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Cost evaluation of airline maintenance investigation-triggering methods

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  • Melody Dai
  • Kuan-Hsun Chen

Abstract

A reliable investigation-triggering mechanism is critical for airlines in managing aircraft fleet reliability. This study developed a simulation model to evaluate the performance of various investigation-triggering mechanisms in various scenarios of aircraft fleet reliability. Factors that affect performance include flight delay costs, investigation costs, the costs of corrective actions, the accuracy of investigations, the effectiveness of corrective actions, and the monthly improvement rate. Nine investigation-triggering mechanisms were evaluated. The simulation results show that the monthly improvement rate significantly influences performance. The subject airline’s original investigation-triggering mechanism is not outstanding in most scenarios. This study recommends two of the nine investigation-triggering mechanisms for airlines when they select investigation-triggering mechanisms in various scenarios. Thus, useful guidance for adjusting airlines’ investigation-triggering mechanisms can be effectively provided. Copyright Sociedad de Estadística e Investigación Operativa 2014

Suggested Citation

  • Melody Dai & Kuan-Hsun Chen, 2014. "Cost evaluation of airline maintenance investigation-triggering methods," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 950-975, October.
    • Handle: RePEc:spr:topjnl:v:22:y:2014:i:3:p:950-975
    DOI: 10.1007/s11750-013-0306-8
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    References listed on IDEAS

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    1. Wu, Cheng-Lung & Caves, Robert E, 2000. "Aircraft operational costs and turnaround efficiency at airports," Journal of Air Transport Management, Elsevier, vol. 6(4), pages 201-208.
    2. C. Lovell & J. Pastor, 1994. "The contribution of operations research techniques to the evaluation of electric utility performance," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(1), pages 167-173, June.
    3. J. Román Ubeda & R. Allan, 1994. "Stochastic Simulation and Monte Carlo methods applied to the assessment of hydro-thermal generating system operation," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(1), pages 1-23, June.
    4. 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.
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    Cited by:

    1. Maxim Finkelstein & Ji Hwan Cha & Shyamal Ghosh, 2021. "Optimal inspection for missions with a possibility of abortion or switching to a lighter regime," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 722-740, October.
    2. Ji Hwan Cha & Maxim Finkelstein, 2019. "Optimal preventive maintenance for systems having a continuous output and operating in a random environment," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 327-350, July.

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