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A Hybrid Energy-Saving Scheduling Method Integrating Machine Tool Intermittent State Control for Workshops

Author

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  • Hong Cheng

    (Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Haixiao Liu

    (Ordnance NCO Academy, Army Engineering University of PLA, Wuhan 430075, China)

  • Shuo Zhu

    (Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China
    The School of Mechanical Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Zhigang Jiang

    (Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

  • Hua Zhang

    (Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)

Abstract

Production scheduling and machine tool intermittent state control separately influence a workshop’s machining and intermittent energy consumption. Effective scheduling decisions and intermittent state control are crucial for optimizing the overall energy consumption in the workshop. However, the scheduling scheme determines the machine tool intermittent durations, which imposes strong constraints on the decision-making process for intermittent state control. This makes it difficult for intermittent state control to be used in providing feedback and optimizing scheduling decisions, significantly limiting the overall energy-saving potential of the workshop. To this end, a workshop energy-saving scheduling method is proposed integrating machine tool intermittent state control. Firstly, the variation characteristics of workshop machining energy consumption, machine tool intermittent durations, and intermittent energy consumption are analyzed, and an energy-saving optimization strategy is designed. Secondly, by incorporating variables such as intermittent durations, intermittent energy consumption, and variable operation start time, a multi-objective integrated optimization model is established. Thirdly, the energy-saving optimization strategy is integrated into chromosome encoding, and multiple crossover and mutation genetic operator strategies, along with a low-level selection strategy, are introduced to improve the NSGA-II algorithm. Finally, the effectiveness of the proposed method is verified through a machining case. Results show that the generated Gantt chart reflects both production scheduling and intermittent state control decision outcomes, resulting in a 1.51% reduction in makespan, and 3.90% reduction in total energy consumption.

Suggested Citation

  • Hong Cheng & Haixiao Liu & Shuo Zhu & Zhigang Jiang & Hua Zhang, 2025. "A Hybrid Energy-Saving Scheduling Method Integrating Machine Tool Intermittent State Control for Workshops," Sustainability, MDPI, vol. 17(13), pages 1-27, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6207-:d:1696068
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    References listed on IDEAS

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    1. João M. R. C. Fernandes & Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2022. "Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review," Sustainability, MDPI, vol. 14(10), pages 1-34, May.
    2. Barış Tan & Oktay Karabağ & Siamak Khayyati, 2024. "Energy-efficient production control of a make-to-stock system with buffer- and time-based policies," International Journal of Production Research, Taylor & Francis Journals, vol. 62(16), pages 5809-5827, August.
    3. Chengshuai Li & Biao Zhang & Yuyan Han & Yuting Wang & Junqing Li & Kaizhou Gao, 2022. "Energy-Efficient Hybrid Flowshop Scheduling with Consistent Sublots Using an Improved Cooperative Coevolutionary Algorithm," Mathematics, MDPI, vol. 11(1), pages 1-27, December.
    4. Shailendra Pawanr & Kapil Gupta, 2024. "A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability," Energies, MDPI, vol. 17(15), pages 1-21, July.
    5. Andy Ham & Myoung-Ju Park & Kyung Min Kim, 2021. "Energy-Aware Flexible Job Shop Scheduling Using Mixed Integer Programming and Constraint Programming," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, June.
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