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Emergy based sustainability evaluation of remanufacturing machining systems

Author

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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    4. 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.
    5. 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).
    6. 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.
    7. Jorge Luis García Alcaraz & Adrián Salvador Morales García & José Roberto Díaz Reza & Julio Blanco Fernández & Emilio Jiménez Macías & Rita Puig i Vidal, 2022. "Machinery Lean Manufacturing Tools for Improved Sustainability: The Mexican Maquiladora Industry Experience," Mathematics, MDPI, vol. 10(9), pages 1-18, April.
    8. Mohammed Alkahtani & Aiman Ziout & Bashir Salah & Moath Alatefi & Abd Elatty E. Abd Elgawad & Ahmed Badwelan & Umar Syarif, 2021. "An Insight into Reverse Logistics with a Focus on Collection Systems," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    9. 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).
    10. Gao, Mengdi & Liu, Conghu & Li, Lei & Li, Qiang & Wang, Qingyang & Liu, Zhifeng, 2024. "Emergy-based method for the sustainability assessment and improvement of additive manufacturing systems," Energy, Elsevier, vol. 290(C).
    11. 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.

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