{"title":"田口损失函数下ewma -半圆图的经济统计设计","authors":"Shin-Li Lu","doi":"10.1504/EJIE.2019.10022257","DOIUrl":null,"url":null,"abstract":"A single exponentially weighted moving average (EWMA) chart is effectively used to monitor the process mean and/or variance simultaneously. An EWMA-semicircle (EWMA-SC) chart designed from the economic-statistical perspective is proposed, which incorporates Taguchi's quadratic loss function into Lorenzen and Vance's cost model. Moreover, economic-statistical performance and the effect on process capability index are compared to those with sum of square EWMA (SS-EWMA) and maximum EWMA (MaxEWMA) charts. The optimal decision variables - namely, sample size n, sampling interval time h, control limit width L and smoothing constant λ - are obtained by minimising the expected cost function. Via simulations, the EWMA-SC chart is found to incur the smallest expected cost when a process mean and variance simultaneously shift. However, the MaxEWMA chart incurs the lowest cost of defective products when a process means shifts on its own. [Received: 1 May 2017; Revised: 22 August 2018; Accepted: 3 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Economic-statistical design of EWMA-semicircle charts under the Taguchi loss function\",\"authors\":\"Shin-Li Lu\",\"doi\":\"10.1504/EJIE.2019.10022257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A single exponentially weighted moving average (EWMA) chart is effectively used to monitor the process mean and/or variance simultaneously. An EWMA-semicircle (EWMA-SC) chart designed from the economic-statistical perspective is proposed, which incorporates Taguchi's quadratic loss function into Lorenzen and Vance's cost model. Moreover, economic-statistical performance and the effect on process capability index are compared to those with sum of square EWMA (SS-EWMA) and maximum EWMA (MaxEWMA) charts. The optimal decision variables - namely, sample size n, sampling interval time h, control limit width L and smoothing constant λ - are obtained by minimising the expected cost function. Via simulations, the EWMA-SC chart is found to incur the smallest expected cost when a process mean and variance simultaneously shift. However, the MaxEWMA chart incurs the lowest cost of defective products when a process means shifts on its own. [Received: 1 May 2017; Revised: 22 August 2018; Accepted: 3 January 2019]\",\"PeriodicalId\":314867,\"journal\":{\"name\":\"European J. of Industrial Engineering\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European J. of Industrial Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/EJIE.2019.10022257\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European J. of Industrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/EJIE.2019.10022257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Economic-statistical design of EWMA-semicircle charts under the Taguchi loss function
A single exponentially weighted moving average (EWMA) chart is effectively used to monitor the process mean and/or variance simultaneously. An EWMA-semicircle (EWMA-SC) chart designed from the economic-statistical perspective is proposed, which incorporates Taguchi's quadratic loss function into Lorenzen and Vance's cost model. Moreover, economic-statistical performance and the effect on process capability index are compared to those with sum of square EWMA (SS-EWMA) and maximum EWMA (MaxEWMA) charts. The optimal decision variables - namely, sample size n, sampling interval time h, control limit width L and smoothing constant λ - are obtained by minimising the expected cost function. Via simulations, the EWMA-SC chart is found to incur the smallest expected cost when a process mean and variance simultaneously shift. However, the MaxEWMA chart incurs the lowest cost of defective products when a process means shifts on its own. [Received: 1 May 2017; Revised: 22 August 2018; Accepted: 3 January 2019]