Abstract
Deadlock resolution has been an important research topic in the field of automated manufacturing systems (AMSs). Researchers generally assume that AMS resources never break down whereas only a few resolve the issues of resource failures in the discrete-event supervision of AMSs. In fact, an AMS consists of a number of numerically controlled machines interacting with each other. The failure of resources happens unexpectedly. In this article, we allow parallel routes to use unreliable resources. Because of their powerful modeling capabilities, Petri nets are used to model the considered AMSs. By using a look-ahead control strategy, a robust supervisory control policy is developed for AMSs with assembly operations allowing resource failures. Our objective is to advance parts requiring failed resources in their remaining routes into a special position so as to release shared resources in case some unreliable resources fail. Consequently, those parts not necessarily requiring any failed resource can keep progressing all the time. The conventional methods are on the basis of monolithic and structure-oriented control specifications with centralized supervisors. Our policy can be implemented in a distributed, online, and local way. Several examples are given to elucidate our control policy clearly. Note to Practitioners -In automated manufacturing systems (AMSs), resources such as machines and tools with higher reliablity are always expensive. Sometimes, when it is not cost-effective to use resources with higher reliability, manufacturers may choose some resources with possible failures. These resources are thus considered as unreliable ones in our article. Normally, unreliable resources may fail unexpectedly. Their occurrences can lead a system to stagnation, causing unnecessary downtime, and bringing economic loss to enterprises. To resolve such stagnation issues, we develop a robust supervisory control policy to synthesize a robust liveness-enforcing supervisor for AMSs with assembly operations and unreliable resources. The supervisor can guarantee that a controlled system continues to progress without deadlock and blocking states even if some unreliable resources fail to work.