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Energy efficiency for condition-based maintenance decision-making: Application to a manufacturing platform

Author

Listed:
  • Phuc Do
  • Anh Hoang
  • Benoit Iung
  • Hai-Canh Vu

Abstract

Condition-based maintenance has been developed and successfully applied in various industrial systems to preventively maintain the correct equipment at the right time with regard to its current health “condition†such as oil temperature, harmonics data, and vibration. The monitoring of these conventional indicators may however be costly. Moreover, energy efficiency addressed by sustainability requirements has been recently considered as an emerging key performance indicator to be controlled. Nevertheless, this emerging key performance indicator is not yet integrated in condition-based maintenance decision-making. To face these issues, the main objective of this article is to investigate the interests to use energy efficiency for condition-based maintenance decision-making. The first original contribution of this article is to propose a new energy efficiency–based condition-based maintenance model using energy efficiency indicator which is defined as the amount of energy consumption to produce one useful output unit. The proposed model leads to consider not only the maintenance cost but also energy and useful output performance in the condition-based maintenance optimization process. The second contribution concerns an investigation of the proposed energy efficiency–based condition-based maintenance model for the case study of the TELMA platform. The performance of the proposed model is verified by comparing to an extended traditional one. The obtained results allow to highlight the impacts of energy efficiency on existing condition-based maintenance strategies and to conclude on the interest of a new energy efficiency indicator–based condition-based maintenance practice in terms of both cost and efficiency.

Suggested Citation

  • Phuc Do & Anh Hoang & Benoit Iung & Hai-Canh Vu, 2018. "Energy efficiency for condition-based maintenance decision-making: Application to a manufacturing platform," Journal of Risk and Reliability, , vol. 232(4), pages 379-388, August.
  • Handle: RePEc:sae:risrel:v:232:y:2018:i:4:p:379-388
    DOI: 10.1177/1748006X18762282
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