{"title":"制造应用的仿真实验设计","authors":"P. Farrington, J. J. Swain","doi":"10.1109/WSC.1993.718031","DOIUrl":null,"url":null,"abstract":"The statistical analysis of simulation experiments is frequently honored more in the breach than in practice, yet the benefits of planning and proper design can often increase the precision of estimates and strengthen confidence in conclusions drawn. While simulation experiments are broadly similar to any statistical experiment, there are a number of differences. Manufacturing models are used to illustrate the methodology described.","PeriodicalId":177234,"journal":{"name":"Proceedings of 1993 Winter Simulation Conference - (WSC '93)","volume":"49 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Design of Simulation Experiments with Manufacturing Applications\",\"authors\":\"P. Farrington, J. J. Swain\",\"doi\":\"10.1109/WSC.1993.718031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The statistical analysis of simulation experiments is frequently honored more in the breach than in practice, yet the benefits of planning and proper design can often increase the precision of estimates and strengthen confidence in conclusions drawn. While simulation experiments are broadly similar to any statistical experiment, there are a number of differences. Manufacturing models are used to illustrate the methodology described.\",\"PeriodicalId\":177234,\"journal\":{\"name\":\"Proceedings of 1993 Winter Simulation Conference - (WSC '93)\",\"volume\":\"49 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1993 Winter Simulation Conference - (WSC '93)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC.1993.718031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1993 Winter Simulation Conference - (WSC '93)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.1993.718031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Simulation Experiments with Manufacturing Applications
The statistical analysis of simulation experiments is frequently honored more in the breach than in practice, yet the benefits of planning and proper design can often increase the precision of estimates and strengthen confidence in conclusions drawn. While simulation experiments are broadly similar to any statistical experiment, there are a number of differences. Manufacturing models are used to illustrate the methodology described.