Ammar I. Shihab1, Ali H. Kashmar2, Sarmad Abdullatef3.and Wafaa Sabah Jawad4
1,2University of Baghdad, College of Science, Computer Science Dept.
3Ministry of transportation, Iraqi air fortunes. Republic of Iraq
4Ministry of Higher Education and Scientific Research, Republic of Iraq.
Email: [email protected]
DOI: 10.23918/ICABEP2022p58
Abstract
The goal of the following protocol is to provide methodological representation to optimize and prediction of unscheduling and scheduling maintenance in the Iraqi airway system using smart technology.
Aircraft maintenance is an important part of safety. With the rapid development of technology, the growth of maintenance data, and a large number of flights, the development of maintenance programs shows initial to make them more flexible, smooth, easy, and safe in order to meet the requirements of airports in the whole world. Modern maintenance programs can be created according to organized conditions (camo) and developed from them using prediction models, classification, or deep learning using SVM. These methods help, for example, in determining the methods available for aircraft maintenance and repair, or in predicting maintenance schedules. The system which has been created can be able to overcome problems in the best way and move from the ordinary system to the smart system in managing based on smart technologies used.
Therefore, this study provides a powerful maintenance system based on MySQL and PHP databases, which aims to build high-security sites, and also uses the prediction algorithm in (SVM) to predict unscheduling and scheduling maintenance in the aircraft. Maintenance of journey schedule if maintenance occurs or not, whether it is scheduled or unscheduled maintenance.
The data of the Iraqi Airways B.737-800 REG was studied. YI-AST The data was from the year 2015-2019, and the number of flights was approximately 6,400 round trips. The algorithm was applied in the Iraqi airway, trained on this data, tested and predicted on 269 extracted from the basic data, and obtained high accuracy in prediction in that it was similar to the values that occurred in the real world.
In conclusion, the site maintained aircraft systems that are highly efficient in entering and exiting data and performing calculations without problems and gives the best prediction for unscheduling maintenance in calculating and storing in dealing with sections and eliminating the use of paper, which is a very high cost for a large amount of data for aircraft, unlike the ordinary system that was complaining of these problems. and forecasting the aircraft maintenance schedule and unscheduling.
Keyword: prediction, unscheduling system, Aircraft management system, SVM
ICABEP2022
4th International Conference on Accounting, Business, Economics and Politics
Organized by
Tishk International University, College of Administration and Economics, Salahaddin University-Erbil, and
University of Szczecin, Poland.
