IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v153y2016icp151-158.html
   My bibliography  Save this article

Optimization of test and maintenance of ageing components consisting of multiple items and addressing effectiveness

Author

Listed:
  • Martón, I.
  • Martorell, P.
  • Mullor, R.
  • Sánchez, A.I.
  • Martorell, S.

Abstract

There are many models in the literature that have been proposed in the last decades aimed at assessing the reliability, availability and maintainability (RAM) of safety equipment, many of them with a focus on their use to assess the risk level of a technological system or to search for appropriate design and/or surveillance and maintenance policies in order to assure that an optimum level of RAM of safety systems is kept during all the plant operational life. This paper proposes a new approach for RAM modelling that accounts for equipment ageing and maintenance and testing effectiveness of equipment consisting of multiple items in an integrated manner. This model is then used to perform the simultaneous optimization of testing and maintenance for ageing equipment consisting of multiple items. An example of application is provided, which considers a simplified High Pressure Injection System (HPIS) of a typical Power Water Reactor (PWR). Basically, this system consists of motor driven pumps (MDP) and motor operated valves (MOV), where both types of components consists of two items each. These components present different failure and cause modes and behaviours, and they also undertake complex test and maintenance activities depending on the item involved. The results of the example of application demonstrate that the optimization algorithm provide the best solutions when the optimization problem is formulated and solved considering full flexibility in the implementation of testing and maintenance activities taking part of such an integrated RAM model.

Suggested Citation

  • Martón, I. & Martorell, P. & Mullor, R. & Sánchez, A.I. & Martorell, S., 2016. "Optimization of test and maintenance of ageing components consisting of multiple items and addressing effectiveness," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 151-158.
  • Handle: RePEc:eee:reensy:v:153:y:2016:i:c:p:151-158
    DOI: 10.1016/j.ress.2016.04.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832016300436
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2016.04.015?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. Courtois, Pierre-Jacques & Delsarte, Philippe, 2006. "On the optimal scheduling of periodic tests and maintenance for reliable redundant components," Reliability Engineering and System Safety, Elsevier, vol. 91(1), pages 66-72.
    2. Khatab, A. & Aghezzaf, E.-H., 2016. "Selective maintenance optimization when quality of imperfect maintenance actions are stochastic," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 182-189.
    3. Sanchez, Ana & Carlos, Sofia & Martorell, Sebastian & Villanueva, Jose F., 2009. "Addressing imperfect maintenance modelling uncertainty in unavailability and cost based optimization," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 22-32.
    4. Compare, M. & Martini, F. & Zio, E., 2015. "Genetic algorithms for condition-based maintenance optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 244(2), pages 611-623.
    5. Martorell, S. & Carlos, S. & Villanueva, J.F. & Sanchez, A.I & Galvan, B. & Salazar, D. & Cepin, M., 2006. "Use of multiple objective evolutionary algorithms in optimizing surveillance requirements," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1027-1038.
    6. Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    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. Mocellin, Paolo & Pilenghi, Lisa, 2023. "Semi-quantitative approach to prioritize risk in industrial chemical plants aggregating safety, economics and ageing: A case study," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Afzali, Peyman & Keynia, Farshid & Rashidinejad, Masoud, 2019. "A new model for reliability-centered maintenance prioritisation of distribution feeders," Energy, Elsevier, vol. 171(C), pages 701-709.
    3. Martorell, P. & Martón, I. & Sánchez, A.I. & Martorell, S., 2017. "Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 18-27.
    4. Thiago Lima de Barros & Rodrigo Sampaio Lopes, 2021. "Continuous improvement of imperfect maintenance actions in PAS and PAR models," Journal of Risk and Reliability, , vol. 235(5), pages 941-958, October.
    5. Martón, I. & Sánchez, A.I. & Carlos, S. & Mullor, R. & Martorell, S., 2023. "Prognosis of wear-out effect on of safety equipment reliability for nuclear power plants long-term safe operation," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Martorell, S. & Martón, I. & Sánchez, A. & Carlos, S., 2020. "Harmonisation of surveillance requirements and maintenance in a context of ageing and obsolescence based on reliability, availability and risk information," Reliability Engineering and System Safety, Elsevier, vol. 202(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. KanÄ ev, DuÅ¡ko & ÄŒepin, Marko & Gjorgiev, Blaže, 2014. "Development and application of a living probabilistic safety assessment tool: Multi-objective multi-dimensional optimization of surveillance requirements in NPPs considering their ageing," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 135-147.
    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    3. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2009. "Modelling and optimization of proof testing policies for safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 838-854.
    4. Hajipour, Yassin & Taghipour, Sharareh, 2016. "Non-periodic inspection optimization of multi-component and k-out-of-m systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 228-243.
    5. Martorell, S. & Villamizar, M. & Martón, I. & Villanueva, J.F. & Carlos, S. & Sánchez, A.I., 2014. "Evaluation of risk impact of changes to surveillance requirements addressing model and parameter uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 153-165.
    6. Dilaver, Halit Metehan & Akçay, Alp & van Houtum, Geert-Jan, 2023. "Integrated planning of asset-use and dry-docking for a fleet of maritime assets," International Journal of Production Economics, Elsevier, vol. 256(C).
    7. Son, Kwang Seop & Seong, Seung Hwan & Kang, Hyun Gook & Jang, Gwi Sook, 2020. "Development of state-based integrated dependability model of RPS in NPPs considering CCF and periodic testing effects at the early design phase," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Radim Briš & Nuong Thi Thuy Tran, 2023. "Discrete Model for a Multi-Objective Maintenance Optimization Problem of Safety Systems," Mathematics, MDPI, vol. 11(2), pages 1-18, January.
    9. Mancuso, A. & Compare, M. & Salo, A. & Zio, E., 2021. "Optimal Prognostics and Health Management-driven inspection and maintenance strategies for industrial systems," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    10. Wenbin Cao & Xisheng Jia & Yu Liu & Qiwei Hu & Jianmin Zhao, 2019. "Selective maintenance optimisation considering random common cause failures and imperfect maintenance," Journal of Risk and Reliability, , vol. 233(3), pages 427-443, June.
    11. Shuo-Yan Chou & Xuan Loc Pham & Thi Anh Tuyet Nguyen & Tiffany Hui-Kuang Yu, 2023. "Optimal maintenance planning with special emphasis on deterioration process and vessel routing for offshore wind systems," Energy & Environment, , vol. 34(4), pages 739-763, June.
    12. Tanwar, Monika & Rai, Rajiv N. & Bolia, Nomesh, 2014. "Imperfect repair modeling using Kijima type generalized renewal process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 24-31.
    13. Ágota Bányai, 2021. "Energy Consumption-Based Maintenance Policy Optimization," Energies, MDPI, vol. 14(18), pages 1-33, September.
    14. Shin, Sung Min & Jeon, In Seop & Kang, Hyun Gook, 2015. "Surveillance test and monitoring strategy for the availability improvement of standby equipment using age-dependent model," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 100-106.
    15. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
    16. Briš, Radim & Byczanski, Petr, 2013. "Effective computing algorithm for maintenance optimization of highly reliable systems," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 77-85.
    17. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    18. Hamzea Al-Jabouri & Ahmed Saif & Claver Diallo, 2023. "Robust selective maintenance optimization of series–parallel mission-critical systems subject to maintenance quality uncertainty," Computational Management Science, Springer, vol. 20(1), pages 1-31, December.
    19. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    20. Liu, Lujie & Yang, Jun & Kong, Xuefeng & Xiao, Yiyong, 2022. "Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

    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:153:y:2016:i:c:p:151-158. 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.