Combining AI with Chemical Engineering First Principles Will Take Process Performance, Safety and Sustainability to New Levels

Digitalization is now in the spotlight in terms of creating improved agility, resilience, and ability to operate process industry assets remotely and safely.

Sensors, connectivity, and cloud computing are making process data more available for use in optimization and prediction. High performance, edge computing, and new algorithms are enabling placing process models online for monitoring, optimization, and operational advice.

Most process and chemical engineers in industry have observed the influx of data science and data scientists into their organizations. This session will cover an area called "hybrid modeling". This combines and embeds AI and machine learning within first-principles rigorous models. You may think of this as putting chemical engineering guardrails around machine learning. Rigorous, first principles models, brings to bear decades of chemical engineering knowledge. Machine learning and AI brings to bear ability to rapidly analyze, and progressively learn from empirical operating data. When combined, it is now possible to achieve a new level of modeling that will further leverage both types of analysis. We have been validating this breakthrough combination of AI and chemical engineering with over 100 companies in industry, and will cover several high value and immediately practical use cases during this session.