Intelligent token Petri nets for modelling and control of reconfigurable automated manufacturing systems with dynamical changes

Abstract

Considering dynamical changes in manufacturing systems, such as rework and system reconfiguration, this paper presents a new Petri net (PN) model called an intelligent token PN (ITPN). In this model, tokens representing job instances carry real-time knowledge about system status and changes just like smart cards in practice. By taking this advantage, dynamical changes of a system can be easily modelled. An ITPN can model a system in a modular way, leading to a very compact model. When changes occur, it needs to modify only the changed part from the current model. Thus, an ITPN is highly reusable. Based on the ITPN model, a deadlock-free control (DFC) policy is presented. With this control policy, an ITPN is deadlock-free and reversible. In particular, when an ITPN is changed according to the changes of the system, the policy is still applicable to the modified model. Thus, one need not modify the control policy when an ITPN model is modified.