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Energy economics in the manufacturing industry: A return on investment strategy

Author

Listed:
  • Brundage, Michael P.
  • Chang, Qing
  • Zou, Jing
  • Li, Yang
  • Arinez, Jorge
  • Xiao, Guoxian

Abstract

Manufacturers lack the economic tools to properly perform maintenance procedures to increase manufacturing reliability while reducing system energy consumption. A return on investment strategy is developed to provide plant managers with a quantitative method to optimize the maintenance actions that lead to the largest return on investment. Over the long term, this energy economic analysis results in the largest decrease in energy costs for a manufacturing facility. A control methodology is developed to increase profits on a daily basis by inserting energy opportunity windows at various machines thus reducing energy consumption with minimal production impact. A simulation case study is performed to validate the return on investment strategy and to test the control methodology's impact on the overall profit of the facility.

Suggested Citation

  • Brundage, Michael P. & Chang, Qing & Zou, Jing & Li, Yang & Arinez, Jorge & Xiao, Guoxian, 2015. "Energy economics in the manufacturing industry: A return on investment strategy," Energy, Elsevier, vol. 93(P2), pages 1426-1435.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1426-1435
    DOI: 10.1016/j.energy.2015.10.038
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    References listed on IDEAS

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    Cited by:

    1. 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).
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    3. Memon, Abdul Jabbar & Shaikh, Muhammad Mujtaba, 2016. "Confidence bounds for energy conservation in electric motors: An economical solution using statistical techniques," Energy, Elsevier, vol. 109(C), pages 592-601.
    4. Liang Yang & Qinming Liu & Tangbin Xia & Chunming Ye & Jiaxiang Li, 2022. "Preventive Maintenance Strategy Optimization in Manufacturing System Considering Energy Efficiency and Quality Cost," Energies, MDPI, vol. 15(21), pages 1-18, November.
    5. Palander, Teijo & Haavikko, Hanna & Kärhä, Kalle, 2018. "Towards sustainable wood procurement in forest industry – The energy efficiency of larger and heavier vehicles in Finland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 100-118.
    6. Zou, Jing & Chang, Qing & Arinez, Jorge & Xiao, Guoxian, 2017. "Data-driven modeling and real-time distributed control for energy efficient manufacturing systems," Energy, Elsevier, vol. 127(C), pages 247-257.

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