"Advancing Sustainable Process Design Through Systems Thinking: Synergies Between Optimization Frameworks and Data-Driven Tools"

Presentation Abstract:

Nowadays, environmental and social criteria must be included alongside traditional economic indicators during process retrofitting and design. The complex system-like nature of processes and societies adds another layer of challenge. Systematic design

and optimization methods provide a powerful framework to navigate this complexity. However, practical implementation is often limited by model uncertainties, unknown parameters, formulation errors, and the generation of single solutions that may not suit real-world constraints. Join this webinar to explore how the combination of rigorous graphtheoretic optimization with data-driven approaches can overcome these challenges. We will discuss how this synergy advances the generation of design and engineering tools that provide valuable information for decision-making. Participants will gain insight into the identification of process alternatives considering economic feasibility, environmental impact, resilience, and reliability.

Don't miss this opportunity to gain valuable knowledge on applying advanced process optimization tools to achieve comprehensive, sustainability-focused designs.

Speaker:

Dr. Jean Pimentel is a research associate at the Széchenyi István University specializing in process systems engineering (PSE). He earned his PhD in chemical engineering from the Budapest University of Technology and Economics. His research focuses on the synthesis and optimization of production processes with a strong emphasis on advancing the sustainability of industrial systems. His research has implemented the graphtheoretical optimization approach known as the P-graph framework in various fields and has contributed significantly to the development of this method. He has co-authored the book “P-graphs for Process Systems Engineering” and has contributed to various publications in international journals. He addresses complex engineering challenges through rigorous mathematical modeling and combinatorial optimization techniques with the goal of supporting the transition to more efficient and sustainable production systems.