Configuration design of reconfigurable single-product robotic assembly line for capacity scalability

Abstract

Rapid product changes and fierce global competition force companies to react quickly to market changes associated with dynamic capacity. This paper investigates how to design and reconfigure configurations of the single-product scalable reconfigurable robotic assembly line (RAL) over multiple demand periods (DPs) with fluctuating demands. A two-phase approach is proposed, in phase 1, the configuration of RAL is designed to minimize the capital cost following the initial demand. In phase 2, the reconfiguration for each DP is performed according to demand fluctuations to minimize the sum of capital costs and reconfiguration costs between consecutive DPs. Mathematical models for the two phases are established. Then a hybrid particle swarm algorithm combined with simulated annealing (PSOSA) is proposed for practical-sized problems, and PSO and SA are chosen for comparison. Two other different approaches are selected for comparison. In approach 1 (robust strategy), each DP of the product lifecycle is calculated separately, and then a fixed configuration that can satisfy the maximal capacity of all DPs is obtained. In approach 2 (changeable strategy), the minimal-cost configuration for each DP is calculated separately first, and then the reconfiguration cost between adjacent DPs is counted. Furthermore, a set of instances is designed and the computational results of three approaches accompanied by PSOSA, PSO and SA versus the devised instances demonstrate the superiority and robustness of the proposed approach and PSOSA.