OperationsOwn ModelsHigh complexity
Process Optimisation Models
Find the best settings for each process from the plant's own historical data.
How we approach it
Models trained on years of process and quality data recommend setpoints for yield, energy and quality. Recommendations stay within engineering limits, operators approve each change, and results are tracked against what the model predicted.
Business value
Higher yield and lower energy use
Technology stack
- Historian data
- ML models
- optimisation
- operator interface
Related service
Proprietary AI DevelopmentRelated use cases
- Manufacturing · OperationsPredictive MaintenancePredict equipment failures from sensor data before they stop the line.
- Manufacturing · OperationsProduction SchedulingRebuild production schedules quickly when orders, materials or machines change.
- Manufacturing · OperationsSupply Chain VisibilitySee inventory, shipments and supplier risk across tiers, and meet new EU product data duties from the same data.