{"title":"制造系统中的生产力和人为因素改进。A系统建模与仿真方法","authors":"I. Taleb, A. Etienne, A. Siadat","doi":"10.1109/IEEM50564.2021.9673046","DOIUrl":null,"url":null,"abstract":"Systems modeling, and simulation have been widely used to better understand the behavior of complex systems. Some of the main benefits of these tools are the cheaper and faster way of testing compared to real-life testing, and the flexibility that simulation offers via the tweaking of parameters, variables, and functions. It has drawbacks too, such as precision and accuracy, difficulty of modeling and simulating productivity. In fact, there are multiple ways of defining productivity, either through activities or output or time. This article offers a new definition of productivity and in contrast, non-productivity, and the different levels between them, and we study the possibility to model complex manufacturing systems and simulate them. The main contribution of this research consists in developing a flexible model and tool able to simulate complex manufacturing systems. The goal of this tool is to model productivity and be flexible enough to allow for easier and cheaper alternatives to testing, and complex enough to encompass a large part of possibilities.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"1 1","pages":"6-10"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Productivity and Human Factors Improvement in Manufacturing Systems. A Systems Modeling and Simulation Approach\",\"authors\":\"I. Taleb, A. Etienne, A. Siadat\",\"doi\":\"10.1109/IEEM50564.2021.9673046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Systems modeling, and simulation have been widely used to better understand the behavior of complex systems. Some of the main benefits of these tools are the cheaper and faster way of testing compared to real-life testing, and the flexibility that simulation offers via the tweaking of parameters, variables, and functions. It has drawbacks too, such as precision and accuracy, difficulty of modeling and simulating productivity. In fact, there are multiple ways of defining productivity, either through activities or output or time. This article offers a new definition of productivity and in contrast, non-productivity, and the different levels between them, and we study the possibility to model complex manufacturing systems and simulate them. The main contribution of this research consists in developing a flexible model and tool able to simulate complex manufacturing systems. The goal of this tool is to model productivity and be flexible enough to allow for easier and cheaper alternatives to testing, and complex enough to encompass a large part of possibilities.\",\"PeriodicalId\":6818,\"journal\":{\"name\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"1 1\",\"pages\":\"6-10\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM50564.2021.9673046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM50564.2021.9673046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Productivity and Human Factors Improvement in Manufacturing Systems. A Systems Modeling and Simulation Approach
Systems modeling, and simulation have been widely used to better understand the behavior of complex systems. Some of the main benefits of these tools are the cheaper and faster way of testing compared to real-life testing, and the flexibility that simulation offers via the tweaking of parameters, variables, and functions. It has drawbacks too, such as precision and accuracy, difficulty of modeling and simulating productivity. In fact, there are multiple ways of defining productivity, either through activities or output or time. This article offers a new definition of productivity and in contrast, non-productivity, and the different levels between them, and we study the possibility to model complex manufacturing systems and simulate them. The main contribution of this research consists in developing a flexible model and tool able to simulate complex manufacturing systems. The goal of this tool is to model productivity and be flexible enough to allow for easier and cheaper alternatives to testing, and complex enough to encompass a large part of possibilities.