{"title":"基于仿真的Runs-Type规则非参数控制图对比分析","authors":"I. Triantafyllou","doi":"10.5772/intechopen.91040","DOIUrl":null,"url":null,"abstract":"In this chapter, we study well-known distribution-free Shewhart-type monitoring schemes based on order statistics. In order to empower the in- and out-of-control performance of the control charts being under consideration, several runs-type rules are enhanced. The simulation-based experimentation carried out reveals that the proposed schemes achieve remarkable efficiency for detecting possible shifts in the distribution of the underlying process.","PeriodicalId":194972,"journal":{"name":"Quality Control - Intelligent Manufacturing, Robust Design and Charts","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Simulation-Based Comparative Analysis of Nonparametric Control Charts with Runs-Type Rules\",\"authors\":\"I. Triantafyllou\",\"doi\":\"10.5772/intechopen.91040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this chapter, we study well-known distribution-free Shewhart-type monitoring schemes based on order statistics. In order to empower the in- and out-of-control performance of the control charts being under consideration, several runs-type rules are enhanced. The simulation-based experimentation carried out reveals that the proposed schemes achieve remarkable efficiency for detecting possible shifts in the distribution of the underlying process.\",\"PeriodicalId\":194972,\"journal\":{\"name\":\"Quality Control - Intelligent Manufacturing, Robust Design and Charts\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quality Control - Intelligent Manufacturing, Robust Design and Charts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5772/intechopen.91040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Control - Intelligent Manufacturing, Robust Design and Charts","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/intechopen.91040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation-Based Comparative Analysis of Nonparametric Control Charts with Runs-Type Rules
In this chapter, we study well-known distribution-free Shewhart-type monitoring schemes based on order statistics. In order to empower the in- and out-of-control performance of the control charts being under consideration, several runs-type rules are enhanced. The simulation-based experimentation carried out reveals that the proposed schemes achieve remarkable efficiency for detecting possible shifts in the distribution of the underlying process.
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