Affiliations: [a] Department of Airframe and Powerplant Maintenance, Faculty of Aeronautics and Astronautics, Eskisehir Technical University, Eskisehir, Turkey
| [b] Department of Industrial Engineering, Faculty of Engineering, Atatürk University, Erzurum, Turkey
Correspondence:
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Address for correspondence: Elif Kılıç Delice, Department of Industrial Engineering, Faculty of Engineering, Atatürk University, Erzurum, Turkey. E-mail: elif.kdelice@atauni.edu.tr.
Abstract: BACKGROUND:Aircraft maintenance technicians (AMTs) have the most difficulty in terms of total workload criteria working in line maintenance. This is a very important problem for the Aircraft Maintenance Organization. A systematic and scientific approach is required for its solution. OBJECTIVE:This study proposes a new Multi-Criteria Decision Making (MCDM) based approach to evaluating the total workloads of AMTs to identify the most challenging AMT tasks in the aircraft maintenance organization. METHODS:A new hybrid MCDM approach is proposed by integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Preference by Similarity (TOPSIS) methods to compare AMTs on the basis of workloads according to license categories. The hybrid method proposed in this study evaluates the total workload under three main titles: mental, physical, and environmental workload. RESULTS:Focusing on AMTs working in line maintenance of an aircraft maintenance organization, this study revealed that the most important workload criteria determined by the DEMATEL method are lower back strain, upper back strain, time pressure, and air temperature criteria. The results of the TOPSIS method showed that the license categories of AMTs are sorted according to the workloads as follows: A, B2, B1, and B1 + B2. The AMTs holding a “Category A” license have fewer workloads than the other categories. CONCLUSION:The findings of the study reveal some measures that might allow authorities to minimize the workload of AMTs. In addition, the study contributes to the literature because there are few studies that systematically analyze total workloads by using MCDM methods.
