Strategic configuration of flexible electronics assembly facilities facing stochastic requirements

Flexible configuration of manufacturing facilities is a key strategy for efficiently improving market responsiveness and market share in the face of uncertain future product demand. Flexible facility configurations can produce an efficient production system that allows higher capacity utilization given uncertainty in product demand and mix. The aim of this paper is to consider the alternative choices of flexible equipment available at the strategic planning level and to make decisions about the facility design and configuration that best suit the specific needs of the manufacturing system under consideration. A chance constrained mixed integer programming model for strategic configuration and capacity planning of flexible multiple-stage production facilities under time-varying production requirements is introduced in this paper. It is an integrated model that determines the number of assembly lines required, the flexible automation levels required in each line, capacity levels, and product assignment/reassignments for a multiple-stage production system, considering the stochastic nature of the demand. A two-step heuristic based on genetic algorithms is proposed and tested. Experimental results indicate that the two-step heuristic performs well in terms of both computation speed and solution accuracy.