Hierarchical Stochastic Production Planning with Delay Interaction

Abstract

This paper explores the problem of hierarchical stochastic production planning (HSPP) for flexible automated workshops (FAWs), each consisting of a number of flexible manufacturing systems (FMSs). The objective is to devise a production plan which tells each FMS how many parts to produce and when to produce them so as to simultaneously minimize the amount of work in progress, maximize the machine utilization, and satisfy demands for finished products over a finite horizon of N time periods. Here, the problem formulation includes not only uncertainty in demand, capacities, and material supply (which is standard in the literature), but also uncertainties in processing times, rework, and waste products. It considers also multiple products and multiple time periods. This is in contrast to most work which looks at either a single periods or at an infinite horizon. The delay interaction aspect arises from taking into account the transportation of parts between FMSs. Apparently, any job which requires processing on more than one FMS cannot be transported directly from one FMS to the next. Instead, a semifinished product completed in one period must be put into shop storage until some future time period at which it can be transported to the next FMS for further processing. Herein, a stochastic interaction/prediction algorithm is developed by using standard calculus of variations techniques. By means of the software package developed, many HSPP examples have been studied, showing that the algorithm is very effective.