A novel hybrid MCDM model based on fuzzy AHP and fuzzy TOPSIS for the most affected gas turbine component selection by the failures

Abstract

Gas turbines are usually the core elements of numerous mechanical systems. Subsequent to the advancement of high efficiency and clean energy, gas turbine has a significantly growing role in different areas, such as aviation and marine propulsion systems, electric power stations, and natural gas and petroleum transportation. However, gas turbines are decisive in operating many industrial plants, and their accompanying maintenance costs are likely to be exceedingly high. A number of failures in the gas turbine components have been detailed and discussed in this paper, with a view to thwarting future breakdowns by suggesting specification for notable maintenance and utilisation of gas turbine components. This study puts forward Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods applied in failure detection of gas turbine components. This paper attempts to handle gas turbine components, which contain hydraulic-pneumatic equipment, electronic control equipment, and bearing equipment. Thanks to the assessment of specialists, heavily influenced by failures, gas turbine components have been decided. The results have proved the bearing equipment to have been the most effective alternative, as being ensued by hydraulic-pneumatic equipment and electronic control equipment.