Optimization of Interval Tasks for Civil Aircraft with Hidden Non-Safety Failures

This study focuses on optimizing maintenance activities for civil aircraft, with a specific emphasis on identifying and addressing hidden non-safety failures. The study investigates the development and application of mathematical models to optimize maintenance policies, with the goal of enhancing the overall efficiency and reliability of aircraft operations. We optimize maintenance tasks by gathering comprehensive maintenance data from multiple sources, such as routine and non-routine cards, and converting this data into life data for analysis. The Weibull distribution is used as the main model in our reliability research to determine the duration to failure and operational lifespan of aircraft components. A case study is presented to illustrate the actual application of our optimization methods. Using empirical data extracted from airplane maintenance logs and inspection reports, we detect Maintenance Significant Items (MSIs) and build a systematic analytical method for classifying repair tasks according to their safety, operational, and economic consequences. The case study demonstrates the effectiveness of our optimization framework in minimizing repair costs and enhancing the reliability of the aircraft's operational system. The results demonstrate that the suggested optimization models and approaches have the potential to greatly improve maintenance scheduling, ultimately resulting in reliable aircraft operations. This study enhances the field of aviation maintenance by presenting a comprehensive framework for improving maintenance chores and assuring the ongoing safety and efficiency of civil aircraft.