Abstract
We developed a model that integrates fuzzy logic, the analytic hierarchy process (AHP), and quality function deployment (QFD) to evaluate the importance weighting of the technical factors in aviation safety, as defined by the International Air Transport Association. AHP evaluates the technical factors using pairwise comparisons, and QFD categorizes the relationship between the criteria and subcriteria using expert knowledge. Based on a questionnaire given to aviation professionals, the model shows that the importance weightings of technical factors “Extensive engine failure, uncontained engine fire,” “Design, manufacture,” and “Engine overheat, propeller failure” are most significant. The result also shows that the over-valued and/or under-valued factors predicted by the conventional AHP model can be better described by the integrated fuzzy AHP and QFD models.









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Boeing (2009) Accident rates and onboard fatalities by year. Statistical summary of commercial jet airplane accidents, p 18
Braithwaite GR, Caves RE, Faulkner JPE (1998) Australian aviation safety—observations from the ‘lucky’ country. J Air Transp Manag 4:55–62
Gill GK, Shergill GS (2004) Perceptions of safety management and safety culture in the aviation industry in New Zealand. J Air Transp Manag 10:233–239
McFadden KL, Towell ER (1999) Aviation human factors: a framework for the new millennium. J Air Transp Manag 5:177–184
Chen CC, Chen J, Lin PC (2009) Identification of significant threats and errors affecting aviation safety in Taiwan using the analytical hierarchy process. J Air Transp Manag 15:261–263
Liou JJH, Tzeng GH, Chang HC (2007) Airline safety measurement using a hybrid model. J Air Transp Manag 13(4):243–249
Netjasov F, Janic M (2008) A review of research on risk and safety modelling in civil aviation. J Air Transp Manag 14:213–220
Yang TH, Yan S, Chen HH (2003) An airline maintenance manpower planning model with flexible strategies. J Air Transp Manag 9:233–239
Wiegmann D, Shappell S (2003) A human error approach to aviation accident analysis: the human factors analysis and classification system. Ashgate, Aldershot
Edwards E (1972) Man and machine: systems for safety. In: The BALPA technical symposium, London
Heinrich HW (1931) Industrial accident prevention. McGraw-Hill Insurance Series, USA
Reason J (1990) Human error. Cambridge University Press, England
Herrera IA, Nordskag AO, Myhre G, Halvorsen K (2009) Aviation safety and maintenance under major organizational changes, investigating non-existing accidents. Accid Anal Prev 41:1155–1163
IATA (2007) IATA’s accident classification system. IATA Safety Report, Annex 1, A1, pp 67–71
Steuer RE, Na P (2003) Multiple criteria decision making combined with finance: a categorized bibliographic study. Eur J Oper Res 150(3):496–515
Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29
Ho W (2008) Integrated analytic hierarchy process and its applications—a literature review. Eur J Oper Res 186(1):211–228
Ho W, Xu X, Dey PK (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202(1):16–24
Bhattacharya A, Geraghty J, Young P (2010) Supplier selection paradigm: an integrated hierarchical QFD methodology under multiple-criteria environment. Appl Soft Comput 10(4):1013–1027
Ho W, He T, Lee CKM, Emrouznejad A (2012) Strategic logistics outsourcing: an integrated QFD and fuzzy AHP approach. Expert Syst Appl 39:10841–10850
Myint S (2003) A framework of an intelligent quality function deployment (IQFD) for discrete assembly environment. Comput Ind Eng 45(2):269–283
Lin YH, Cheng HP, Tseng ML, Tsai CC (2010) Using QFD and ANP to analyze the environmental production requirements in linguistic preferences. Expert Syst Appl 37(3):2186–2196
Wang YM, Chin KS (2011) Technical importance ratings in fuzzy QFD by integrating fuzzy normalization and fuzzy weighted average. Comput Math Appl 62(11):4207–4221
Bhattacharya A, Sarkar B, Mukherjee SK (2005) Integrating AHP with QFD for robot selection under requirement perspective. Int J Prod Res 43(17):3671–3685
Partovi FY (2006) An analytic model for locating facilities strategically. Int J Manag Sci Omega 34(1):41–55
Hanumaiah N, Ravi B, Mukherjee NP (2006) Rapid hard tooling process selection using QFD–AHP methodology. J Manuf Technol Manag 17(3):332–350
Cheung A, Ip WH, Lu D (2005) Expert system for aircraft maintenance services industry. J Qual Maint Eng 11(4):348–358
Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26
Xue Z, Xiao Y, Liu W, Cheng H, Li Y (2012) Intuitionistic fuzzy filter theory of BL-algebras. Int J Mach Learn Cybern. doi:10.1007/s13042-012-0130-8
Katagiri H, Uno T, Kato K, Tsuda H, Tsubaki H (2012) Random fuzzy bilevel linear programming through possibility-based value at risk model. Int J Mach Learn Cybern. doi:10.1007/s13042-012-0126-4
Wang X, Chen A, Feng H (2011) Upper integral network with extreme learning mechanism. Neurocomputing 74(16):2520–2525
Wang X, Fang SF, Zhai JH (2007) A nonlinear integral defined on partition and its application to decision trees. Soft Comput 11(4):317–321
Cheng CH, Mon DL (1994) Evaluating weapon system by analytic hierarchy process based on fuzzy scales. Fuzzy Sets Syst 63:1–10
Shillito ML (1994) Advanced QFD. Wiley, USA
Saaty TL (1996) Decision making with dependence and feedback: the analytic network process. RWS, Pittsburgh
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Appendix: Questionnaire of assessing the technical factors in aviation safety
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Chen, CJ., Yang, SM. & Chang, SC. A model integrating fuzzy AHP with QFD for assessing technical factors in aviation safety. Int. J. Mach. Learn. & Cyber. 5, 761–774 (2014). https://doi.org/10.1007/s13042-013-0169-1
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DOI: https://doi.org/10.1007/s13042-013-0169-1