IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v142y2018icp258-263.html
   My bibliography  Save this article

Energy benchmarking rules in machining systems

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217316997
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.10.030?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. 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.
    2. 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.
    3. 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.
    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. 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.
    8. 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.
    9. 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.
    10. 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.
    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.
    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. Xiao, Qinge & Li, Congbo & Tang, Ying & Li, Lingling & Li, Li, 2019. "A knowledge-driven method of adaptively optimizing process parameters for energy efficient turning," Energy, Elsevier, vol. 166(C), pages 142-156.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. Salvatori, Simone & Benedetti, Miriam & Bonfà, Francesca & Introna, Vito & Ubertini, Stefano, 2018. "Inter-sectorial benchmarking of compressed air generation energy performance: Methodology based on real data gathering in large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 217(C), pages 266-280.
    8. Raman Kumar & Sehijpal Singh & Ardamanbir Singh Sidhu & Catalin I. Pruncu, 2021. "Bibliometric Analysis of Specific Energy Consumption (SEC) in Machining Operations: A Sustainable Response," Sustainability, MDPI, vol. 13(10), pages 1-30, May.
    9. Shang, Zhendong & Gao, Dong & Jiang, Zhipeng & Lu, Yong, 2021. "A multi-perspective analysis of sustainability of machining processes based on a new extended virtual manufacturing framework," Energy, Elsevier, vol. 225(C).
    10. Minda Ma & Ran Yan & Weiguang Cai, 2018. "Energy savings evaluation in public building sector during the 10th–12th FYP periods of China: an extended LMDI model approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(1), pages 429-441, May.
    11. 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).
    12. Cabello Eras, Juan José & Sagastume Gutiérrez, Alexis & Sousa Santos, Vladimir & Cabello Ulloa, Mario Javier, 2020. "Energy management of compressed air systems. Assessing the production and use of compressed air in industry," Energy, Elsevier, vol. 213(C).
    13. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2018. "Application of the novel fractional grey model FAGMO(1,1,k) to predict China's nuclear energy consumption," Energy, Elsevier, vol. 165(PB), pages 223-234.

    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. 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. 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).
    3. 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.
    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. 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.
    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. Benedetti, Miriam & Bonfa', Francesca & Bertini, Ilaria & Introna, Vito & Ubertini, Stefano, 2018. "Explorative study on Compressed Air Systems’ energy efficiency in production and use: First steps towards the creation of a benchmarking system for large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 227(C), pages 436-448.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. Patterson, S.R. & Kozan, E. & Hyland, P., 2017. "Energy efficient scheduling of open-pit coal mine trucks," European Journal of Operational Research, Elsevier, vol. 262(2), pages 759-770.
    13. Topno, Seema Ashishan & Sahoo, Lalit Kumar & Umre, B.S., 2021. "Energy efficiency assessment of electric shovel operating in opencast mine," Energy, Elsevier, vol. 230(C).
    14. Salvatori, Simone & Benedetti, Miriam & Bonfà, Francesca & Introna, Vito & Ubertini, Stefano, 2018. "Inter-sectorial benchmarking of compressed air generation energy performance: Methodology based on real data gathering in large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 217(C), pages 266-280.
    15. 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.
    16. 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).
    17. 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.
    18. Zhaohui Feng & Xinru Ding & Hua Zhang & Ying Liu & Wei Yan & Xiaoli Jiang, 2023. "An Energy Consumption Estimation Method for the Tool Setting Process in CNC Milling Based on the Modular Arrangement of Predetermined Time Standards," Energies, MDPI, vol. 16(20), pages 1-18, October.
    19. 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.
    20. 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).

    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:142:y:2018:i:c:p:258-263. 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.