Lin Tan, B. Liu, Xing Li, Shunkun Yang, Xianghong Liu
{"title":"Insights into the complexity: A method to manage the complex system by controlling the couplings based on the systemic modeling","authors":"Lin Tan, B. Liu, Xing Li, Shunkun Yang, Xianghong Liu","doi":"10.1109/ICRSE.2017.8030813","DOIUrl":null,"url":null,"abstract":"New forms of complex systems with novel working patterns are emerging in contrast to our ignorance, to some degree, of their internal functioning mechanism. Research should be conducted to make better understandings of these complexity problems. In this paper, we proposed a method to study into the system complexity and to cope with it by controlling the system interactions and couplings based on the systemic modeling. A case study was conducted in which we described the system complexity in terms of interactions and couplings using FRAM. Based on that, the analysis was conducted and the risks of system accident were identified to be the result of the collaboration of function variabilities and the tight-couplings. Measures to control the couplings were suggested accordingly. With the effects of these measures, we could reduce the level of system couplings and manage the system complexity for better controlling.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRSE.2017.8030813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
New forms of complex systems with novel working patterns are emerging in contrast to our ignorance, to some degree, of their internal functioning mechanism. Research should be conducted to make better understandings of these complexity problems. In this paper, we proposed a method to study into the system complexity and to cope with it by controlling the system interactions and couplings based on the systemic modeling. A case study was conducted in which we described the system complexity in terms of interactions and couplings using FRAM. Based on that, the analysis was conducted and the risks of system accident were identified to be the result of the collaboration of function variabilities and the tight-couplings. Measures to control the couplings were suggested accordingly. With the effects of these measures, we could reduce the level of system couplings and manage the system complexity for better controlling.