Proactive Anomaly Mitigation in Industrial Processes using a Deep Learning-Driven Predictive Controller with Integrated Sensor Fusion and Temporal Forecasting
Contemporary manufacturing environments are subject to multifaceted process disturbances that culminate in quality deterioration, unscheduled downtime, and elevated operational costs. Reactive control architectures, which respond to anomalies after their manifestation, are fundamentally inadequate for processes demandi...