A graph attention-based virtual metrology framework predicts film thickness from sensor traces by representing step-parameter pairs as nodes and using attention to capture parameter-to-layer dependencies.
Directly from Surface to Bulk: Rapid Prediction of Internal Densification in Laser Powder Bed Fusion Additively Manufactured Nickel -Based S uperalloy Using Machine Learning
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An ontology-augmented LLM system for LPBF defect diagnosis and mitigation guidance reaches 0.808 macro F1 and substantial Cohen's kappa agreement on a literature-derived test set.
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A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion
An ontology-augmented LLM system for LPBF defect diagnosis and mitigation guidance reaches 0.808 macro F1 and substantial Cohen's kappa agreement on a literature-derived test set.