Design of resilient, platform-based manufacturing networks for highly-customized production
针对高度定制化生产中供应商技术能力不确定的问题，建立两阶段随机规划模型，优化供应商、生产商和物流承运商的选择及产运量，并通过应急订单和公开市场采购应对供应商失败风险，以最大化期望利润。
Inspired by the growing interest in enhancing the lead time and cost of mass personalisation in the advanced technology sector, this study investigates the design of a platform-based manufacturing network (PBMN) in the context of highly customised production. The uncertain technological capabilities of suppliers in manufacturing customised components with intricate design specifications have been explicitly addressed by establishing a stochastic decision framework. The proposed two-stage stochastic programming model determines the optimal choice of suppliers, producers, and logistics carriers, in addition to the quantities of production and transportation in a PBMN. Two types of corrective actions, namely emergency orders to backup entities and purchasing from the open market, have been foreseen to mitigate the risk of suppliers’ failure in delivering customised items. The objective is to maximise the expected profit under uncertain scenarios. In addition, a scenario sampling heuristic is developed to overcome the computational complexity of the proposed model. Our numerical experiments underline the effectiveness of the proposed decision framework in identifying more reliable entities as the primary partners in the network. Moreover, the results emphasise the critical role of accurate supplier failure prediction and a broader selection of suppliers in enhancing network profitability and resilience.