Server Failure Detection for Robustness Analysis in Automated Manufacturing Systems With Arbitrary Resource Failures

In the paradigm of Petri nets (PNs), this paper focuses on the maximally permissive robustness analysis for automated manufacturing systems (AMSs) with arbitrary resource failures through server failure detection. First, unreliable system of sequential systems with shared resources (U-S4Rs) are constructed by adding detection subnets to the original PNs for each unreliable place. Based on different failed statuses of unreliable resources, the reachable marking set of a U-S4R is partitioned into one safe and multiple failed subsets, where there exists a one-to-one relationship between all markings in the safe subset and those of the original system. Second, subnet systems corresponding to part types are categorized to provide the definitions of the robust, strongly robust, and weakly robust markings. Third, we provide algorithms to compute the sets of strongly connected, weakly connected, and dangerous markings in each failed zone. When resources are in a failed statusXf, we establish anXf-failure-dependent marking set. The robustness of all markings within that set can be evaluated by examining the connectedness of the markings derived from those in that set. Moreover, for all markings not in theXf-failure-dependent marking set but in the safe subset, we provide conditions further to determine the robustness of these markings. Finally, examples are presented to illustrate the proposed methods and show the advantage over the existing ones.