Abstract—Failure mode and effects analysis (FMEA) is used
commonly for the prioritization of failures in the automotive
production. Traditional FMEA determines the risk priorities of
failure modes, which require the risk factors like the occurrence
(O), severity (S) and detection (D) of each failure mode to be
evaluated. However, it has some drawbacks so that affect the
risk evaluation and correction action. It is very difficult for
three risk factors to be evaluated precisely. Additionally,
traditional method cannot capture different team members’
opinions and prioritize failure modes under different types of
uncertainties. So, in this study, FMEA using fuzzy evidential
approach and grey theory are used to prioritize the failures for
a truck production company in Turkey. Degrees of relation for
the six failure modes are determined. The defect of “unstable” is
found as the most important and serious risk according to the
Index Terms—Automotive production, failure mode and effects analysis (FMEA), fuzzy evidential approach, grey theory, risk prioritization.
The authors are with the Istanbul Technical University, Industrial Engineering Department Macka 34367 Istanbul, Turkey (e-mail: email@example.com, firstname.lastname@example.org).
Cite: Mehmet Turgut and Alp Ustundag, "A Hybrid Risk Evaluation Model for Automotive Production," International Journal of Machine Learning and Computing vol. 4, no. 5, pp. 458-462, 2014.