Detects machine failure risks using IoT and sensor data.
Reduces downtime and maintenance costs.
Automated defect detection using computer vision.
Improves quality control and reduces waste.
Predicts inventory needs with past sales and seasonality.
Prevents stockouts and overstocking.
Uses AI to allocate resources efficiently in production lines.
Improves throughput and OEE.
Monitors real-time energy usage for optimization.
Reduces utility costs and carbon footprint.
Detects disruptions using external signals.
Improves resilience and agility.
AI detects abnormal patterns in real-time operations.
Enhances operator safety and compliance.
Simulates factory floor for testing process changes.
Reduces trial-and-error cost of optimization.