An aviation management requires safety and dependability during flight which are ensured through routine inspections, repairs, and replacements of its parts, systems, and structures. It is a crucial component of aviation safety since even little flaws or faults can have detrimental effects when an aircraft is in the air. Artificial intelligence (AI) has become more prevalent in aviation management to increase efficiency, improve safety, and save costs. AI applications encompass maintenance planning, condition monitoring, troubleshooting, robotic maintenance, adaptive spare parts management, natural language processing (NLP) for documentation, and augmented reality (AR) for maintenance support. Proactive maintenance, continuous surveillance, fast troubleshooting, automated chores, optimised spare parts management, easy access to information, and improved assistance for personnel are all possible with these technologies. AI applications in aviation maintenance help identify potential equipment failures, predict maintenance issues, and enable proactive maintenance interventions. This improves safety by reducing the risk of unexpected breakdowns or failures, ensuring the reliability and airworthiness of aircraft systems. AI-driven predictive maintenance and condition monitoring systems optimize maintenance schedules, reducing unscheduled downtime and maximizing aircraft availability. By automating routine tasks, AI also enhances operational efficiency and reduces human error. The aviation sector hopes to improve maintenance operations and assure aircraft reliability and availability by embracing AI, while minimizing downtime and enhancing overall maintenance processes. Grey relational analysis used in conjunction with statistical regression analysis to examine relationships between sequences while using less data and various parameters. In this study Artificial Intelligence methods are analysed using Grey relationship analysis method for Aviation Management.


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    Title :

    Application of Grey Relational Analysis for Utilizing Artificial Intelligence Methods in Aviation Management


    Additional title:

    Studies in Systems, Decision and Control




    Publication date :

    2024-02-20


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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