{"title":"精益、数据和统计","authors":"Pere Grima, Lourdes Rodero, X. Tort-Martorell","doi":"10.1080/08982112.2022.2141125","DOIUrl":null,"url":null,"abstract":"Key Point Although Lean techniques are often presented as something unrelated to statistics, the truth is that many Lean techniques and methodologies use data in varying degrees. Often this data is somewhat underused, and a better use of statistical thinking and basic statistical techniques will enhance the usually good results of these methodologies.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"364 - 369"},"PeriodicalIF":1.3000,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lean, data, and statistics\",\"authors\":\"Pere Grima, Lourdes Rodero, X. Tort-Martorell\",\"doi\":\"10.1080/08982112.2022.2141125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Key Point Although Lean techniques are often presented as something unrelated to statistics, the truth is that many Lean techniques and methodologies use data in varying degrees. Often this data is somewhat underused, and a better use of statistical thinking and basic statistical techniques will enhance the usually good results of these methodologies.\",\"PeriodicalId\":20846,\"journal\":{\"name\":\"Quality Engineering\",\"volume\":\"35 1\",\"pages\":\"364 - 369\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quality Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/08982112.2022.2141125\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quality Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/08982112.2022.2141125","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Key Point Although Lean techniques are often presented as something unrelated to statistics, the truth is that many Lean techniques and methodologies use data in varying degrees. Often this data is somewhat underused, and a better use of statistical thinking and basic statistical techniques will enhance the usually good results of these methodologies.
期刊介绍:
Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed.
You are invited to submit manuscripts and application experiences that explore:
Experimental engineering design and analysis
Measurement system analysis in engineering
Engineering process modelling
Product and process optimization in engineering
Quality control and process monitoring in engineering
Engineering regression
Reliability in engineering
Response surface methodology in engineering
Robust engineering parameter design
Six Sigma method enhancement in engineering
Statistical engineering
Engineering test and evaluation techniques.