Graph-theoretic deadlock detection and resolution for flexible manufacturing systems

Flexible manufacturing systems are capable of producing a broad variety of products and changing their characteristics quickly and frequently. This flexibility provides for more efficient use of resources, but makes control of these systems more difficult. Control problems previously unstudied now require practical resolution, like system deadlock. A system deadlock is a situation that arises due to resource sharing in manufacturing systems, when the flow of parts is permanently inhibited and/or operations on parts cannot be performed. This problem has been ignored by most scheduling and control studies, which usually assume infinite machine queue capacity and unlimited tooling resources. FMS´s, however, have little or no queue capacity and limited tooling resources. In this paper, graph-theoretic deadlock detection and resolution procedures are presented which are suitable for real-time control of manufacturing systems. These procedures determine whether part movement in the system causes system deadlock or not. To this end, a system status graph representing part routings is virtually updated for every part movement before parts move physically to the next destination. Two types of system deadlocks, part flow deadlock and impending part flow deadlock, are detected using the updated system status graph. If a deadlock detection and recovery method is used to recover from a deadlock using a storage buffer, only part flow deadlocks need to be detected. On the other hand, if no buffer is available, both types of existing as well as impending system deadlocks need to be detected to avoid a deadlock situation