Effects of Aviation Maintenance-Related Flight Incidents on Air Traffic in the National Air Space System

National Airspace System (NAS) is a highly aviation complex network managed by the Federal Aviation Administration (FAA), which oversees over 45,000 flights daily. Incidents within the NAS can lead to numerous flight deviations, significantly disrupting air traffic flow. In 2021, the International Air Transportation Association (IATA) indicated maintenance errors as latent factors in 35% of aircraft accidents [1]. Malfunctions in any component of an aircraft can have far-reaching consequences. These errors not only compromise aviation safety but also affect air navigation services. Accurately predicting aviation maintenance-related incidents is key to managing changes and mitigating risks in air traffic systems.Predominantly, human errors are recognized as primary contributors to aviation maintenance-related incidents. While extensive research has focused on human factors, the role of flight characteristics in predicting such incidents remains underexplored. This research aims to fill this gap by shifting the focus from a human-centric approach to an analysis based on flight characteristics. The study has two main objectives: (1) to analyze the impact of aviation maintenance-related incidents on NAS air traffic and (2) to predict the types of these incidents based on the perspective of flight characteristics.Utilizing the National Aeronautics and Space Administration (NASA) Aviation Safety Reporting System (ASRS) dataset, a predictive model is developed using flight characteristics as primary predictors. This model employs logistic regression to examine the correlation between specific flight variables – such as flight phase, aircraft manufacturer, lighting conditions, and time of day– and the types of maintenance-related incidents.This study’s uniqueness lies in its detailed analysis of these factors within the ASRS dataset, a facet not extensively explored in current literature. Its findings are particularly pertinent to air traffic and traffic management, offering insights for the development of models that preempt maintenance-related flight deviations. Such proactive strategies can enhance air traffic management by minimizing disruptions and optimizing flight schedules.Further, the research findings, which indicate the intricate relationships between various flight characteristics and maintenance-related incidents, enable the FAA to make more informed decisions in traffic management. Identifying high-risk phases or times could better prepare air traffic controllers, leading to more efficient traffic handling and improved safety.In conclusion, this study contributes to the existing body of knowledge in air traffic management and aviation safety by offering a focused examination of factors influencing maintenance-related incidents. Its findings hold the potential to provide actionable insights for aviation professionals, thereby fostering a safer and more efficient airspace.