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Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations

机译:同时使用多范式模拟在生产设施规划中同时考虑疏散安全性和生产率

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摘要

Manufacturing facilities are expected to maintain a high level of production and at the same time, employ strict safety standards to ensure the safe evacuation of the people in the event of emergencies (fire is considered in this paper). These two goals are often conflicting. This paper presents a methodology to evaluate evacuation safety versus productivity concurrently for various, widely known manufacturing layouts. While the safety performance indicators such as evacuation times are inferred from the crowd (agent based) simulation, the productivity performance indicators (e.g. throughput) are analyzed using the discrete event simulation. To this end, this research focuses on creating innovative techniques for developing accurate crowd simulations, where Belief-Desire-Intention (BDI) agent framework is employed to build each person's individual actions and the interactions between them. The data model and rule based action algorithms for each agent are reverse-engineered from the human-in-the-loop experiments in the immersive virtual reality environments. Finally, experiments are conducted using the constructed simulations to compare safety and productivity for different layouts. To demonstrate the proposed methodology, an automotive power-train (engine and transmission) manufacturing plant was used. Initial results look quite promising.
机译:预计生产设施将保持较高的生产水平,同时采用严格的安全标准以确保在紧急情况下人员安全撤离(本文考虑了火灾)。这两个目标经常是矛盾的。本文提出了一种方法,用于同时评估各种广为人知的制造布局的疏散安全性与生产率。从人群(基于代理)模拟中推断出诸如疏散时间之类的安全绩效指标时,使用离散事件模拟来分析生产力绩效指标(例如吞吐量)。为此,本研究着重于创建创新技术以开发准确的人群模拟,其中采用了信念-愿望-意向(BDI)代理框架来构建每个人的个人行为及其之间的相互作用。在沉浸式虚拟现实环境中,通过在环实验进行逆向工程,对每个代理的数据模型和基于规则的动作算法进行了逆向工程。最后,使用构建的模拟进行实验,以比较不同布局的安全性和生产率。为了演示所提出的方法,使用了汽车动力总成(发动机和变速器)制造厂。初步结果看起来很有希望。

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