Investigation on matching of individualised requirements and shared manufacturing resources in the context of shared factory runtime
针对共享制造中个性化订单与闲置资源的匹配难题，提出工厂级运行时框架和自组织冗余匹配算法，通过工业案例验证其有效性，为工业5.0背景下的人本制造提供可行方案。
Shared Manufacturing (SharedM) empowers individuals to engage in manufacturing via order-driven, resource-sharing processes, embodying the principles of Industry 5.0 and a human-centric approach. This study tackles the challenges of requirement-resource matching to realise Production Planning and Scheduling (PP&S), stemming from conflicts in the distribution and ownership of shared Manufacturing Resources (MRs). We introduce a factory-level runtime framework alongside a self-organising redundant matching algorithm based on sample average approximation to efficiently manage shared MRs and individualised orders. Then, an industrial case study illustrates the application from the modelling of MRs and individualised requirements, to the generation of the final matching Gantt chart. The findings demonstrate that the proposed shared factory can align idle MRs with personalised consumer demands effectively. This paper presents a viable solution for implementing shared factories in industrial settings, providing valuable insights into social manufacturing, SharedM, and novel manufacturing paradigms focused on human-centric values.