Volume List  / Volume 6 (1)



DOI: 10.7708/ijtte.2016.6(1).08

6 / 1 / 92-103 Pages


Akinyemi Olasunkanmi Oriola - Mechanical Engineering Department, Olabisi Onabanjo University, Ago-Iwoye, Nigeria -

Adebiyi Kazeem Adekunle - Mechanical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria -


This research proposes an improved model for estimating runway accident cost in the aviation industry in Nigeria. Bayesian Network was used to model the probability of consequences of runway accidents and subsequently the cost of the potential consequences. The Bayesian Network was also used to implement causal and diagnostic inference. Market interest rate which incorporates the effect of inflation was included to relax the assumption of constant economic value. The three classes of consequences of runway accidents identified in this study were fatal, serious, and minor. Domain experts were used to obtain relevant Bayesian causes and evidences related to the occurrence of consequence of runway accident. A mathematical equation was developed to solve the Bayesian Network influence diagram to obtain the probability of minor runway accident, serious runway accident and fatal runway accident as 0.7603, 0.1547 and 0.0850 respectively. Consequently, the estimated cost of runway accident (minor, serious and fatal) was $23, 813.52, $20, 052.64 and $772, 856.06 respectively. The Bayesian Network diagnostic inference reveals the close relation of runway accidents in Nigeria aviation sector with aircraft system failure, approach/takeoff procedures, human factors, weather conditions and collision risk.

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