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Integrated optimization of cutting tool and cutting parameters in face milling for minimizing energy footprint and production time

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  • Chen, Xingzheng
  • Li, Congbo
  • Tang, Ying
  • Li, Li
  • Du, Yanbin
  • Li, Lingling

Abstract

Cutting tool and cutting parameters are important components in the process planning. Proper selection of cutting tool and cutting parameters can significantly reduce the energy consumption and production time of the machining process. In this paper, an integrated approach of cutting tool and cutting parameter optimization is proposed to minimize the energy footprint and production time of the face milling process. Firstly, the energy footprint characteristics are analyzed by considering multiple cutting tool flexibilities and cutting parameters. Then a multi-objective integrated optimization model for minimizing energy footprint and production time is proposed and solved via a multi-objective Cuckoo Search algorithm. Finally, case studies are conducted to verify the feasibility and validity of the proposed integrated optimization approach. From the results of the case studies, interaction effects between cutting tool and cutting parameters are revealed. Integrated optimization of cutting tool and cutting parameters can achieve more energy footprint savings than either cutting parameter optimization or cutting tool optimization. Moreover, it also can be found that the optimization results for minimum production time does not necessarily satisfy the optimization criterion of minimum energy footprint. The proposed multi-objective integrated optimization approach can strike a balance between minimum energy footprint and minimum production time.

Suggested Citation

  • Chen, Xingzheng & Li, Congbo & Tang, Ying & Li, Li & Du, Yanbin & Li, Lingling, 2019. "Integrated optimization of cutting tool and cutting parameters in face milling for minimizing energy footprint and production time," Energy, Elsevier, vol. 175(C), pages 1021-1037.
    • Handle: RePEc:eee:energy:v:175:y:2019:i:c:p:1021-1037
    DOI: 10.1016/j.energy.2019.02.157
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    References listed on IDEAS

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    1. Cai, Wei & Liu, Fei & Xie, Jun & Liu, Peiji & Tuo, Junbo, 2017. "A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking," Energy, Elsevier, vol. 138(C), pages 332-347.
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    Cited by:

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    3. Zhang, Tao & Liu, Zhanqiang & Sun, Xiaodong & Xu, Jixiang & Dong, Longlong & Zhu, Genglei, 2020. "Investigation on specific milling energy and energy efficiency in high-speed milling based on energy flow theory," Energy, Elsevier, vol. 192(C).
    4. Xiangxin An & Guojin Si & Tangbin Xia & Qinming Liu & Yaping Li & Rui Miao, 2022. "Operation and Maintenance Optimization for Manufacturing Systems with Energy Management," Energies, MDPI, vol. 15(19), pages 1-19, October.
    5. Zhang, Jiaqi & Han, Xin & Li, Li & Jia, Shun & Jiang, Zhigang & Duan, Xiangmin & Lai, Kee-hung & Cai, Wei, 2023. "Multi-objective optimisation for energy saving and high efficiency production oriented multidirectional turning based on improved fireworks algorithm considering energy, efficiency and quality," Energy, Elsevier, vol. 284(C).
    6. Tangbin Xia & Xiangxin An & Huaqiang Yang & Yimin Jiang & Yuhui Xu & Meimei Zheng & Ershun Pan, 2023. "Efficient Energy Use in Manufacturing Systems—Modeling, Assessment, and Management Strategy," Energies, MDPI, vol. 16(3), pages 1-20, January.
    7. Zhao, Junhua & Li, Li & Li, Lingling & Zhang, Yunfeng & Lin, Jiang & Cai, Wei & Sutherland, John W., 2023. "A multi-dimension coupling model for energy-efficiency of a machining process," Energy, Elsevier, vol. 274(C).
    8. Muhammad Asif & Hang Shen & Chunlin Zhou & Yuandong Guo & Yibo Yuan & Pu Shao & Lan Xie & Muhammad Shoaib Bhutta, 2023. "Recent Trends, Developments, and Emerging Technologies towards Sustainable Intelligent Machining: A Critical Review, Perspectives and Future Directions," Sustainability, MDPI, vol. 15(10), pages 1-28, May.
    9. Hadhami Ben Slama & Raoudha Gaha & Mehdi Tlija & Sami Chatti & Abdelmajid Benamara, 2023. "Proposal of a Combined AHP-PROMETHEE Decision Support Tool for Selecting Sustainable Machining Process Based on Toolpath Strategy and Manufacturing Parameters," Sustainability, MDPI, vol. 15(24), pages 1-20, December.

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