"name":"Conference Quality Production Improvement – CQPI","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis Procedure of Inspection Errors Based on MSA Attribute Study Data Set for the Improvement Purposes: Part 2 – Results and Discussion\",\"authors\":\"K. Knop\",\"doi\":\"10.2478/cqpi-2020-0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In the first article in this series, the research methodology concerning the analysis of inspection errors based on MSA attribute study data set for the improvement purposes was presented. In the final article in the series, applying the methodology in practice step by step was presented. Instructions for correct performance of the analysis, in compliance with the author’s procedure, were determined. Both advantages and disadvantages of the developed approach were underlined.\",\"PeriodicalId\":166707,\"journal\":{\"name\":\"Conference Quality Production Improvement – CQPI\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Quality Production Improvement – CQPI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/cqpi-2020-0018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Quality Production Improvement – CQPI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/cqpi-2020-0018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在本系列的第一篇文章中,提出了基于MSA属性研究数据集的检测误差分析的研究方法。在本系列的最后一篇文章中,介绍了在实践中逐步应用该方法。根据作者的程序,确定了正确执行分析的说明。强调了已开发的方法的优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis Procedure of Inspection Errors Based on MSA Attribute Study Data Set for the Improvement Purposes: Part 2 – Results and Discussion
Abstract In the first article in this series, the research methodology concerning the analysis of inspection errors based on MSA attribute study data set for the improvement purposes was presented. In the final article in the series, applying the methodology in practice step by step was presented. Instructions for correct performance of the analysis, in compliance with the author’s procedure, were determined. Both advantages and disadvantages of the developed approach were underlined.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信