The phenomenon of deadlock in robotic cells has been long ignored by most scheduling literature. A deadlock situation arises if a part cannot change its current state indefinitely since the destination machine is occupied by another part. The probability of the deadlock occurrence is likely to be large when the processing route cannot be predicted with certainty due to inspection processes. Our focus here is on a specific robotic cell with a post-process inspection system where the inspection is performed on an independent inspection machine. Avoidance and recovery policies are applied to overcome deadlocks originated from this cell. We develop these policies to prevent deadlock or alternatively resolve it during the online implementation of cycles. The former policy minimizes the storage cost, whereas the later policy minimizes the expected cycle time. An analysis of the scheduling problem that involves timings and costs is also carried out for comparing policies.
This study is focused on the domain of a two-machine robotic cell scheduling problem. Particularly, we propose the first analytical method for minimizing the partial cycle time of such a cell with a PC-based automatic inspection system to make the problem more realistic. It is assumed that parts must be inspected in one of the production machines, and this may result in a rework process. The stochastic nature of the rework process prevents us from applying existing deterministic solution methods for the scheduling problem. This study aims to develop an in-line inspection of identical parts using multiple contact/non-contact sensors. Initially, we present a heuristic method that converts a multiple-sensor inspection system into a single-sensor inspection system. Then, the expected sequence times of two different cycles are derived based on a geometric distribution, and finally the maximum expected throughput is pursued for each individual case.