Performance analysis of Stochastic Petri Nets in manufacturing systems.

Petri Nets have been recognised as a powerful tool for modelling and analysis of discrete event systems. For complicated dynamical systems with many interdependent components, stochastic discrete event models such as Markov models or Stochastic Petri Nets are commonly used (SPN). Such a model is mathematically sound and can be used to carry out either analytical or numerical simulations. The time-dependent token flow for each place in the model, as well as the firing frequency of each transition, is determined via stochastic simulation of the network's time-dependent dynamic behaviour. Steady-state behaviour values of Continuous Time Markov Chain (CTMC) can be used for performance analysis. The scope of this paper pertains to the analysis of the stochastic marking process of the net based on CTMC, a semi-Markov Chain and a generalised semi-Markov process. [ABSTRACT FROM AUTHOR]