Process Optimization
Real-time parameter tuning with hybrid models.
SUPi uses hybrid physics + ML models to analyze production workflows and recommend real-time parameter adjustments — temperatures, pressures, flow rates, timing — tailored to your specific plant dynamics.
Optimization Approach
Every recommendation is:
- Traceable — full audit trail for compliance
- Explainable — physics-backed reasoning, not black-box suggestions
- Safe — constrained within equipment design limits
- Reversible — suggested changes, not autonomous control
Common Use Cases
| Industry | Optimization Target | Typical Improvement |
|---|---|---|
| Pharma | Batch yield and consistency | +30% quality improvement |
| Chemicals | Reactor temperature profiles | -15% energy consumption |
| Oil & Gas | Compressor efficiency | +8% throughput |
| Power | Turbine heat rate | -5% fuel consumption |
Compliance & Traceability
Every recommendation includes a full data lineage — from the sensor readings that triggered it, through the model calculations, to the final suggestion. This meets GMP, FDA 21 CFR Part 11, and ISO audit requirements.