AI Research
Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems
As Industry 4.0 accelerates the integration of Cyber-Physical Systems (CPS) in manufacturing, robust anomaly detection has become critical for ensuring process safety and security. Current data-driven approaches typically employ "product-agnostic" or global models trained on the ...
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ArXiv CS.AI
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ArXiv CS.AI
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For multi-product manufacturing, generic anomaly detection models can mask subtle issues or attacks by averaging across product variations. A product-aware approach provides targeted monitoring, significantly improving security and reliability in flexible industrial settings.
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