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Anticipating the Chaotic Behaviour of Industrial Systems Based on Stochastic, Event-Driven Simulations

机译:基于随机,事件驱动模拟的工业系统的混沌行为预测

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In logistics and industrial production managers must deal with the impact of stochastic events to improve performances and reduce costs. In fact, production and logistics systems are generally designed considering some parameters as deterministically distributed. While this assumption is mostly used for preliminary prototyping, it is sometimes also retained during the final design stage, and especially for estimated parameters (i.e. Market Request). The proposed methodology can determine the impact of stochastic events in the system by evaluating the chaotic threshold level. Such an approach, based on the application of a new and innovative methodology, can be implemented to find the condition under which chaos makes the system become uncontrollable. Starting from problem identification and risk assessment, several classification techniques are used to carry out an effect analysis and contingency plan estimation. In this paper the authors illustrate the methodology with respect to a real industrial case: a production problem related to the logistics of distributed chemical processing.
机译:在物流和工业生产经理必须处理随机事件的影响,提高表演,降低成本。实际上,生产和物流系统通常考虑确定的一些参数,如确定性分布。虽然这种假设主要用于初步原型,但有时也在最终设计阶段保留,特别是对于估计的参数(即市场请求)。所提出的方法可以通过评估混沌阈值水平来确定系统中随机事件的影响。可以实施基于新的和创新方法的应用,以找到混乱使系统变得无法控制的条件。从问题识别和风险评估开始,使用几种分类技术来执行效果分析和应急计划估计。在本文中,作者说明了关于实际工业案例的方法:与分布式化学加工的物流相关的生产问题。

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