Autonomous resource allocation of smart workshop for cloud machining orders. Issue 2 (7th May 2021)

• Record Type: Journal Article
• Authors: Hui, Jizhuang; Lei, Jingyuan; Ding, Kai; Zhang, Fuqiang; Lv, Jingxiang
• Is Part Of: AI EDAM. Volume 35:Issue 2(2021)
• Page Start: 226
• Page End: 239
• Publication Date: 2021-05-07
• Subjects: Cloud machining orders, -- fuzzy analysis, -- improved firefly algorithm, -- particle swarm optimization, -- resource allocation; Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S089006042000044X
• Languages: English
• ISSNs: 0890-0604

Abstract

Abstract: In order to realize the online allocation of collaborative processing resource of smart workshop in the context of cloud manufacturing, a multi-objective optimization model of workshop collaborative resources (MOM-WCR) was proposed. Considering the optimization objectives of processing time, processing cost, product qualification rate, and resource utilization, MOM-WCR was constructed. Based on the time sequence of workshop processing tasks, the workshop collaborative manufacturing resource was integrated in MOM-WCR. Fuzzy analytic hierarchy process (FAHP) was adopted to simplified the multi-objective problem into the single-objective problem. Then, the improved firefly algorithm which integrated the particle swarm algorithm (IFA-PSA) was used to solve MOM-WCR. Finally, a group of connecting rod processing experiments were used to verify the model proposed in this paper. The results show that the model is feasible in the application of workshop-level resource allocation in the context of cloud manufacturing, and the improved firefly algorithm shows good performance in solving the multi-objective resource allocation problem.