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Making sense of transient responses in simulation studies

机译:在仿真研究中理解瞬态响应

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Traditional simulation modelling focuses upon the analysis of steady-state data. This focus may not be appropriate, however, for the study of transient responses - data reflecting some form of disruption or change in the system norms. Transient responses are often encountered when dealing with new product introductions, changes in production systems, or supply chain disruptions. In these situations, it is the transient response, how the system responds to these changes as well as the tactics and strategies used to deal with these changes, that tend to be of the greatest interest. Unfortunately, current approaches that focus on analysing such responses are limited. This paper introduces a new approach for analysing transient responses - one that merges outlier detection, a time series analysis tool, with simulation modelling. This combined approach allows the researcher to identify those factors that have the greatest impact upon operations during these transient conditions. Using a simulated supply chain disruption to illustrate the potential of the approach, it is shown that the new approach expands the applicability of simulation and enables certain types of problems to be investigated with confidence not previously provided.
机译:传统的仿真建模专注于稳态数据的分析。但是,此重点可能不适用于瞬态响应的研究-反映系统规范某种形式的破坏或变化的数据。在处理新产品介绍,生产系统变更或供应链中断时,经常会遇到瞬态响应。在这些情况下,人们最感兴趣的是瞬态响应,系统如何响应这些更改以及用于应对这些更改的策略和策略。不幸的是,目前专注于分析此类响应的方法是有限的。本文介绍了一种用于分析瞬态响应的新方法-该方法将离群值检测(一种时间序列分析工具)与仿真建模相结合。这种组合方法使研究人员能够识别出在这些瞬态条件下对运行产生最大影响的因素。使用模拟的供应链中断来说明该方法的潜力,结果表明,该新方法扩展了模拟的适用性,并使某些类型的问题能够以以前没有的信心进行调查。

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