Modular product platforming with supply chain postponement decisions by leader-follower interactive optimization

Abstract

Modular product platforming empowers product family design by identifying the common product platform and configuration of product variants for mass customization. The prevailing practice of fulfilling product families is to postpone certain customization modules in the downstream supply chain. Product platforming and postponement decisions are inherently coupled in terms of developing a modular product architecture to leverage product variety and the supply chain. This paper is motivated towards integrated decision making underlying modular product platforming (MPP) with supply chain postponement (SCP). The paper formulates integrated MPP and SCP decisions as a Stackelberg game that entails joint optimization for interactive evaluation of product modularity and supply chain fulfillment costs. A bilevel mixed 0–1 programming model is developed to characterize the leader-follower decision making process. Virtual compound modules are introduced to justifying which modules should be postponed. An upper level optimization problem is established for identification of basic modules and compound modules by maximizing customer-perceived utilities and postponement utilities of product families, whereas a lower level optimization problem deals with the selection of most appropriate postponement service providers for a minimal total supply chain cost. A nested genetic algorithm is developed to solve the bilevel joint optimization model. A case study of laser printer product platforming and supply chain postponement is reported to illustrate the feasibility and potential of the proposed decision model.