Ticari turbofan uçak motorlarının uçuş ömürlerinin optimizasyonu

The primary objective of an airline powerplant engineer responsible from turbofan aircraft engines is to technically manage the engines to be available for revenue flight, while achieving the desired goals of cost of use, reliability and safety, with adequate engine performance level for operational flexibility. For an airline, flight safety is a must. Thus, aviation authorities throughout the world strictly bound the range in which an airline could move to meet the above goals. Since, approximately 40-45% of total aircraft maintenance cost is directly arising from engine maintenance costs, meeting these objectives becomes a very important issue as far as the competitiveness of the airline business is concerned. Under these circumstances, airlines always seek to find and explore methods in order keep the powerplants running with an optimized cost versus on wing life. The engine on wing maintenance concept is known as “on-condition maintenance”. In this concept, engines are continuously monitored during their on wing operation in order to prevent failures and to meet goals on reliability and safety. In other words, engines are kept on wing as long as reliability, safety and performance levels are acceptable. All of the above conditions end up with raising the following important question: What is the time on wing of an aircraft engine that will fulfill all of these goals at the required levels? This question forms the basis of analyzes performed in this study. It is known that there is an optimum time at which engine should have essential restoration done, in order to meet an optimized cost for removal. In other words, at times prior to the optimum one; the opportunity costs which are arising due to repairing an engine before all its useful life is consumed result in an increase in maintenance cost. At times greater than the optimum; the number of parts which need repair, the difficulty and cost of repair and the number of parts which must be scrapped increase. As a result, the maintenance cost increases. In order to search for this optimum, available data is gathered from one airline and analyzed both analytically and statistically. The problem is mathematically modeled by making assumptions, without effecting the accuracy of the real problem. In order to achieve a better understanding, the objectives (maintenance cost, performance, reliability and safety) are studied as sub problems. The data relating these objectives to the engine on wing time are searched and analyzed. For each of these objectives, mathematical expressions are derived. As far as the integrity of the goals of maintenance cost, performance, reliability and safety is concerned, a multi objective optimization problem is proposed. The model is converted into a fitness function form by an airline engineering perspective and multi objective problem of on wing life optimization is solved by using a Genetic Algorithm based solver. Genetic Algorithm method has been selected as being a robust and reliable technique for multi objective engineering optimization problems. Since performance deterioration characteristics end up with three different types of deterioration curves, three sub problems have been solved. This ensured the diversity in terms of actual engine performance deterioration characteristics, which is a result of operational, configurational and manufacturing diversities encountered in the real operation. Performance related diversity is believed to cover the above mentioned facts of the actual problem and enables a better forecast on the optimum on wing life of commercial turbofan aircraft engines. All the results are gathered considering airline engineering priorities and the optimum on wing life of a CFM56-3C1 engine is calculated. A removal planned within this optimum removal interval will achieve all the priorities in terms of minimum maintenance cost, adequate performance, while not sacrificing from reliability and safety. The result of the optimization is compared with the actual removals and found to be in line with the actual removal time frame. This proves the proficiency of proposed method and the mathematical model. Additionally, the operational factors affecting the aircraft engine on wing life is discussed in order to derive a generalized mathematical model for adaptation to other airline engine fleets and to other engine types. Thus, a generaized model is formulated in order to find the optimum time on wing for any type of commercial turbofan engine operated in any fleet.