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Emergy based sustainability evaluation of remanufacturing machining systems

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Listed:
  • Liu, Conghu
  • Cai, Wei
  • Dinolov, Ognyan
  • Zhang, Cuixia
  • Rao, Weizhen
  • Jia, Shun
  • Li, Li
  • Chan, Felix T.S.

Abstract

The remanufacturing machining has been recognized as an effective technology that helps improving the energy and materials utilization, and resulting environmental emissions and production costs decrease. Due to the intense lack of sustainability evaluation, therefore, this paper presents a novel emergy based evaluation method considering these objects in the remanufacturing machining systems. On basis of analyzing the remanufacturing machining and sustainability, this method comprises data collection, emergy based sustainability evaluation model and development of sustainable evaluation indexes and systems. Meanwhile, this method translates the quality loss function, time loss function, and cost into emergy by the Emdollar value, and calculates the emergy value of the environmental losses caused by the energy and resources used in remanufacturing machining process and its waste. Finally, the results of the remanufacturing crankshaft machining show that the remanufacturing machining system possesses high production efficiency and return with heavy environmental load state, and the sustainability index is less than 0.05. There is considerable potential for utilizing the energy and alloy powders of the remanufacturing technologies. This study contributes to studying sustainability modeling of remanufacturing to evaluate machining process and to optimize remanufacturers and manufacturers.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:670-680
    DOI: 10.1016/j.energy.2018.02.113
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    References listed on IDEAS

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    5. 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.
    6. Yuyao Guo & Lei Wang & Zelin Zhang & Jianhua Cao & Xuhui Xia, 2023. "Association Rule Mining-Based Generalized Growth Mode Selection: Maximizing the Value of Retired Mechanical Parts," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    7. Sun, Jingchao & Na, Hongming & Yan, Tianyi & Che, Zichang & Qiu, Ziyang & Yuan, Yuxing & Li, Yingnan & Du, Tao & Song, Yanli & Fang, Xin, 2022. "Cost-benefit assessment of manufacturing system using comprehensive value flow analysis," Applied Energy, Elsevier, vol. 310(C).
    8. Jian Cao & Xihui Chen & Sisi Wu & Sanjay Kumar, 2021. "Evolving remanufacturing strategies in China: an evolutionary game theory perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14827-14853, October.
    9. Cui Wang & Yingyan Zhang & Conghu Liu & Fagang Hu & Shuling Zhou & Juan Zhu, 2021. "Emergy-Based Assessment and Suggestions for Sustainable Development of Regional Ecological Economy: A Case Study of Anhui Province, China," Sustainability, MDPI, vol. 13(5), pages 1-20, March.
    10. Liu, Conghu & Gao, Mengdi & Zhu, Guang & Zhang, Cuixia & Zhang, Pan & Chen, Jianqing & Cai, Wei, 2021. "Data driven eco-efficiency evaluation and optimization in industrial production," Energy, Elsevier, vol. 224(C).

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