Analyses data from sensors on manufacturing equipment to predict when a machine will fail, allowing maintenance to be scheduled before the equipment breaks down and production is interrupted.
Analyses data from the supply chain to identify bottlenecks and inefficiencies, leading to improved delivery times and reduced waste.
Optimizes the production plan by considering factors such as raw material availability, equipment capacity, and delivery deadlines. This can lead to improved efficiency and reduced waste.
Automates the optimization of manufacturing processes by continually analysing data from sensors and adjusting parameters to improve efficiency.
Analyses data from quality control sensors to identify patterns and anomalies in the manufacturing process that may indicate a problem. This can lead to improved quality and reduced defects
Creates new designs for parts and products that are optimized for specific performance criteria. This can lead to lighter, stronger, and more efficient designs.