N. Furian, Clemens Gutschi, D. Neubacher, C. Walker, M. O'Sullivan
{"title":"The Activity-Entity-Impact Method: Understanding Bottleneck Behavior of Simulation Models Demonstrated by an Emergency Department Model","authors":"N. Furian, Clemens Gutschi, D. Neubacher, C. Walker, M. O'Sullivan","doi":"10.1109/WSC40007.2019.9004751","DOIUrl":null,"url":null,"abstract":"Simulation models are often used to gain a better understanding of a system’s sensitivity to changes in the input parameters. Data gathered during simulation runs is aggregated to Key Performance Indicators (KPIs) that allow one to assess a model’s or system’s performance. KPIs do not provide a deeper understanding of the causes of the observed output because this is not their primary objective. By contrast, dynamic bottleneck methods both identify elements that yield the largest gain in productivity with increased availability and also visualize these elements over time to enable bottlenecks to be better understood. In this paper we discuss whether dynamic bottleneck detection methods can be utilized to identify, measure, and visualize causes of observed behavior in complex models. We extend standard bottleneck detection methods, and introduce the Activity-Entity-Impact-Method. The practicality of the method is demonstrated by an example model of a typical Emergency Department setting.","PeriodicalId":127025,"journal":{"name":"2019 Winter Simulation Conference (WSC)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC40007.2019.9004751","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
Simulation models are often used to gain a better understanding of a system’s sensitivity to changes in the input parameters. Data gathered during simulation runs is aggregated to Key Performance Indicators (KPIs) that allow one to assess a model’s or system’s performance. KPIs do not provide a deeper understanding of the causes of the observed output because this is not their primary objective. By contrast, dynamic bottleneck methods both identify elements that yield the largest gain in productivity with increased availability and also visualize these elements over time to enable bottlenecks to be better understood. In this paper we discuss whether dynamic bottleneck detection methods can be utilized to identify, measure, and visualize causes of observed behavior in complex models. We extend standard bottleneck detection methods, and introduce the Activity-Entity-Impact-Method. The practicality of the method is demonstrated by an example model of a typical Emergency Department setting.