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

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.