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AI-Driven EoL Aircraft Treatment: A Research Perspective

  • Ashkan Amirnia,
  • Samira Keivanpour

摘要

End-of-life (EoL) aircraft treatment is a crucial step in the circular manufacturing of the aircraft industry, delivering considerable economic and environmental benefits. Despite these advantages, complex and sensitive operations are a serious challenge in this field due to the high complexity of an aircraft structure and its constituent materials and composites. Poor operations can significantly reduce output quality and increase operational costs. Consequently, the value of the recovered materials may not exceed the operational costs. Artificial intelligence (AI) is a valuable tool for enhancing the effectiveness and sustainability of EoL aircraft management by automating and optimizing the identification, separation, processing, and transformation of materials. AI can also help to reduce waste and emissions, increase material recovery and reuse, and create new markets and jobs. This paper comprehensively reviews the AI applications in EoL aircraft treatment. It discusses the current state-of-the-art AI models across three domains: recycling, maintenance, and dismantling/disassembly. This article then carefully highlights the existing gaps based on the analyses. It also describes the possible directions of future research.