期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 15, 期 9, 页码 5042-5051出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2894111
关键词
Cloud manufacturing; dynamic data; real-time; service scheduling; simulation
类别
资金
- National Key Research and Development Program of China [2018YFB1004001]
- National Natural Science Foundation of China [61374199, 61873014, 61572057, 61836001]
- National High-Tech Research and Development Plan of China [2015AA042101]
In service-oriented manufacturing modes, service scheduling is important for providing just-in-time delivery of manufacturing services to customers. In this paper, the mathematical model of the dynamic cloud manufacturing scheduling problem is constructed, and a scheduling method based on dynamic data-driven simulation is proposed to improve the scheduling performance. The framework, scheduling rules and simulation strategies are discussed in detail. Specifically, three single scheduling rules and three combined scheduling rules are designed based on service time, logistics time, and subtask queue status of candidate services. The real-time information of tasks and services is involved in the simulation strategy to select better scheduling rules. The simulation models of proposed scheduling strategies are constructed and simulated in the Simio software, which is connected to a real-time information database. The proposed method is tested through a case study of numerical control machining in cloud manufacturing, and the results show that the proposed method is promising.
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