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Improving Maintenance Decision Making in the Finnish Air Force Through Simulation

Author

Listed:
  • Ville Mattila

    (Systems Analysis Laboratory, Helsinki University of Technology, FIN-02015 HUT, Finland)

  • Kai Virtanen

    (Systems Analysis Laboratory, Helsinki University of Technology, FIN-02015 HUT, Finland)

  • Tuomas Raivio

    (Gaia Consulting Oy, Systems Analysis Laboratory, Helsinki University of Technology, FIN-02015 HUT, Finland)

Abstract

We used discrete-event simulation to model the maintenance of fighter aircraft and improve maintenance-related decision making within the Finnish Air Force. We implemented the simulation model as a stand-alone tool that maintenance designers could use independently. The model has helped the designers to study the impact of maintenance resources, policies, and operating conditions on aircraft availability. It has also enabled the Finnish Air Force to advance the operational capability of its aircraft fleet. We designed the model to simulate both normal and conflict operating conditions. The main challenge of the project was the scarcity and confidentiality of data about the fighter aircraft, their maintenance, and various operational scenarios, especially during conflict situations.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:orinte:v:38:y:2008:i:3:p:187-201
    DOI: 10.1287/inte.1080.0349
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    Citations

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    Cited by:

    1. Gavranis, Andreas & Kozanidis, George, 2015. "An exact solution algorithm for maximizing the fleet availability of a unit of aircraft subject to flight and maintenance requirements," European Journal of Operational Research, Elsevier, vol. 242(2), pages 631-643.
    2. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints," European Journal of Operational Research, Elsevier, vol. 246(2), pages 661-673.
    3. George Kozanidis & Andreas Gavranis & Eftychia Kostarelou, 2012. "Mixed integer least squares optimization for flight and maintenance planning of mission aircraft," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(3‐4), pages 212-229, April.
    4. 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.
    5. Poropudas, Jirka & Virtanen, Kai, 2011. "Simulation metamodeling with dynamic Bayesian networks," European Journal of Operational Research, Elsevier, vol. 214(3), pages 644-655, November.
    6. George Kozanidis & Andreas Gavranis & George Liberopoulos, 2014. "Heuristics for flight and maintenance planning of mission aircraft," Annals of Operations Research, Springer, vol. 221(1), pages 211-238, October.

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