Process parameter optimisation
Control reactors and plants at their optimum.
Process parameter optimisation uses historical and real-time data to continuously adjust temperature, pressure, throughput and dosing to the current product, improving both quality and throughput.
- Higher quality
- Higher efficiency
- Cost reduction
throughput
scrap
payback
energy efficiency
Calculated from additional output, reduced scrap and energy savings.
- 01
Data integration
Consolidate data from ERP, MES and further sources for Process parameter optimisation.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the Process parameter optimisation model on historical data.
- 04
Pilot
Pilot Process parameter optimisation in one area and collect feedback.
- 05
Rollout
Scale the solution and integrate it into operational processes.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
Sensor data
Real-time IoT and process sensors.
Historian data
Time series from the process control level.
MES data
Production orders, feedback and machine data.
Recipe data
Ingredients, quantities, allergens and work instructions.
Quality data
Inspection results, lab values and complaints.
Energy consumption
Electricity, gas, water and steam per area.
Production manager
Uses insights directly in daily operations.
Quality management
Secures compliance with standards and regulations.
Sustainability lead
Captures and communicates sustainability metrics.
Controlling
Quantifies effects and supports budgeting.
Higher quality
Higher efficiency
Cost reduction
Better sustainability balance
Higher margins
With a solid data foundation this use case gets faster, cheaper and far more stable.
Central data platform
Real-time data integration
Scalable analytics pipelines
Reusable data products
Predictive quality
Same data reveals quality deviations.
Energy optimisation
Process data enables demand-based energy control.
Digital twin
Models can be reused in simulations.