A hybrid type-2 fuzzy based supplier performance evaluation methodology: The Turkish Airlines technic case

In the globalized world, fatal competition ruling in almost all business sectors hits especially airline companies due to the global nature of the industry. Thus, maintaining the business operations in a cost-effective manner is of paramount importance in this destructive business environment. While realizing this goal, a special focus on Maintenance Repair and Overhaul (MRO) operations is indispensable, considering that a significant proportion of expenses in the industry are originated from them. Since the MRO departments are responsible for maintenance, repair, and overhaul of aircrafts and engines under very strict standards, a smooth, clean-cut supply chain does not only provide a solid technical ground for daily operations but also it helps to gain a comparative advantage in cost leadership which, in turn, results with high customer satisfaction. Obviously, a key component of this chain is designing a robust and reliable Supplier Performance Evaluation (SPE) methodology where numerous tangible and intangible evaluation criteria come into play reflecting the multifaceted characteristic of the decision problem. This work proposes a three-phase hybrid approach to address the SPE problem in aviation industry where the suppliers are obliged to follow tight tolerances regarding quality and delivery times. Starting with selection of the most significant evaluation criteria, in the second stage, an Interval Type-2 Fuzzy (IT2F)-Analytic Hierarchy Process (AHP) is employed to determine their relative importance. These weights are then given as input to an IT2F-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. We used the IT2F extensions due to the fact that some of the evaluation criteria are subjective and qualitative in nature. To prove the merit of the proposed methodology, an application is presented to SPE problem at Turkish Technic Inc., a subsidiary of Turkish Airlines. (C) 2017 Elsevier B.V. All rights reserved.