A multi-agent AI framework using processing and acoustic agents achieves 91.6% accuracy and 0.821 F1 score for in-situ porosity defect detection in wire-arc additive manufacturing.
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A Fire Event Tracker (FET) algorithm performs spatio-temporal clustering on MTG-FCI active fire detections to enable consistent near-real-time and retrospective fire event monitoring.
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In-situ process monitoring for defect detection in wire-arc additive manufacturing: an agentic AI approach
A multi-agent AI framework using processing and acoustic agents achieves 91.6% accuracy and 0.821 F1 score for in-situ porosity defect detection in wire-arc additive manufacturing.
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Leveraging MTG-FCI fire observations for event-based fire behavior monitoring from near-real-time operation to seasonal analysis
A Fire Event Tracker (FET) algorithm performs spatio-temporal clustering on MTG-FCI active fire detections to enable consistent near-real-time and retrospective fire event monitoring.