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A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

Citations

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Cited by:

  1. Garmabaki, A.H.S. & Ahmadi, Alireza & Block, Jan & Pham, Hoang & Kumar, Uday, 2016. "A reliability decision framework for multiple repairable units," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 78-88.
  2. Rajkumar Bhimgonda Patil & Basavraj S Kothavale & Laxman Yadu Waghmode, 2019. "Selection of time-to-failure model for computerized numerical control turning center based on the assessment of trends in maintenance data," Journal of Risk and Reliability, , vol. 233(2), pages 105-117, April.
  3. Carlos Parra & Adolfo Crespo & Fredy Kristjanpoller & Pablo Viveros, 2012. "Stochastic model of reliability for use in the evaluation of the economic impact of a failure using life cycle cost analysis. Case studies on the rail freight and oil industries," Journal of Risk and Reliability, , vol. 226(4), pages 392-405, August.
  4. Syed, Zaki & Lawryshyn, Yuri, 2020. "Risk analysis of an underground gas storage facility using a physics-based system performance model and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
  5. Hu, Wei & Westerlund, Per & Hilber, Patrik & Chen, Chuanhai & Yang, Zhaojun, 2022. "A general model, estimation, and procedure for modeling recurrent failure process of high-voltage circuit breakers considering multivariate impacts," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
  6. Wu, Shaomin, 2021. "Two methods to approximate the superposition of imperfect failure processes," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
  7. Ali N Qarahasanlou & Abbas Barabadi & Yonas Z Ayele, 2018. "Production performance analysis during operation phase: A case study," Journal of Risk and Reliability, , vol. 232(6), pages 559-575, December.
  8. Slimacek, Vaclav & Lindqvist, Bo Henry, 2017. "Nonhomogeneous Poisson process with nonparametric frailty and covariates," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 75-83.
  9. Izquierdo, J. & Crespo Márquez, A. & Uribetxebarria, J., 2019. "Dynamic artificial neural network-based reliability considering operational context of assets," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 483-493.
  10. Moghadam, Mehdi Akbari & Bagheri, Sajad & Salemi, Amir Hosein & Tavakoli, Mohammad Bagher, 2023. "Long-term maintenance planning of medium voltage overhead lines considering the uncertainties and reasons for interruption in a real distribution network," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
  11. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.
  12. Ali Nouri Gharahasanlou & Mohammad Ataei & Reza Khalokakaie & Abbas Barabadi & Vahid Einian, 2017. "Risk based maintenance strategy: a quantitative approach based on time-to-failure model," 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. 8(3), pages 602-611, September.
  13. Thijssens, O.W.M. & Verhagen, Wim J.C., 2020. "Application of Extended Cox Regression Model to Time-On-Wing Data of Aircraft Repairables," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
  14. Peng, Yizhen & Wang, Yu & Zi, YanYang & Tsui, Kwok-Leung & Zhang, Chuhua, 2017. "Dynamic reliability assessment and prediction for repairable systems with interval-censored data," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 301-309.
  15. Rezgar Zaki & Abbas Barabadi & Javad Barabady & Ali Nouri Qarahasanlou, 2022. "Observed and unobserved heterogeneity in failure data analysis," Journal of Risk and Reliability, , vol. 236(1), pages 194-207, February.
  16. Barabadi, A. & Ayele, Y.Z., 2018. "Post-disaster infrastructure recovery: Prediction of recovery rate using historical data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 209-223.
  17. Wu, Shaomin, 2019. "A failure process model with the exponential smoothing of intensity functions," European Journal of Operational Research, Elsevier, vol. 275(2), pages 502-513.
  18. Hu, Wei & Yang, Zhaojun & Chen, Chuanhai & Wu, Yue & Xie, Qunya, 2021. "A Weibull-based recurrent regression model for repairable systems considering double effects of operation and maintenance: A case study of machine tools," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
  19. Juan Izquierdo & Adolfo Crespo Márquez & Jone Uribetxebarria & Asier Erguido, 2019. "Framework for Managing Maintenance of Wind Farms Based on a Clustering Approach and Dynamic Opportunistic Maintenance," Energies, MDPI, vol. 12(11), pages 1-17, May.
  20. Dursun, İpek & Akçay, Alp & van Houtum, Geert-Jan, 2022. "Data pooling for multiple single-component systems under population heterogeneity," International Journal of Production Economics, Elsevier, vol. 250(C).
  21. Seyed Hadi Hoseinie & Hussan Al-Chalabi & Behzad Ghodrati, 2018. "Comparison between Simulation and Analytical Methods in Reliability Data Analysis: A Case Study on Face Drilling Rigs," Data, MDPI, vol. 3(2), pages 1-12, April.
  22. Taghipour, Sharareh & Banjevic, Dragan, 2011. "Trend analysis of the power law process using Expectation–Maximization algorithm for data censored by inspection intervals," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1340-1348.
  23. 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).
  24. Zhi-Ming Wang & Xia Yu, 2013. "Log-linear process modeling for repairable systems with time trends and its applications in reliability assessment of numerically controlled machine tools," Journal of Risk and Reliability, , vol. 227(1), pages 55-65, February.
  25. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico & Ault, Graham & Bell, Keith, 2013. "Reinforcement learning for microgrid energy management," Energy, Elsevier, vol. 59(C), pages 133-146.
  26. Mostafa Aliyari & Yonas Z Ayele & Abbas Barabadi & Enrique Lopez Droguett, 2019. "Risk analysis in low-voltage distribution systems," Journal of Risk and Reliability, , vol. 233(2), pages 118-138, April.
  27. Braglia, Marcello & Carmignani, Gionata & Frosolini, Marco & Zammori, Francesco, 2012. "Data classification and MTBF prediction with a multivariate analysis approach," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 27-35.
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