期刊
JOURNAL OF CLEANER PRODUCTION
卷 246, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119071
关键词
Energy efficiency; Production mode; Hybrid flow shop scheduling; Forging operation; Multiple time factors
资金
- National Science and Technology Major Project of China [2019ZX04024001]
- National Natural Science Foundation of China [51975019]
- Fundamental Research Funds of Beijing Municipal Universities
- Beijing University of Technology
Energy-saving scheduling in forging production has attracted increasing attention because of the advances in sustainable manufacturing technologies. The unit energy consumption of forging production equipment is significantly higher than that of other general manufacturing equipment. Employing efficient and energy-saving scheduling methods can significantly reduce the energy consumption in forging production. However, the relationship between heating furnace and other equipment in forging production is complicated, resulting in few studies on energy-saving scheduling problem for forging production line. Thus, the energy-efficient hybrid flow shop scheduling problem with forging operations (EHFSP-FO) was investigated in this research. First, the production mode considering multiple time factors and mixed production was established. The mixed production mode consisted of continuous processing with variable parameters and intermittent processing. Then, a novel mathematical model considering makespan and energy consumption was constructed based on the mixed production mode for the proposed problem, and a new rule to identify the optimum transportation sequence and time was formulated. Furthermore, the population and major operators were designed and applied to an evolutionary algorithm by weighted sum approach. The scheduling results were achieved based on the real-world process data for different types of ring forgings to verify the feasibility of the established mathematical model. The experimental results demonstrated that the proposed mathematical model can be used to identify the optimal schedule considering makespan and energy consumption simultaneously. (C) 2019 Elsevier Ltd. All rights reserved.
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