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Industrial maintenance policy development: A quantitative framework

Author

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  • Faccio, M.
  • Persona, A.
  • Sgarbossa, F.
  • Zanin, G.

Abstract

All manufacturing companies define their business strategies and competitive priorities based on several factors related to their production systems, like flexibility, productivity and quality. As a consequence, maintenance plays a crucial role in guaranteeing availability and reliability of production facilities; hence, designing proper maintenance policies allows companies reach their goals.

Suggested Citation

  • Faccio, M. & Persona, A. & Sgarbossa, F. & Zanin, G., 2014. "Industrial maintenance policy development: A quantitative framework," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 85-93.
    • Handle: RePEc:eee:proeco:v:147:y:2014:i:pa:p:85-93
    DOI: 10.1016/j.ijpe.2012.08.018
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    References listed on IDEAS

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    6. Alessandro Persona & Fabio Sgarbossa & Hoang Pham, 2009. "Systemability function to optimisation reliability in random environment," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 1(3), pages 397-417.
    7. Richard Barlow & Larry Hunter, 1960. "Optimum Preventive Maintenance Policies," Operations Research, INFORMS, vol. 8(1), pages 90-100, February.
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    Citations

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    Cited by:

    1. Tao, Xin & Mårtensson, Jonas & Warnquist, Håkan & Pernestål, Anna, 2022. "Short-term maintenance planning of autonomous trucks for minimizing economic risk," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    2. Amir Homayoun Sarfaraz & Amir Karbassi Yazdi & Thomas Hanne & Peter Fernandes Wanke & Raheleh Sadat Hosseini, 2023. "Assessing repair and maintenance efficiency for water suppliers: a novel hybrid USBM-FIS framework," Operations Management Research, Springer, vol. 16(3), pages 1321-1342, September.
    3. Alireza Tabrizikahou & Piotr Nowotarski, 2021. "Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes," Energies, MDPI, vol. 14(11), pages 1-20, June.
    4. Erkoyuncu, John Ahmet & Khan, Samir & Eiroa, Alexandre López & Butler, Nigel & Rushton, Keith & Brocklebank, Simon, 2017. "Perspectives on trading cost and availability for corrective maintenance at the equipment type level," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 53-69.
    5. de Jonge, Bram & Dijkstra, Arjan S. & Romeijnders, Ward, 2015. "Cost benefits of postponing time-based maintenance under lifetime distribution uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 15-21.
    6. Havinga, Maik J.A. & de Jonge, Bram, 2020. "Condition-based maintenance in the cyclic patrolling repairman problem," International Journal of Production Economics, Elsevier, vol. 222(C).
    7. B. Kirubakaran & M. Ilangkumaran, 2016. "Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS," Annals of Operations Research, Springer, vol. 245(1), pages 285-313, October.
    8. Chin, Hon Huin & Wang, Bohong & Varbanov, Petar Sabev & Klemeš, Jiří Jaromír & Zeng, Min & Wang, Qiu-Wang, 2020. "Long-term investment and maintenance planning for heat exchanger network retrofit," Applied Energy, Elsevier, vol. 279(C).
    9. Toon Vanderschueren & Robert Boute & Tim Verdonck & Bart Baesens & Wouter Verbeke, 2022. "Prescriptive maintenance with causal machine learning," Papers 2206.01562, arXiv.org.
    10. Vanderschueren, Toon & Boute, Robert & Verdonck, Tim & Baesens, Bart & Verbeke, Wouter, 2023. "Optimizing the preventive maintenance frequency with causal machine learning," International Journal of Production Economics, Elsevier, vol. 258(C).

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