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Performance assessment of industrial control system during pre-sales uncertain context using automatic Colored Petri Nets model generation

机译:售前不确定环境下工业控制系统的性能评估,使用有色Petri网模型自动生成

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Industrial control systems (ICS) are defined with hardware and software components dedicated to control and monitoring tasks for factory process. Proper functioning of ICS architectures is mainly linked to the performance they offer. System integrators (SI) must know performance of the architecture they propose to the customers by assessing them. Many methodologies have already proven their capabilities to assess ICS architecture performance. One of them is colored Petri Nets (CPN). To assess the performance of ICS architecture using CPN involve defining manually the model. Pre-sales uncertain context involves problematic making this manual model definition challenging. This paper introduces a concept allowing automatic CPN model generation by instantiation and parameterization. However before introducing the concept, the paper shows the problematic involved by the pre-sales context. Then shows why CPN methodology is a relevant solution for assessing the performance of ICS in this context.
机译:工业控制系统(ICS)由专用于控制和监视工厂过程任务的硬件和软件组件定义。 ICS架构的正常运行主要与其提供的性能有关。系统集成商(SI)必须通过评估来了解他们向客户提出的架构的性能。许多方法已经证明了其评估ICS架构性能的能力。其中之一是有色Petri网(CPN)。要评估使用CPN的ICS体系结构的性能,需要手动定义模型。售前不确定的环境会带来问题,使此手动模型定义具有挑战性。本文介绍了一种允许通过实例化和参数化自动生成CPN模型的概念。但是,在介绍该概念之前,本文显示了售前环境所涉及的问题。然后说明了CPN方法为何是在这种情况下评估ICS性能的相关解决方案。

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