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公式動画＆関連する動画 [Manufacturing AI: Production Incident Response Demo]
See how Oracle's AI Data Platform helps manufacturers detect production defects, assess operational risk, and recommend corrective actions that reduce downtime and protect delivery schedules. Explore how Oracle's AI Data Platform supports faster manufacturing decisions with governed data, AI agents, and machine learning at https://social.ora.cl/6004BDLzQe
See how Oracle's AI Data Platform helps manufacturers respond to production incidents with coordinated AI. In this demonstration, a production supervisor receives an alert when defect rates on a manufacturing line exceed acceptable limits. Instead of manually reviewing multiple dashboards, an AI agent identifies the affected machine, analyzes operational risk, reviews inspection data, and quantifies potential business impact. The platform evaluates response options and recommends corrective actions that eliminate production delays while addressing the root cause of the issue.
The demonstration also shows how Oracle brings together structured and unstructured enterprise data through an AI Lakehouse architecture and Medallion data pipelines. Spark notebooks and data pipelines support large-scale data engineering, while machine learning models managed with MLflow generate predictive insights and real-time risk scoring. Foundation agents use retrieval-augmented generation with governed enterprise context to explain risks and recommend operational actions. Git integration, bundle features, and Credential Store simplify deployment across manufacturing facilities while maintaining secure collaboration. Together, these capabilities help manufacturers turn operational signals into trusted, real-time decisions that improve quality, reduce downtime, and support continuous operations.
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