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.
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References
Berenson ML, Levine DM, Krehbiel TC et al (2002) Basic business statistics. Prentice-Hall International Inc, New Jersey
Federal Aviation Administration (1978) Maintenance control by reliability methods, advisory circular AC 120-17A. U.S. Department of Transportation
Friend CF (1997) Aircraft maintenance management. Addison Wesley Longman Limited, England, p 57
Hillier FS, Lieberman G.J (2010) Introduction to operations research, International edn. McGraw-Hill Companies Inc, New York, pp 1084–1175
International Civil Aviation Organization (2001) Operation of aircraft part I international commercial air transport—Aeroplanes, 11.3 Maintenance programme, Annex 6 to the Convention on International Civil Aviation, 8th edn
Kinnison HA (2004) Aviation maintenance management. McGraw-Hill Companies Inc, New York, p 206
Lovell CAK, Pastor JT (1994) The contribution of operations research techniques to the evaluation of electric utility performance. TOP 2(1):167–173
Moretti S, Patrone F (2008) Transversality of the Shapley value. TOP 16:1–41
Ören TI (1994) Artificial intelligence in simulation. Ann Oper Res 53:287–319
Safaei N, Banjevic D, Jardine AKS (2011) Workforce-constrained maintenance scheduling for military aircraft fleet: a case study. Ann Oper Res 186:295–316
Ubeda JR, Allan RN (1994) Stochastic simulation and Monte Carlo methods applied to the assessment of hydro-thermal generating system operation. TOP 2(1):1–24
Wu C-L, Caves RE (2000) Aircraft operational costs and turnaround efficiency at airports. J Air Transpl Manag 6(4):201–208
Acknowledgments
The authors are grateful for and acknowledge the provision of technical data by an airline that wishes to remain anonymous. The authors also thank anonymous referees of this journal for their valuable comments.
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Dai, M.DM., Chen, KH. Cost evaluation of airline maintenance investigation-triggering methods. TOP 22, 950–975 (2014). https://doi.org/10.1007/s11750-013-0306-8
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DOI: https://doi.org/10.1007/s11750-013-0306-8