TY - JOUR
T1 - A model integrating fuzzy AHP with QFD for assessing technical factors in aviation safety
AU - Chen, Chuen Jyh
AU - Yang, Shih Ming
AU - Chang, Shih Chuan
N1 - Publisher Copyright:
© 2013, Springer-Verlag Berlin Heidelberg.
PY - 2014/10
Y1 - 2014/10
N2 - 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.
AB - 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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U2 - 10.1007/s13042-013-0169-1
DO - 10.1007/s13042-013-0169-1
M3 - Article
AN - SCOPUS:84919913659
SN - 1868-8071
VL - 5
SP - 761
EP - 774
JO - International Journal of Machine Learning and Cybernetics
JF - International Journal of Machine Learning and Cybernetics
IS - 5
ER -