UC Berkeley

In most Cloud Manufacturing (CMfg) systems, Design Resource (DR) is encapsulated into cloud service under a fine-grained condition. However, due to the small granularity of DRs provided by cloud provider, it is difficult for the cloud services to match with design tasks if there is no initiative resource. For example, because of the lack of initiative perception capabilities, it is difficult for design software to match with design tasks directly. A method of DR multi-granularity modeling with two-stage aggregation is proposed, by which the resource granularity is increased and dynamic design capability is formed. In the proposed DR multi-granularity model, DRs are classified into three granularities: Static Physical Resource (SPR), Dynamic Capacity Resource (DCR), and Cross-functional Design Unit (CDU). Their ontology models are set up to represent the basic function, structure and component of DRs. In the two-stage aggregation of DRs, two strategies are proposed to increase the granularity of DRs. The first is DCR aggregation strategy based on auxiliary resources actively pushing, and the second is CDU aggregation strategy based on meta task and meta capability matching. Using the operation parameters of DRs and the associated evaluation matrix, a method of DCR and CDU evaluation is proposed to optimize the searched DRs. With the help of the preceding multi-granularity DR modeling and the two-stage access strategy, DR granularity is enlarged and initiative design capability is formed, which solves the problem of DRs matching with design tasks because of small resource granularity.