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Over the past several years, researchers have developed numerous control policies that assure deadlock-free operation for flexible manufacturing systems. Using this research base as a foundation, we have developed several supervisory policies that assure robust operation in the face of resource failure. Along with deadlock-free operation, these policies guarantee that failure of unreliable resources does not block production of part types not requiring failed resources. In our previous work, we developed two types of robust policies, those that 'absorb' all parts requiring failed resources into the buffer space of failure-dependent resources (resources that support only parts requiring failed resources), and those that 'distribute' parts requiring failed resources among the buffer space of shared resources (resources shared by parts requiring and parts not requiring failed resources). These two types of robust controllers assure different levels of robust system operation and impose very different operating dynamics on the system, thus affecting system performance in different ways. In this research, we use extensive simulation and experimentation on a highly complex and configurable system to develop guidelines for choosing the best robust supervisor based on manufacturing system characteristics and performance objectives. We validate these guidelines using seven randomly generated complex systems and find a better than 88% agreement. [ABSTRACT FROM AUTHOR]

Deadlock-free resource allocation has been an active area of research in flexible manufacturing. Most researchers have assumed that allocated resources do not fail, and thus, little research has addressed the discrete-event supervision of manufacturing systems that are subject to resource failure. In our previous work, we developed supervisory controllers to ensure robust deadlock-free operation for systems with unreliable resources. These controllers guarantee that parts requiring failed resources do not block the production of parts that are not requiring failed resources. This previous work assumes that parts requiring failed resources can be advanced into failure-dependent (FD) buffer space (buffer space exclusively dedicated to parts requiring unreliable resources). Supervisors admit only states for which a sequence of such part advancements is feasible. The research presented in this paper relaxes this assumption because, in some systems, providing FD buffer space might be too expensive or it might be desirable to load the system more heavily with FD parts. In this paper, we concentrate on distributing parts requiring failed resources throughout the buffer space of shared resources so that these distributed parts do not block the production of part types that are not requiring failed resources. The approach presented here requires no state enumeration and is polynomial in stable measures of system size. We also present results from simulation experiments that compare system performance under these new policies with system performance under our previously published supervisors. These results show that our new policies allow better performance if the required part mixes favor FD part types. The systems of interest are single-unit resource allocation systems. [ABSTRACT FROM AUTHOR]

In the first of this pair of papers, the Neighborhood Policy was shown to be a correct and scalable Structural Control Policy (SCP). Operating constraints that guarantee deadlock-free flexible manufacturing system (FMS) operation are generated based on machine capacity. For some systems these constraints appear to be quite conservative. This paper generalizes the Neighborhood Policy so that many different SCPs can be generated for the same FMS configuration. A method of finding permissive neighborhood systems is then developed. Finally, SCP efficiency is defined and investigated for Capacity-Based and Optimal Neighborhood Policies. [ABSTRACT FROM AUTHOR]

Structural Control Policies (SCPs) are real-time flexible manufacturing systems(FMS) operating policies that guarantee deadlockfree operation. SCPs must be correct and scalable. A correct SCP guarantees deadlock-free operation whereas a scalable (polynomial) SCP remains computationally tractable as FMS size increases. The NP-completeness of state safety (is there a sequence of state transitions leading to the empty state?) implies that a correct and scalable SCP will reject some safe states. SCP efficiency is the ratio of policy admissible space to FMS safe state space. This paper, the first of a two-part series, discusses FMS structural control and presents a correct and scalable SCP referred to as the Neighborhood Policy. SCP efficiency issues will be discussed in the second part. [ABSTRACT FROM AUTHOR]