Work-in-progress storage and handling capacity trade-offs in material flow design

Abstract

An important class of manufacturing facility design problems involves job shop systems where material flow is supported by discrete handling systems. Discrete handling describes systems that use a fixed number of vehicles (e.g. industrial trucks, AGVs, etc.) for transferring unit loads between workcenters. In designing job shop facilities using discrete materials handling systems, the designer must cost-effectively trade-off handling opacity and the storage capacity used for buffering work in process unit loads. It is also necessary to effectively allocate the total buffer storage capacity among the individual workcenters of a facility. Treatment of the latter problem with respect to workcenter reliability issues has been well documented in the literature, particularly for flow shop systems with serial dependencies among workcenters. However, the problem is typically solved without regard to the interaction between storage requirements and the service level provided by a materials handling system. Buffer storage requirements in a job shop system can be sensitive to the relationship between handling demand and capacity, since slack capacity can be applied to minimize buffer queue fluctuations. The precise nature of this trade-off can be characterized in several ways, including the use of simulation (Ozden, 1988), Petri nets (Zeng, Wang and Jin, 1991) or analytical models (Malmborg, 1990; Maxwell and Muckstadt, 1982).