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Towards an innovative lubricant condition monitoring strategy for maintenance of ageing multi-unit systems

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  • Wakiru, James
  • Pintelon, Liliane
  • Muchiri, Peter N.
  • Chemweno, Peter K.
  • Mburu, Stanley

Abstract

The high acquisition cost retained by replacement of ageing and deteriorating assets triggers operational life-extension for the systems. Subsequently, ageing effects like compromised performance and wear are introduced, adversely affecting system economics and performance. An integrated maintenance and spares strategy incorporating lubricant condition monitoring (LCM) under condition-based maintenance (CBM), corrective maintenance (CM) and preventive maintenance (PM) is proposed, to mitigate the ageing effect challenges. The study considers the lubricant not only as a monitored item, but as a spare like other repairable units, similarly deteriorating, and retaining different maintenance interventions. We link the lubricant degradation (iron and viscosity oil properties) and repairable units’ degradation and performance, by integrating rate-state interactions with imperfect maintenance to derive stochastic dependencies in the degradation model. The applicability of the proposed discrete event simulation model is illustrated for a geothermal drilling rig, whose performance (maintenance cost and lubricant volume) are derived. Results demonstrate system performance dependency on PM intervals and CM strategies for both the lubricant and the repairable units. The significance of LCM policy to maintenance and system performance is substantiated. The developed framework has widespread use in real-life and broader applications that include LCM in deriving maintenance decision support.

Suggested Citation

  • Wakiru, James & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K. & Mburu, Stanley, 2020. "Towards an innovative lubricant condition monitoring strategy for maintenance of ageing multi-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020307018
    DOI: 10.1016/j.ress.2020.107200
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    References listed on IDEAS

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    1. Poppe, Joeri & Basten, Rob J.I. & Boute, Robert N. & Lambrecht, Marc R., 2017. "Numerical study of inventory management under various maintenance policies," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 262-273.
    2. Wakiru, James M. & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K., 2019. "A simulation-based optimization approach evaluating maintenance and spare parts demand interaction effects," International Journal of Production Economics, Elsevier, vol. 208(C), pages 329-342.
    3. Sequeira, C. & Pacheco, A. & Galego, P. & Gorbeña, E., 2019. "Analysis of the efficiency of wind turbine gearboxes using the temperature variable," Renewable Energy, Elsevier, vol. 135(C), pages 465-472.
    4. Mugnaini, Marco & Addabbo, Tommaso & Fort, Ada & Elmi, Alessandro & Landi, Elia & Vignoli, Valerio, 2020. "Magnetic brakes material characterization under accelerated testing conditions," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Do, Phuc & Assaf, Roy & Scarf, Phil & Iung, Benoit, 2019. "Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 86-97.
    6. Shahraki, Ameneh Forouzandeh & Yadav, Om Prakash & Vogiatzis, Chrysafis, 2020. "Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    7. Alrabghi, Abdullah & Tiwari, Ashutosh, 2016. "A novel approach for modelling complex maintenance systems using discrete event simulation," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 160-170.
    8. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2015. "Multi-level predictive maintenance for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 83-94.
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    Cited by:

    1. Pan, Yan & Liang, Bin & Yang, Lei & Liu, Houde & Wu, Tonghai & Wang, Shuo, 2024. "Spatial-temporal modeling of oil condition monitoring: A review," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Wakiru, James & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K., 2021. "Integrated remanufacturing, maintenance and spares policies towards life extension of a multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. González-Muñiz, Ana & Díaz, Ignacio & Cuadrado, Abel A. & García-Pérez, Diego, 2022. "Health indicator for machine condition monitoring built in the latent space of a deep autoencoder," Reliability Engineering and System Safety, Elsevier, vol. 224(C).

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