Abstract
The times that parts spend in work areas are random owing to random processing times, random failure and repair events in manufacturing systems. This randomness gives rise to blocking and starvation of the work areas, because storage areas can hold only a finite amount of parts. These phenomena not only decrease the productivity, but also make the performance evaluation complicated. This paper surveys the approaches to model and analyze the manufacturing systems using queueing theory. In particular, we are concerned with features that are prevalent in modeling the basic manufacturing systems. Exact and approximate methods for obtaining performance measures, such as throughput, average lead time, average inventory level, and utilization of the machines, are also reviewed. Extensions of the approaches for more complex systems are briefly discussed.
