Towards integrated optimal configuration of platform products, manufacturing processes, and supply chains

This paper seeks to address the challenge of designing effective supply chain systems that integrate platform product decisions, manufacturing process decisions, and supply sourcing decisions. Specifically, this paper considers the specific scenario of optimizing the configuration of the supply chain system given commonality among platform products. The paper uses and extends the concept of Generic Bills of Materials (GBOM) of a product family as a unified framework for qualitatively capturing and representing the structure of its supply chain. This qualitative model is then enhanced by a mathematical model developed to quantify the relationships among various design decisions. Endeavoring to solve the mathematical model more efficiently, we propose an effective heuristic method using Genetic Algorithm (GA). Although GA generally does not guarantee the optimal solution, the best heuristic solutions obtained in this study are consistent with the optimal solutions obtained using Dynamic Programming. The resulting mathematical model and solution algorithm are then used to investigate the mutual impact between the design decisions of platform products and of processes in the supply chain through sensitivity analyses. Several useful managerial insights are generated and discussed.