Application of Extended Coloured Stochastic Petri Nets for Modelling and Analysis of RAMS+C of Production Systems

Modern production systems are characterized by numerous conjoint and interacting production machines each with sophisticated maintenance and logistic processes. To remain competitive, it is necessary to reduce the system downtimes by applying the optimal maintenance strategy and therefore reducing life cycle costs. Condition monitoring often is a very effective way to minimize downtimes of crucial system components such as ball screws, ball bearings and drives. But sometimes condition monitoring is not cost-effective or even reduces the system's operational availability. The decision whether it's reasonable to implement condition based maintenance or not requires a detailed analysis of the system's behavior. Since many analytical models of technical systems have significant limitations and simplifications, simulation techniques are applied very often In our paper we will present an improved comprehensive methodology for the modeling and analysis of production systems which has been basically introduced at the RAMS-Symposium in 2008. The model incorporates an extended colored stochastic Petri net (ECSPN) and a reliability block diagram (RBD) in a conjoint modeling procedure which allows a close-to-reality representation of a complex production system's behavior.