This program is a Streamlit-based engineering decision-support tool for chemical and biological process optimization.
- Calculates process performance as a function of operating temperature
- Estimates energy use, operating cost, and carbon emissions
- Identifies feasible operating conditions that meet a target performance
- Finds the cost-optimal feasible temperature
- Generates AI-style engineering recommendations
- Python
- Streamlit
- NumPy
- Pandas
- Matplotlib
- Process modeling
- Energy balance
- Cost estimation
- Carbon emissions analysis
- Process optimization
- Rule-based recommendation systems
Current temperature is higher than necessary for the target performance. Lowering temperature to around 106°C could reduce operating cost and carbon emissions while still meeting the target.# process-optimization-assistant-