Hydrocarbon Engineering, learn how CLARITY Prime combines plant-specific machine learning, predictive analytics, and hybrid modelling to optimize catalyst health and process efficiency.

Explore impactful case studies in ammonia, propylene, and ethylene production.

Discover how INEOS, Clariant, and Navigance turned a catalyst risk into a success case using digital tools for real-time collaboration.

This paper from the Nitrogen + Syngas Conference 2024 explains how hybrid process models enable predictive catalyst performance modelling to make faster, smarter decisions. It examines the opportunities and challenges for syngas plants.

This article from the Nitrogen+Syngas magazine details the practical use of machine learning in chemical plants and explains its use for improving efficiency and anomaly detection.

Learn how Navigance helps plants turn data into action with real-time recommendations and drives continuous optimisation - without tying up too many resources of your plant team.

Explore how hybrid modelling and machine learning can overcome the limits of traditional control systems.

This article from Nitrogen+Syngas explains how Navigance integrates domain knowledge and real-time data analytics to deliver prescriptive recommendations — enabling dynamic, non-linear process optimisation across a variety of technologies and catalyst types.