Konya Technical University (KTUN) has implemented a project that will make a significant contribution to the aviation industry of the country. The project titled “ADLOG (Analysis of Logistics Maintenance Data)", carried out by Prof. Dr. Harun Uğuz, Faculty Member of the Department of Computer Engineering, Faculty of Engineering and Natural Sciences, within the scope of the Researcher Training Program for the Defence Industry (SAYP), has been completed. Thanks to the project, by using artificial intelligence techniques, the operating life of aircraft equipment will be increased; safe and high-reliability flight will be provided.
Konya Technical University Faculty of Engineering and Natural Sciences Department of Computer Engineering faculty member Prof. Dr. Harun Uğuz, who has been working on this subject for two years, has successfully completed the first project of the university within the scope of the Researcher Training Program for the Defence Industry (SAYP) - Category-C. The project named ADLOG (Analysis of Logistics Maintenance Data) whose stakeholders are the Presidency of Defence Industries (SSB), Air Electronics Industry and Trade Inc. (HAVELSAN) will lay the groundwork for safe and highly reliable flight by performing artificial intelligence techniques of aircraft maintenance periods and MTBF (Mean Time Between Failure and NFF (No Fault Found)) analysis of aircraft equipment, analysing the records of aircraft equipment with the developed data pre-processing techniques, estimating the number of failures with artificial intelligence and optimization algorithms.
Prof. Dr. Harun Uğuz stated, “The aviation sector has built up a large amount of data and information. Many data are kept in database management systems in this sector, including maintenance plans, failure notifications, repair orders, equipment removal/installation records, and flying hours. These data may be turned into information using statistical and mathematical methods, and artificial intelligence and machine learning-based techniques can be used to make massive volumes of complex data intelligible. The most basic feature of artificial intelligence techniques is that they learn events or problems based on current information and make decisions by creating solutions for subsequent scenarios while producing solutions to events and problems without the requirement for human interpretation.”
Uğuz continued as follows: “With the project outputs, this project aims to reduce unplanned assembly and disassembly, to reduce unexpected failures, to cancel unnecessary maintenance, to arrange maintenance periods efficiently, to measure the effectiveness of the applied maintenance and to reduce the maintenance cost, and the results to be obtained were made available by engineers for insights on inspection in workshops, maintenance units, maintenance planning change, material requirement planning, etc.”
Expressing his satisfaction with the successful completion of the project, Prof. Dr. Harun Uğuz said, “In accordance with the maintenance standards of aircraft material and equipment manufacturers, each material or equipment must have a certain maintenance period and flight life, but due to factors such as external factors such as mission conditions, climatic conditions and the inability to determine preventive maintenance periods appropriately, materials and equipment are deprived of their flight life. It may malfunction in shorter periods, and the maintenance periods in the manufacturer's catalogue may vary. In this context, it is extremely important that the preventive maintenance planning is carried out under the conditions of our country, which will ensure that the aircraft equipment is in working condition, long working life, high flight safety and reliability, while helping to reduce labour and maintenance costs. We are proud to have successfully completed our project, which we carried out in line with these aims. I hope it will be beneficial for our country, university and aviation industry.”
Prof. Dr. Harun Uğuz also said they have completed a doctoral thesis titled "Predicting Aircraft Maintenance Periods and Failure Counts through Artificial Intelligence Techniques" within the scope of the project, together with Kadir Çelikmıh, PhD student of Konya Technical University Graduate Education Institute Computer Engineering Department, and 1 SCI indexed article and an international conference presentation have been made.