IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v168y2017icp171-188.html
   My bibliography  Save this article

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Author

Listed:
  • Aizpurua, J.I.
  • Catterson, V.M.
  • Papadopoulos, Y.
  • Chiacchio, F.
  • D'Urso, D.

Abstract

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry.

Suggested Citation

  • Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    • Handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:171-188
    DOI: 10.1016/j.ress.2017.04.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832016308626
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2017.04.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Caballé, N.C. & Castro, I.T. & Pérez, C.J. & Lanza-Gutiérrez, J.M., 2015. "A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 98-109.
    2. Huynh, K.T. & Grall, A. & Bérenguer, C., 2017. "Assessment of diagnostic and prognostic condition indices for efficient and robust maintenance decision-making of systems subject to stress corrosion cracking," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 237-254.
    3. Cadini, F. & Zio, E. & Avram, D., 2009. "Model-based Monte Carlo state estimation for condition-based component replacement," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 752-758.
    4. An, Dawn & Kim, Nam H. & Choi, Joo-Ho, 2015. "Practical options for selecting data-driven or physics-based prognostics algorithms with reviews," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 223-236.
    5. Li, Heping & Deloux, Estelle & Dieulle, Laurence, 2016. "A condition-based maintenance policy for multi-component systems with Lévy copulas dependence," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 44-55.
    6. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    7. Manno, G. & Chiacchio, F. & Compagno, L. & D'Urso, D. & Trapani, N., 2014. "Conception of Repairable Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab® toolbox based on the ATS formalism," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 250-262.
    8. Chiacchio, F. & Cacioppo, M. & D'Urso, D. & Manno, G. & Trapani, N. & Compagno, L., 2013. "A Weibull-based compositional approach for hierarchical dynamic fault trees," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 45-52.
    9. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe & Bouvard, Keomany & Brissaud, Florent, 2013. "Dynamic grouping maintenance with time limited opportunities," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 51-59.
    10. Verbert, K. & De Schutter, B. & Babuška, R., 2017. "Timely condition-based maintenance planning for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 310-321.
    11. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe, 2008. "Reliability importance analysis of Markovian systems at steady state using perturbation analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1605-1615.
    12. Fink, Olga & Zio, Enrico & Weidmann, Ulrich, 2014. "Predicting component reliability and level of degradation with complex-valued neural networks," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 198-206.
    13. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    14. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, February.
    15. Asadzadeh, S.M. & Azadeh, A., 2014. "An integrated systemic model for optimization of condition-based maintenance with human error," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 117-131.
    16. Andrews, John & Fecarotti, Claudia, 2017. "System design and maintenance modelling for safety in extended life operation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 95-108.
    17. V Zille & C Bérenguer & A Grall & A Despujols, 2011. "Modelling multicomponent systems to quantify reliability centred maintenance strategies," Journal of Risk and Reliability, , vol. 225(2), pages 141-160, June.
    18. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    19. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    20. Wildeman, R. E. & Dekker, R. & Smit, A. C. J. M., 1997. "A dynamic policy for grouping maintenance activities," European Journal of Operational Research, Elsevier, vol. 99(3), pages 530-551, June.
    21. Cavalcante, Cristiano A.V. & Lopes, Rodrigo S., 2015. "Multi-criteria model to support the definition of opportunistic maintenance policy: A study in a cogeneration system," Energy, Elsevier, vol. 80(C), pages 32-40.
    22. Chiacchio, F. & D’Urso, D. & Manno, G. & Compagno, L., 2016. "Stochastic hybrid automaton model of a multi-state system with aging: Reliability assessment and design consequences," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 1-13.
    23. Khorasgani, Hamed & Biswas, Gautam & Sankararaman, Shankar, 2016. "Methodologies for system-level remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 8-18.
    24. Shafiee, Mahmood & Finkelstein, Maxim & Bérenguer, Christophe, 2015. "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 463-471.
    25. Zio, Enrico & Compare, Michele, 2013. "Evaluating maintenance policies by quantitative modeling and analysis," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 53-65.
    26. Van Horenbeek, Adriaan & Pintelon, Liliane, 2013. "A dynamic predictive maintenance policy for complex multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 39-50.
    27. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe, 2010. "From differential to difference importance measures for Markov reliability models," European Journal of Operational Research, Elsevier, vol. 204(3), pages 513-521, August.
    28. Do, Phuc & Voisin, Alexandre & Levrat, Eric & Iung, Benoit, 2015. "A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 22-32.
    29. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    30. Bouvard, K. & Artus, S. & Bérenguer, C. & Cocquempot, V., 2011. "Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles," Reliability Engineering and System Safety, Elsevier, vol. 96(6), pages 601-610.
    31. Andrews, John & Prescott, Darren & De Rozières, Florian, 2014. "A stochastic model for railway track asset management," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 76-84.
    32. Azadeh, A. & Asadzadeh, S.M. & Salehi, N. & Firoozi, M., 2015. "Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 357-368.
    33. Wu, Shaomin & Chen, Yi & Wu, Qingtai & Wang, Zhonglai, 2016. "Linking component importance to optimisation of preventive maintenance policy," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 26-32.
    34. 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.
    35. Do, Phuc & Vu, Hai Canh & Barros, Anne & Bérenguer, Christophe, 2015. "Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 56-67.
    36. Rasmekomen, Nipat & Parlikad, Ajith Kumar, 2016. "Condition-based maintenance of multi-component systems with degradation state-rate interactions," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 1-10.
    37. Shafiee, Mahmood & Finkelstein, Maxim, 2015. "An optimal age-based group maintenance policy for multi-unit degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 230-238.
    38. 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.
    39. Koutras, V.P. & Malefaki, S. & Platis, A.N., 2017. "Optimization of the dependability and performance measures of a generic model for multi-state deteriorating systems under maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 73-86.
    40. Vu, Hai Canh & Do, Phuc & Barros, Anne & Bérenguer, Christophe, 2014. "Maintenance grouping strategy for multi-component systems with dynamic contexts," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 233-249.
    41. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2016. "Clustering condition-based maintenance for systems with redundancy and economic dependencies," European Journal of Operational Research, Elsevier, vol. 251(2), pages 531-540.
    42. Borgonovo, E., 2007. "Differential, criticality and Birnbaum importance measures: An application to basic event, groups and SSCs in event trees and binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1458-1467.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang, Zhenglin & Parlikad, Ajith Kumar, 2020. "Predictive group maintenance for multi-system multi-component networks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Victor Bolbot & Gerasimos Theotokatos & Rainer Hamann & George Psarros & Evangelos Boulougouris, 2021. "Dynamic Blackout Probability Monitoring System for Cruise Ship Power Plants," Energies, MDPI, vol. 14(20), pages 1-19, October.
    3. Ferdinando Chiacchio & Fabio Famoso & Diego D’Urso & Luca Cedola, 2019. "Performance and Economic Assessment of a Grid-Connected Photovoltaic Power Plant with a Storage System: A Comparison between the North and the South of Italy," Energies, MDPI, vol. 12(12), pages 1-25, June.
    4. He, Rui & Tian, Zhigang & Wang, Yifei & Zuo, Mingjian & Guo, Ziwei, 2023. "Condition-based maintenance optimization for multi-component systems considering prognostic information and degraded working efficiency," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. Li Li & Yong Wang & Kuo-Yi Lin, 2021. "Preventive maintenance scheduling optimization based on opportunistic production-maintenance synchronization," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 545-558, February.
    6. Ariannik, Mohamadreza & Razi-Kazemi, Ali A. & Lehtonen, Matti, 2020. "An approach on lifetime estimation of distribution transformers based on degree of polymerization," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    7. Aizpurua, J.I. & Stewart, B.G. & McArthur, S.D.J. & Penalba, M. & Barrenetxea, M. & Muxika, E. & Ringwood, J.V., 2022. "Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    8. Gia-Shie Liu, 2019. "A Group Replacement Decision Support System Based on Internet of Things," Mathematics, MDPI, vol. 7(9), pages 1-23, September.
    9. Meissner, Robert & Rahn, Antonia & Wicke, Kai, 2021. "Developing prescriptive maintenance strategies in the aviation industry based on a discrete-event simulation framework for post-prognostics decision making," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    10. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.
    11. Chiacchio, Ferdinando & Iacono, Alessandra & Compagno, Lucio & D'Urso, Diego, 2020. "A general framework for dependability modelling coupling discrete-event and time-driven simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    12. Tsoumpris, Charalampos & Theotokatos, Gerasimos, 2023. "A decision-making approach for the health-aware energy management of ship hybrid power plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    13. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.
    14. Centeno-Telleria, Manu & Aizpurua, Jose Ignacio & Penalba, Markel, 2023. "Computationally efficient analytical O&M model for strategic decision-making in offshore renewable energy systems," Energy, Elsevier, vol. 285(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    2. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    3. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2017. "Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 249-261.
    4. 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.
    5. Wu, Tianyi & Yang, Li & Ma, Xiaobing & Zhang, Zihan & Zhao, Yu, 2020. "Dynamic maintenance strategy with iteratively updated group information," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    6. Shafiee, Mahmood & Finkelstein, Maxim & Bérenguer, Christophe, 2015. "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 463-471.
    7. Liu, Bin & Pandey, Mahesh D. & Wang, Xiaolin & Zhao, Xiujie, 2021. "A finite-horizon condition-based maintenance policy for a two-unit system with dependent degradation processes," European Journal of Operational Research, Elsevier, vol. 295(2), pages 705-717.
    8. Mahmood Shafiee & Maxim Finkelstein, 2015. "A proactive group maintenance policy for continuously monitored deteriorating systems: Application to offshore wind turbines," Journal of Risk and Reliability, , vol. 229(5), pages 373-384, October.
    9. Urbani, Michele & Brunelli, Matteo & Punkka, Antti, 2023. "An approach for bi-objective maintenance scheduling on a networked system with limited resources," European Journal of Operational Research, Elsevier, vol. 305(1), pages 101-113.
    10. Olde Keizer, Minou C.A. & Flapper, Simme Douwe P. & Teunter, Ruud H., 2017. "Condition-based maintenance policies for systems with multiple dependent components: A review," European Journal of Operational Research, Elsevier, vol. 261(2), pages 405-420.
    11. de Jonge, Bram, 2019. "Discretizing continuous-time continuous-state deterioration processes, with an application to condition-based maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 1-5.
    12. Wang, Yukun & Li, Xiaopeng & Chen, Junyan & Liu, Yiliu, 2022. "A condition-based maintenance policy for multi-component systems subject to stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    13. KarabaÄŸ, Oktay & Eruguz, Ayse Sena & Basten, Rob, 2020. "Integrated optimization of maintenance interventions and spare part selection for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    14. Do, Phuc & Vu, Hai Canh & Barros, Anne & Bérenguer, Christophe, 2015. "Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 56-67.
    15. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.
    16. Do, Phuc & Bérenguer, Christophe, 2020. "Conditional reliability-based importance measures," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    17. Shi, Yue & Zhu, Weihang & Xiang, Yisha & Feng, Qianmei, 2020. "Condition-based maintenance optimization for multi-component systems subject to a system reliability requirement," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    18. Fecarotti, Claudia & Andrews, John & Pesenti, Raffaele, 2021. "A mathematical programming model to select maintenance strategies in railway networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    19. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    20. Uit Het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1119-1131.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:171-188. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.