{"title":"具有随机需求的易故障制造工厂的生产计划","authors":"M. Eleftheriu, A. Desrochers","doi":"10.1109/CIM.1988.5393","DOIUrl":null,"url":null,"abstract":"The production planning of a manufacturing facility with uncertain capacity and stochastic demand is discussed. The plan is based on the hedging point policy as derived by S.B. Gershwin et al. (1985). The same policy is applied for a system that has stochastic demand and is prone to failures. The same policy can also be used to determine the size of the buffer for a system with two machines. Simulation is used to evaluate the method, since there is no analytic proof of optimality.<<ETX>>","PeriodicalId":334994,"journal":{"name":"[Proceedings] 1988 International Conference on Computer Integrated Manufacturing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Production planning for a prone to failures manufacturing facility with stochastic demand\",\"authors\":\"M. Eleftheriu, A. Desrochers\",\"doi\":\"10.1109/CIM.1988.5393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The production planning of a manufacturing facility with uncertain capacity and stochastic demand is discussed. The plan is based on the hedging point policy as derived by S.B. Gershwin et al. (1985). The same policy is applied for a system that has stochastic demand and is prone to failures. The same policy can also be used to determine the size of the buffer for a system with two machines. Simulation is used to evaluate the method, since there is no analytic proof of optimality.<<ETX>>\",\"PeriodicalId\":334994,\"journal\":{\"name\":\"[Proceedings] 1988 International Conference on Computer Integrated Manufacturing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1988 International Conference on Computer Integrated Manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIM.1988.5393\",\"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] 1988 International Conference on Computer Integrated Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIM.1988.5393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Production planning for a prone to failures manufacturing facility with stochastic demand
The production planning of a manufacturing facility with uncertain capacity and stochastic demand is discussed. The plan is based on the hedging point policy as derived by S.B. Gershwin et al. (1985). The same policy is applied for a system that has stochastic demand and is prone to failures. The same policy can also be used to determine the size of the buffer for a system with two machines. Simulation is used to evaluate the method, since there is no analytic proof of optimality.<>