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Energy benchmarking rules in machining systems

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  • Cai, Wei
  • Liu, Fei
  • Dinolov, Ognyan
  • Xie, Jun
  • Liu, Peiji
  • Tuo, Junbo

Abstract

The energy benchmarking has been recognised as an effective analytical methodology and a significant management tool that helps to improve the efficiency and performance of the energy utilisation. Studies on energy benchmarking has been worldwide carried out in many areas for different objectives. However, there are few systematic theories to support the development of a reasonable energy benchmarking and to provide efficient application measures in machining systems. To overcome these challenges, based on previous studies we propose two significant rules of energy benchmarking in machining systems contributing to the development of the energy benchmarking and application. This paper describes the concept, content and scope of the energy benchmarking rules laying a solid theoretical foundation for the energy benchmarking research in the machining field and giving the research directions. Meanwhile, through application analysis of the rules, the energy benchmarking rules have wide application prospects in machining systems and play an important role in the energy-efficient production.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:142:y:2018:i:c:p:258-263
    DOI: 10.1016/j.energy.2017.10.030
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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.
    2. Yoon, Hae-Sung & Kim, Eun-Seob & Kim, Min-Soo & Lee, Jang-Yeob & Lee, Gyu-Bong & Ahn, Sung-Hoon, 2015. "Towards greener machine tools – A review on energy saving strategies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 870-891.
    3. Sahoo, Lalit Kumar & Bandyopadhyay, Santanu & Banerjee, Rangan, 2014. "Benchmarking energy consumption for dump trucks in mines," Applied Energy, Elsevier, vol. 113(C), pages 1382-1396.
    4. Mui, K.W. & Wong, L.T. & Law, L.Y., 2007. "An energy benchmarking model for ventilation systems of air-conditioned offices in subtropical climates," Applied Energy, Elsevier, vol. 84(1), pages 89-98, January.
    5. 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.
    6. 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.
    7. Wang, Ning & Wen, Zongguo & Liu, Mingqi & Guo, Jie, 2016. "Constructing an energy efficiency benchmarking system for coal production," Applied Energy, Elsevier, vol. 169(C), pages 301-308.
    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. 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. 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.
    11. Saygin, D. & Worrell, E. & Patel, M.K. & Gielen, D.J., 2011. "Benchmarking the energy use of energy-intensive industries in industrialized and in developing countries," Energy, Elsevier, vol. 36(11), pages 6661-6673.
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    4. Ku-Hsieh Chen & Jen-Chi Cheng & Joe-Ming Lee & Liou-Yuan Li & Sheng-Yu Peng, 2020. "Energy Efficiency: Indicator, Estimation, and a New Idea," Sustainability, MDPI, vol. 12(12), pages 1-19, June.
    5. 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.
    6. Shun Jia & Qingwen Yuan & Wei Cai & Qinghe Yuan & Conghu Liu & Jingxiang Lv & Zhongwei Zhang, 2018. "Establishment of an Improved Material-Drilling Power Model to Support Energy Management of Drilling Processes," Energies, MDPI, vol. 11(8), pages 1-16, August.
    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).
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    11. Jia, Shun & Cai, Wei & Liu, Conghu & Zhang, Zhongwei & Bai, Shuowei & Wang, Qiuyan & Li, Shuoshuo & Hu, Luoke, 2021. "Energy modeling and visualization analysis method of drilling processes in the manufacturing industry," Energy, Elsevier, vol. 228(C).
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