Using high-fidelity digital twins to improve process operations

With guest speakers from Clariant, SK Innovation, and Immaterial

On-demand webinar

Recently the chemical industry has faced surges and volatility in crude oil and natural gas prices, affecting margins and impacting energy-intensive manufacturing. This has been further intensified by the transition to decarbonization backed by regulatory, scientific and public pressures. As a result, companies need to maximize current production and minimize operational costs to stay competitive.

Digital replicas of operating assets that combine deep process knowledge in the form of high-fidelity process models, along with live plant data, are now bringing a new level of decision support to operations in chemical plants. The combination of plant data and predictive modelling is enormously powerful, making it possible to achieve higher yields and throughput, lower energy consumption and more effective maintenance.

This webinar will explore various case studies from the chemical industry, highlighting the successful use of gPROMS within the context of engineering and operations.

What is the content and focus of the webinar?

  • Toby Hallitt (Siemens) will give a brief introduction and describe how gPROMS is typically applied within the operational space.
  • Stepan Spatenka (Siemens) will present the technical solution for modeling catalytic reactors with Matthias Feigel (Clariant AG) discussing the benefits derived at Clariant.
  • Shashank Maindarkar (Siemens) will present the technical solution for modeling polymerization with Dr. Jaeheum Jung (SK Innovation) discussing the benefits derived at SK Innovation.
  • Qinglin Huang (Siemens) will present the technical solution for modeling adsorption beds with Amin Koochaki (Immaterial) discussing the benefits derived at Immaterial.

Our speakers at a glance

Toby Hallitt is a PreSales Solution Consultant for Siemens Digital Industries working in the Industry Strategy team for Chemicals. Toby earned his master’s degree in chemical engineering from the University of Bath in 2020. At Siemens, Toby has almost 5 years’ experience working with an advanced process modeling solution, helping customers derive value from using digital process twins, as well as identifying and qualifying new opportunities for successful adoption of Siemens’ product portfolio in Software for Process Automation.

Amin Koochaki has a Ph.D. in Chemical Engineering from Iran University of Science and Technology and specializes in molecular modeling for CO2 capture and water uptake using MOFs. As a process engineer at Immaterial, he leverages process modelling techniques for various swing adsorption systems, including Pressure Vacuum Swing Adsorption (PVSA) and Vacuum Temperature Swing Adsorption (VTSA), focusing on CO2 capture with MOFs.

Stepan Spatenka is a chemical engineer with almost 20 years’ experience in delivering projects focusing on development of advanced reactor models and their applications to troubleshooting and optimisation of chemical processes. Stepan earned his PhD from University of Chemistry and Technology in Prague. At Siemens, Stepan and his team are responsible for developing and maintaining advanced reactor model libraries in gPROMS Process and for supporting users in applying the models for development and optimization of industrial chemical processes.

Matthias Feigel holds a master’s degree in chemical engineering from the Technical University of Munich (TUM), which included studies abroad at the Royal Institute of Technology in Stockholm. At TUM, he further specialized with a PhD in kinetic and process modeling of bio-based materials. Since July 2023, Matthias contributes to the success of the Applied Catalyst Technology (ACT) team at Clariant as a Modeling Expert. In this role, he develops sophisticated programs and tools aimed at optimizing Clariant´s catalysts for our global customers. The employed models allow for an enhanced support bringing added value to the users and customers worldwide.

Dr Jaeheum Jung has a B.S (2010) and Ph.D (2016) from Seoul National University, Biological & Chemical Engineering, majoring in Process Modeling & Optimization. Dr Jung completed an internship at Process Systems Enterprise and now works as Professional Manager at SK Innovation Institute of Environmental Science & Technology.

Shashank Maindarkar is a product developer at Process Modeling Competence Center in Siemens. Shashank has earned his PhD in Chemical Engineering from University of Massachusetts in USA. At Siemens, he is responsible for developing and maintaining the polymerization reactor model libraries in gPROMS Process. He has 10 years’ experience of using gPROMS to carry out modeling, simulation and optimization of industrial polymerization processes. He also supports users with applying the models as well as with the implementation of polymerization kinetics as custom models.