This blog category covers the technical application of process modelling within the chemical processing industry, specifically tailored for petrochemical, specialty chemical, and fine chemical facilities. Content should focus on EnerTherm Engineering’s methodology for optimizing complex reaction networks, multi-component separations, and catalyst performance. Key topics include reaction kinetics modelling (predicting conversion, selectivity, and by-product formation), rigorous distillation simulation (optimizing reflux ratios and energy consumption), and catalyst degradation prediction (tracking coking, sintering, and poisoning). Articles should explore the firm’s 6-step methodology: data collection from SCADA/IoT systems, model development (physics-based, data-driven, or hybrid), calibration and validation (using RMSE and MAPE metrics), simulation-based optimization, real-time integration via OPC-UA/APIs, and adaptive maintenance. Technical content should also address process safety modelling, including runaway reaction analysis and relief system adequacy. Authors should reference the firm's ability to deliver measurable outcomes, such as 25% yield improvements, 18% energy cost reductions, and 3x extensions in catalyst life. Content should be framed for engineers and plant managers, emphasizing the use of digital twins, reduced-order models, and the integration of historian data to drive continuous, closed-loop process control.