IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v189y2019icp67-88.html
   My bibliography  Save this article

A coloured Petri net framework for modelling aircraft fleet maintenance

Author

Listed:
  • Sheng, Jingyu
  • Prescott, Darren

Abstract

The aircraft fleet maintenance organisation is responsible for keeping aircraft in a safe, efficient operating condition. Through optimising the use of maintenance resources and the implementation of maintenance activities, fleet maintenance management aims to maximise fleet performance by, for example, ensuring there is minimal deviation from the planned operational schedule, that the number of unexpected failures is minimised or that maintenance cost is kept at a minimum. To obtain overall fleet performance, the performance of individual aircraft must first be known. The calculation of aircraft performance requires an accurate model of the fleet operation and maintenance processes. This paper aims to introduce a framework that can be used to build aircraft fleet maintenance models. A variety of CPN (coloured Petri nets) models are established to represent fleet maintenance activities and maintenance management, as well as the factors that have a significant impact on fleet maintenance including fleet operation, aircraft failure logic and component failure processes. Such CPN models provide an ideal structured framework for Monte Carlo simulation analysis, within which calculations can be performed in order to determine numerous fleet reliability and maintenance performance measures.

Suggested Citation

  • Sheng, Jingyu & Prescott, Darren, 2019. "A coloured Petri net framework for modelling aircraft fleet maintenance," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 67-88.
  • Handle: RePEc:eee:reensy:v:189:y:2019:i:c:p:67-88
    DOI: 10.1016/j.ress.2019.04.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017313431
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2019.04.004?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. Yongquan, Sun & Xi, Chen & He, Ren & Yingchao, Jin & Quanwu, Liu, 2016. "Ordering decision-making methods on spare parts for a new aircraft fleet based on a two-sample prediction," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 40-50.
    2. Vasile DEAC & Gheorghe CARSTEA & Constantin BAGU & Florea PARVU, 2010. "The Modern Approach to Industrial Maintenance Management," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 14(2), pages 133-144.
    3. Gopalan, Ram, 2014. "The Aircraft Maintenance Base Location Problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 634-642.
    4. Ville Mattila & Kai Virtanen & Tuomas Raivio, 2008. "Improving Maintenance Decision Making in the Finnish Air Force Through Simulation," Interfaces, INFORMS, vol. 38(3), pages 187-201, June.
    5. Feng, Qiang & Bi, Xiong & Zhao, Xiujie & Chen, Yiran & Sun, Bo, 2017. "Heuristic hybrid game approach for fleet condition-based maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 166-176.
    6. Sheng, Jingyu & Prescott, Darren, 2017. "A hierarchical coloured Petri net model of fleet maintenance with cannibalisation," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 290-305.
    7. Chew, S.P. & Dunnett, S.J. & Andrews, J.D., 2008. "Phased mission modelling of systems with maintenance-free operating periods using simulated Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 980-994.
    8. Sriram, Chellappan & Haghani, Ali, 2003. "An optimization model for aircraft maintenance scheduling and re-assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(1), pages 29-48, January.
    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. Cheng, Jianda & Cheng, Minghui & Liu, Yan & Wu, Jun & Li, Wei & Frangopol, Dan M., 2024. "Knowledge transfer for adaptive maintenance policy optimization in engineering fleets based on meta-reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    2. Lee, Juseong & Mitici, Mihaela, 2022. "Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    3. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2022. "Using kamikaze components in multi-attempt missions with abort option," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    4. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    5. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2023. "Optimal task sequencing and aborting in multi-attempt multi-task missions with a limited number of attempts," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    6. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2022. "Optimal mission aborting in multistate systems with storage," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    7. Gregory Levitin & Liudong Xing & Yuanshun Dai, 2020. "Mission Abort Policy for Systems with Observable States of Standby Components," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 1900-1912, October.
    8. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2024. "Optimal task aborting and sequencing in time constrained multi-task multi-attempt missions," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Yan, R. & Dunnett, S.J. & Jackson, L.M., 2022. "Model-Based Research for Aiding Decision-Making During the Design and Operation of Multi-Load Automated Guided Vehicle Systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2021. "Partial mission aborting in work sharing systems," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    11. Zhao, Xian & Liu, Haoran & Wu, Yaguang & Qiu, Qingan, 2023. "Joint optimization of mission abort and system structure considering dynamic tasks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    12. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2021. "Dynamic task distribution balancing primary mission work and damage reduction work in parallel systems exposed to shocks," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    13. Zhang, Qin & Liu, Yu & Xiahou, Tangfan & Huang, Hong-Zhong, 2023. "A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities," Reliability Engineering and System Safety, Elsevier, vol. 235(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. Sheng, Jingyu & Prescott, Darren, 2019. "Using a novel hierarchical coloured Petri net to model and optimise fleet spare inventory, cannibalisation and preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    2. Petchrompo, Sanyapong & Parlikad, Ajith Kumar, 2019. "A review of asset management literature on multi-asset systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 181-201.
    3. Peng, Rui & Wu, Di & Xiao, Hui & Xing, Liudong & Gao, Kaiye, 2019. "Redundancy versus protection for a non-reparable phased-mission system subject to external impacts," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Ayse Sena Eruguz & Tarkan Tan & Geert‐Jan van Houtum, 2017. "Optimizing usage and maintenance decisions for k‐out‐of‐n systems of moving assets," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(5), pages 418-434, August.
    5. Deng, Qichen & Santos, Bruno F., 2022. "Lookahead approximate dynamic programming for stochastic aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 299(3), pages 814-833.
    6. Maher, Stephen J. & Desaulniers, Guy & Soumis, François, 2018. "The daily tail assignment problem under operational uncertainty using look-ahead maintenance constraints," European Journal of Operational Research, Elsevier, vol. 264(2), pages 534-547.
    7. Zhe Liang & Wanpracha Art Chaovalitwongse, 2013. "A Network-Based Model for the Integrated Weekly Aircraft Maintenance Routing and Fleet Assignment Problem," Transportation Science, INFORMS, vol. 47(4), pages 493-507, November.
    8. Sciau, Jean-Baptiste & Goyon, Agathe & Sarazin, Alexandre & Bascans, Jérémy & Prud’homme, Charles & Lorca, Xavier, 2024. "Using constraint programming to address the operational aircraft line maintenance scheduling problem," Journal of Air Transport Management, Elsevier, vol. 115(C).
    9. J.P. Sprong & X. Jiang & H. Polinder, 2020. "Deployment of Prognostics to Optimize Aircraft Maintenance – A Literature Review," Journal of International Business Research and Marketing, Inovatus Services Ltd., vol. 5(4), pages 26-37, May.
    10. Tönissen, D.D. & Arts, J.J., 2020. "The stochastic maintenance location routing allocation problem for rolling stock," International Journal of Production Economics, Elsevier, vol. 230(C).
    11. Denise D. Tönissen & Joachim J. Arts & Zuo-Jun (Max) Shen, 2019. "Maintenance Location Routing for Rolling Stock Under Line and Fleet Planning Uncertainty," Transportation Science, INFORMS, vol. 53(5), pages 1252-1270, September.
    12. Deng, Qichen & Santos, Bruno F. & Curran, Richard, 2020. "A practical dynamic programming based methodology for aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 281(2), pages 256-273.
    13. Tiedo Tinga & Rene Janssen, 2013. "The interplay between deployment and optimal maintenance intervals for complex multi-component systems," Journal of Risk and Reliability, , vol. 227(3), pages 227-240, June.
    14. Liao, Zengbu & Zhan, Keyi & Zhao, Hang & Deng, Yuntao & Geng, Jia & Chen, Xuefeng & Song, Zhiping, 2024. "Addressing class-imbalanced learning in real-time aero-engine gas-path fault diagnosis via feature filtering and mapping," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    15. Carlos Lagos & Felipe Delgado & Mathias A. Klapp, 2020. "Dynamic Optimization for Airline Maintenance Operations," Transportation Science, INFORMS, vol. 54(4), pages 998-1015, July.
    16. Fan, Dongming & Zhang, Aibo & Feng, Qiang & Cai, Baoping & Liu, Yiliu & Ren, Yi, 2021. "Group maintenance optimization of subsea Xmas trees with stochastic dependency," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    17. Fritzsche, R., 2012. "Cost adjustment for single item pooling models using a dynamic failure rate: A calculation for the aircraft industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1065-1079.
    18. Diallo, Claver & Venkatadri, Uday & Khatab, Abdelhakim & Liu, Zhuojun, 2018. "Optimal selective maintenance decisions for large serial k-out-of-n: G systems under imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 234-245.
    19. Rajendran, Suchithra & Srinivas, Sharan, 2020. "Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    20. Nima Safaei & Dragan Banjevic & Andrew Jardine, 2011. "Workforce-constrained maintenance scheduling for military aircraft fleet: a case study," Annals of Operations Research, Springer, vol. 186(1), pages 295-316, June.

    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:189:y:2019:i:c:p:67-88. 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.