IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v147y2018icp390-402.html
   My bibliography  Save this article

Minimising the energy consumption of tool change and tool path of machining by sequencing the features

Author

Listed:
  • Hu, Luoke
  • Liu, Ying
  • Peng, Chen
  • Tang, Wangchujun
  • Tang, Renzhong
  • Tiwari, Ashutosh

Abstract

A considerable amount of energy is consumed by machine tools during the run-time operations such as tool change and tool path. The value of this part of energy is affected by the processing sequence of features of a part (PSFP) because the tool path and tool change plan will vary based on the different PSFP. This paper firstly aims to understand the relationship between the PSFP and the energy consumption of tool change and tool path during the feature transitions. Then, a model is introduced for the single objective optimisation problem that minimises the energy consumption of machine tools during the feature transitions which include all the tool path and tool change operations. Finally, optimisation approaches including depth-first search and genetic algorithm are modified and applied to find the optimal PSFP which results in the minimisation of the energy consumption of feature transitions (EFT). In the case study, the optimal and near-optimal sequences of features, in terms of the minimum EFT, of a part which has 15 actual features and is processed by a machining centre have been found. The optimal PSFP achieves a 28.60% EFT reduction, which validates the effectiveness of the developed model and optimisation approaches. Besides, a 27.95% time reduction of feature transitions benefits from the EFT minimisation.

Suggested Citation

  • Hu, Luoke & Liu, Ying & Peng, Chen & Tang, Wangchujun & Tang, Renzhong & Tiwari, Ashutosh, 2018. "Minimising the energy consumption of tool change and tool path of machining by sequencing the features," Energy, Elsevier, vol. 147(C), pages 390-402.
    • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:390-402
    DOI: 10.1016/j.energy.2018.01.046
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218300574
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.01.046?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Schudeleit, Timo & Züst, Simon & Weiss, Lukas & Wegener, Konrad, 2016. "The Total Energy Efficiency Index for machine tools," Energy, Elsevier, vol. 102(C), pages 682-693.
    3. Zhao, G.Y. & Liu, Z.Y. & He, Y. & Cao, H.J. & Guo, Y.B., 2017. "Energy consumption in machining: Classification, prediction, and reduction strategy," Energy, Elsevier, vol. 133(C), pages 142-157.
    4. 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.
    5. 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.
    6. Sneha Singh & Sankha Deb, 2014. "An intelligent methodology for optimising machining operation sequence by ant system algorithm," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 16(4), pages 451-471.
    7. Luoke Hu & Renzhong Tang & Keyan He & Shun Jia, 2015. "Estimating machining-related energy consumption of parts at the design phase based on feature technology," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7016-7033, December.
    8. 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.
    9. 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.
    10. Wang, Yong & Li, Lin, 2013. "Time-of-use based electricity demand response for sustainable manufacturing systems," Energy, Elsevier, vol. 63(C), pages 233-244.
    11. Ruiz, Rubén & Maroto, Concepciøn & Alcaraz, Javier, 2006. "Two new robust genetic algorithms for the flowshop scheduling problem," Omega, Elsevier, vol. 34(5), pages 461-476, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vijay Rathod, 2023. "Multi-drill path sequencing models: A comparative study," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 554-570, March.
    2. 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).
    3. Xiao, Qinge & Li, Congbo & Tang, Ying & Pan, Jian & Yu, Jun & Chen, Xingzheng, 2019. "Multi-component energy modeling and optimization for sustainable dry gear hobbing," Energy, Elsevier, vol. 187(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Liu, Conghu & Cai, Wei & Dinolov, Ognyan & Zhang, Cuixia & Rao, Weizhen & Jia, Shun & Li, Li & Chan, Felix T.S., 2018. "Emergy based sustainability evaluation of remanufacturing machining systems," Energy, Elsevier, vol. 150(C), pages 670-680.
    5. 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.
    6. Shang, Zhendong & Gao, Dong & Jiang, Zhipeng & Lu, Yong, 2019. "Towards less energy intensive heavy-duty machine tools: Power consumption characteristics and energy-saving strategies," Energy, Elsevier, vol. 178(C), pages 263-276.
    7. 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).
    8. 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.
    9. Jia, Shun & Yuan, Qinghe & Lv, Jingxiang & Liu, Ying & Ren, Dawei & Zhang, Zhongwei, 2017. "Therblig-embedded value stream mapping method for lean energy machining," Energy, Elsevier, vol. 138(C), pages 1081-1098.
    10. 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.
    11. 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).
    12. Cai, Wei & Lai, Kee-hung, 2021. "Sustainability assessment of mechanical manufacturing systems in the industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    13. Cai, Wei & Liu, Conghu & Zhang, Cuixia & Ma, Minda & Rao, Weizhen & Li, Wenyi & He, Kang & Gao, Mengdi, 2018. "Developing the ecological compensation criterion of industrial solid waste based on emergy for sustainable development," Energy, Elsevier, vol. 157(C), pages 940-948.
    14. Tuo, Junbo & Liu, Fei & Liu, Peiji & Zhang, Hua & Cai, Wei, 2018. "Energy efficiency evaluation for machining systems through virtual part," Energy, Elsevier, vol. 159(C), pages 172-183.
    15. Xiao, Qinge & Li, Congbo & Tang, Ying & Pan, Jian & Yu, Jun & Chen, Xingzheng, 2019. "Multi-component energy modeling and optimization for sustainable dry gear hobbing," Energy, Elsevier, vol. 187(C).
    16. 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.
    17. Liu, Wei & Li, Li & Cai, Wei & Li, Congbo & Li, Lingling & Chen, Xingzheng & Sutherland, John W., 2020. "Dynamic characteristics and energy consumption modelling of machine tools based on bond graph theory," Energy, Elsevier, vol. 212(C).
    18. 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).
    19. Guo, Yansong & Duflou, Joost R. & Deng, Yelin & Lauwers, Bert, 2018. "A life cycle energy analysis integrated process planning approach to foster the sustainability of discrete part manufacturing," Energy, Elsevier, vol. 153(C), pages 604-617.
    20. Wen, Xuanhao & Cao, Huajun & Li, Hongcheng & Zheng, Jie & Ge, Weiwei & Chen, Erheng & Gao, Xi & Hon, Bernard, 2022. "A dual energy benchmarking methodology for energy-efficient production planning and operation of discrete manufacturing systems using data mining techniques," Energy, Elsevier, vol. 255(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:147:y:2018:i:c:p:390-402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.