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A mixture frailty model for maintainability analysis of mechanical components: a case study

Author

Listed:
  • Rezgar Zaki

    (UiT The Arctic University of Norway)

  • Abbas Barabadi

    (UiT The Arctic University of Norway)

  • Ali Nouri Qarahasanlou

    (Shahrood University of Technology)

  • A. H. S. Garmabaki

    (Luleå University of Technology)

Abstract

Knowing the maintainability of a component or a system means that repair resource allocations, such as spare part procurement and maintenance training, can be planned and optimized more effectively. Repair data are often collected from multiple and distributed units in different operational conditions, which can introduce heterogeneity into the data. Part of such heterogeneity can be explained and isolated by the observable covariates, whose values and the way that they can affect the item’s maintainability are known. However, some factors which may affect maintainability are typically unknown (unobserved covariates), leading to unobserved heterogeneity. Nevertheless, many researchers have ignored the effect of observed and un-observed covariates, and this may lead to erroneous model selection, as well as wrong conclusions and decisions. Moreover, many authors have simplified their analysis by considering a complex system as a single item. In these studies, the assumption is that all repair data represent an identical repair process for the item. In practice, mechanical systems are composed of multiple parts, with various failure mechanisms, which need different repair processes (repair modes) to return to the operational phase; classical distribution, such as lognormal, which is only a function of time, may not be able to model such complexity. The paper utilizes the mixture frailty model (MFM) in the presence of some specific observed or unobserved covariates to predict maintainability more precisely. MFMs can model the effect of observed and unobserved covariates, as well as identifying different repair processes in the repair dataset. The application of the proposed model is demonstrated by a case study.

Suggested Citation

  • Rezgar Zaki & Abbas Barabadi & Ali Nouri Qarahasanlou & A. H. S. Garmabaki, 2019. "A mixture frailty model for maintainability analysis of mechanical components: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(6), pages 1646-1653, December.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:6:d:10.1007_s13198-019-00917-3
    DOI: 10.1007/s13198-019-00917-3
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    References listed on IDEAS

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    1. Bodunrin Brown & Bin Liu & Stuart McIntyre & Matthew Revie, 2023. "Reliability evaluation of repairable systems considering component heterogeneity using frailty model," Journal of Risk and Reliability, , vol. 237(4), pages 654-670, August.
    2. Reza Barabadi & Mohammad Ataei & Reza Khalokakaie & Ali Nouri Qarahasanlou, 2021. "Spare-part management in a heterogeneous environment," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-14, March.
    3. Ali Nouri Qarahasanlou & Ali Zamani & Abbas Barabadi & Mahdi Mokhberdoran, 2021. "Resilience Assessment: A Performance-Based Importance Measure," Energies, MDPI, vol. 14(22), pages 1-16, November.
    4. Luo, Xu & Ge, Zhexue & Zhang, ShiGang & Yang, Yongmin, 2021. "A method for the maintainability evaluation at design stage using maintainability design attributes," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    5. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "Resilience analysis: A formulation to model risk factors on complex system resilience," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 871-883, October.

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