An Operation-Level Dynamic Capacity Scalability Model for Reconfigurable Manufacturing Systems

Abstract

This study considers the problem of determining the facility requirements of a reconfigurable manufacturing system (RMS) to satisfy the demand requirements and the minimum allowable system utilization over a given planning horizon. Unlike the ordinary capacity planning problems, the one in RMSs is an integrated design and operation problem, since the RMS has the capability of changing in its hardware and software components rapidly in response to market changes or intrinsic system changes. To represent the problem mathematically, a nonlinear integer programming model is suggested for the objective of minimizing the sum of facility acquisition and configuration change costs, while the throughputs and utilizations are estimated using a closed queuing network model. Then, due to the problem complexity, we suggest three heuristics, two forward and one backward heuristics. To compare the performances of the three heuristics, computation experiments were done on various instances, and the results show that the backward heuristic outperforms the forward ones, while giving the optimal solutions for small-sized test instances.