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Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed

Author

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  • Hu, Luoke
  • Liu, Ying
  • Lohse, Niels
  • Tang, Renzhong
  • Lv, Jingxiang
  • Peng, Chen
  • Evans, Steve

Abstract

A considerable amount of energy consumed by machine tools is attributable to non-cutting operations, including tool path, tool change, and change of spindle rotation speed. The non-cutting energy consumption of the machine tool (NCE) is affected by the processing sequence of the features of a specific part (PFS) because the plans of non-cutting operations will vary based on the different PFS. This article aims to understand the NCE between processing a specific feature and its pre- or post-feature, especially the energy consumed during the speed change of the spindle rotation. Based on the developed model, a single objective optimisation problem is introduced that minimises the NCE. Then, Ant Colony Optimisation (ACO) is employed to search for the optimal PFS. A case study is developed to validate the effectiveness of the proposed approach. Two parts with 12 and 15 features are processed on a machining centre. The simulation experiment results show that the optimal or near-optimal PFS can be found. Consequently, 8.70% and 30.42% reductions in NCE are achieved for part A and part B, respectively. Further, the performance of ACO for our specific optimisation problem is discussed and validated based on comparisons with other algorithms.

Suggested Citation

  • Hu, Luoke & Liu, Ying & Lohse, Niels & Tang, Renzhong & Lv, Jingxiang & Peng, Chen & Evans, Steve, 2017. "Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed," Energy, Elsevier, vol. 139(C), pages 935-946.
    • Handle: RePEc:eee:energy:v:139:y:2017:i:c:p:935-946
    DOI: 10.1016/j.energy.2017.08.032
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    References listed on IDEAS

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    1. Cai, Wei & Liu, Fei & Zhou, XiaoNa & Xie, Jun, 2016. "Fine energy consumption allowance of workpieces in the mechanical manufacturing industry," Energy, Elsevier, vol. 114(C), pages 623-633.
    2. Bhattacharya, Subir & Roy, Rahul & Bhattacharya, Sumita, 1998. "An exact depth-first algorithm for the pallet loading problem," European Journal of Operational Research, Elsevier, vol. 110(3), pages 610-625, November.
    3. Hu, Luoke & Peng, Chen & Evans, Steve & Peng, Tao & Liu, Ying & Tang, Renzhong & Tiwari, Ashutosh, 2017. "Minimising the machining energy consumption of a machine tool by sequencing the features of a part," Energy, Elsevier, vol. 121(C), pages 292-305.
    4. Cai, Wei & Liu, Fei & Zhang, Hua & Liu, Peiji & Tuo, Junbo, 2017. "Development of dynamic energy benchmark for mass production in machining systems for energy management and energy-efficiency improvement," Applied Energy, Elsevier, vol. 202(C), pages 715-725.
    5. Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    6. Ali, E.S. & Abd Elazim, S.M. & Abdelaziz, A.Y., 2016. "Ant Lion Optimization Algorithm for Renewable Distributed Generations," Energy, Elsevier, vol. 116(P1), pages 445-458.
    7. Ting-Chia Ou & Wei-Fu Su & Xian-Zong Liu & Shyh-Jier Huang & Te-Yu Tai, 2016. "A Modified Bird-Mating Optimization with Hill-Climbing for Connection Decisions of Transformers," Energies, MDPI, vol. 9(9), pages 1-12, August.
    8. Ou, Ting-Chia & Hong, Chih-Ming, 2014. "Dynamic operation and control of microgrid hybrid power systems," Energy, Elsevier, vol. 66(C), pages 314-323.
    9. Schudeleit, Timo & Züst, Simon & Wegener, Konrad, 2015. "Methods for evaluation of energy efficiency of machine tools," Energy, Elsevier, vol. 93(P2), pages 1964-1970.
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    Cited by:

    1. Cai, Wei & Liu, Fei & Dinolov, Ognyan & Xie, Jun & Liu, Peiji & Tuo, Junbo, 2018. "Energy benchmarking rules in machining systems," Energy, Elsevier, vol. 142(C), pages 258-263.
    2. Zhang, Yuanhui & Cai, Wei & He, Yan & Peng, Tao & Jia, Shun & Lai, Kee-hung & Li, Li, 2022. "Forward-and-reverse multidirectional turning: A novel material removal approach for improving energy efficiency, processing efficiency and quality," Energy, Elsevier, vol. 260(C).
    3. Cai, Wei & Wang, Lianguo & Li, Li & Xie, Jun & Jia, Shun & Zhang, Xugang & Jiang, Zhigang & Lai, Kee-hung, 2022. "A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Cai, Wei & Li, Yanqi & Li, Li & Lai, Kee-hung & Jia, Shun & Xie, Jun & Zhang, Yuanhui & Hu, Luoke, 2022. "Energy saving and high efficiency production oriented forward-and-reverse multidirectional turning: Energy modeling and application," Energy, Elsevier, vol. 252(C).

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