Hello everyone,
We are hosting the session "ML/AI technology in aircraft design, control, manufacture, and inspection" at informs annual 2024.
This session invites researchers, practitioners, and industry experts to share insights, challenges, and advancements in the application of ML/AI technologies across the aerospace lifecycle. Topics of interest include but are not limited to:
Data-driven Design Optimization: Leveraging ML/AI techniques for aerodynamic design optimization, structural analysis, and performance prediction to enhance aircraft efficiency and performance.
Manufacturing Process Optimization: Utilizing ML/AI for process optimization, additive manufacturing, and supply chain management to streamline aircraft production and reduce time-to-market.
Quality Assurance and Inspection: Implementing ML/AI algorithms for automated defect detection, non-destructive testing, and quality control to ensure the safety and reliability of aerospace components.
Predictive Maintenance: Harnessing ML/AI for prognostics and health management (PHM) to predict component failures, optimize maintenance schedules, and minimize downtime for aircraft fleets.
Regulatory Compliance and Certification: Addressing challenges and opportunities in integrating ML/AI technologies into regulatory frameworks and certification processes for aerospace systems.
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Xin Peng
University of California Berkeley
Berkeley CA
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