L. Rabelo, M. Helal, Albert T. Jones, Jason Min, Y. Son, A. Deshmukh
{"title":"New manufacturing modeling methodology: a hybrid approach to manufacturing enterprise simulation","authors":"L. Rabelo, M. Helal, Albert T. Jones, Jason Min, Y. Son, A. Deshmukh","doi":"10.5555/1030818.1030968","DOIUrl":null,"url":null,"abstract":"Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions. engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on the system as measured by one or more performance measures. In this paper, we focus on production decisions, where discrete-event simulation models perform that evaluation. We argue that such an evaluation is limited in time and scope, and does not capture the potential impact of these decisions on the whole enterprise. We propose integrating these discrete-event models with system dynamic models and we show the potential benefits of such an integration using an example of semiconductor enterprise.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Online World Conference on Soft Computing in Industrial Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/1030818.1030968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions. engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on the system as measured by one or more performance measures. In this paper, we focus on production decisions, where discrete-event simulation models perform that evaluation. We argue that such an evaluation is limited in time and scope, and does not capture the potential impact of these decisions on the whole enterprise. We propose integrating these discrete-event models with system dynamic models and we show the potential benefits of such an integration using an example of semiconductor enterprise.