Doxazo Consulting closes the gap between process simulators and real plant performance. We pair rigorous chemical process simulation baselines with residual machine learning to deliver yield predictions that are physically grounded, validated against real plant data, and fully explainable.
We build and validate a chemical process simulation across your plant's operating range, giving every corrected prediction a thermodynamically rigorous physics foundation.
Real operating data from your facility is sourced, cleaned and merged with the simulated outputs so every operating condition has a matched pair of simulated and observed yield.
We compute and characterise the systematic gap between the simulated yields and real plant yields, confirming that the deviation is condition dependent and worth correcting before any model is trained.
Traditional ML models such as Linear Regression, Gradient Boosting and XGBoost are trained and benchmarked against the residual, with cross validation and hyperparameter tuning selecting the strongest correction model.
SHAP analysis is applied to the best model to attribute the correction to specific operating conditions, so your engineers can see which variables the simulator underrepresents.
The physics baseline and the residual correction are combined into a single corrected yield prediction, benchmarked against the standalone simulator on RMSE, MAE and R squared.
We sit at the intersection of engineering domain knowledge and modern artificial intelligence, a combination that is uncommon and genuinely valuable when correcting simulator predictions against real plant behaviour.
We specialise in one thing: closing the gap between what a process simulator predicts and what a plant actually produces. The chemical process simulator provides the physics baseline. A residual machine learning model captures the deviations the simulator cannot represent. Every corrected prediction comes with a clear, SHAP driven explanation of the operating conditions behind it.
We take a rigorous, evidence based approach to every engagement. Our simulations are validated, our models are cross validated, and our corrections are benchmarked against the standalone simulator before they are ever handed to your team.
If your process simulator is drifting from real plant performance, we would like to hear about it. Whether you need a new chemical process simulation baseline, a residual correction model or a full physics informed framework, send us a message and we will respond promptly.