{"title":"系统级优化通过使用统计仿真","authors":"R. Cofer, T. Sanders, D. P. Means","doi":"10.1109/SOUTHC.1996.535119","DOIUrl":null,"url":null,"abstract":"A critical issue in the optimization of systems is that of the design of the part, component or system for manufacture. The system engineering function typically finds an acceptable but theoretical design solution with little up-front attention being paid to the \"real-world\" effects caused by manufacturing and operational variabilities. Alternatively when system design attention is paid to such variabilities, it is usually via a \"worst-case\" design process which can only further complicate the manufacturing process and raise costs. To be truly effective in the near future of small-lot flexible system manufacturing, systems engineering must not only optimize against the effects of changing manufacturing variabilities, but the overall systems design and manufacturing processes must be woven more closely together so as to permit routine first pass success. As a result of the above issues, the importance of running early statistically based system level design simulations has become particularly critical in this period of increasingly flexible manufacturing processes, defense conversions and dual-use technologies.","PeriodicalId":199600,"journal":{"name":"Southcon/96 Conference Record","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"System level optimization through the use of statistical simulation\",\"authors\":\"R. Cofer, T. Sanders, D. P. Means\",\"doi\":\"10.1109/SOUTHC.1996.535119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A critical issue in the optimization of systems is that of the design of the part, component or system for manufacture. The system engineering function typically finds an acceptable but theoretical design solution with little up-front attention being paid to the \\\"real-world\\\" effects caused by manufacturing and operational variabilities. Alternatively when system design attention is paid to such variabilities, it is usually via a \\\"worst-case\\\" design process which can only further complicate the manufacturing process and raise costs. To be truly effective in the near future of small-lot flexible system manufacturing, systems engineering must not only optimize against the effects of changing manufacturing variabilities, but the overall systems design and manufacturing processes must be woven more closely together so as to permit routine first pass success. As a result of the above issues, the importance of running early statistically based system level design simulations has become particularly critical in this period of increasingly flexible manufacturing processes, defense conversions and dual-use technologies.\",\"PeriodicalId\":199600,\"journal\":{\"name\":\"Southcon/96 Conference Record\",\"volume\":\"158 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Southcon/96 Conference Record\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOUTHC.1996.535119\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Southcon/96 Conference Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOUTHC.1996.535119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
System level optimization through the use of statistical simulation
A critical issue in the optimization of systems is that of the design of the part, component or system for manufacture. The system engineering function typically finds an acceptable but theoretical design solution with little up-front attention being paid to the "real-world" effects caused by manufacturing and operational variabilities. Alternatively when system design attention is paid to such variabilities, it is usually via a "worst-case" design process which can only further complicate the manufacturing process and raise costs. To be truly effective in the near future of small-lot flexible system manufacturing, systems engineering must not only optimize against the effects of changing manufacturing variabilities, but the overall systems design and manufacturing processes must be woven more closely together so as to permit routine first pass success. As a result of the above issues, the importance of running early statistically based system level design simulations has become particularly critical in this period of increasingly flexible manufacturing processes, defense conversions and dual-use technologies.