Industry 4.0 & Fuels and Petrochemicals Division Joint Plenary

Join us for the joint plenary hosted by AIChE's Fuels & Petrochemicals Division and the Industry 4.0 topical conference which will feature key speakers discussing the current transformation of the chemical industry.

Schedule

Abstracts

The Digital Transformation Promises to Change Innovation in the Materials Industry. Will It?

Andre Argenton, Research & Development, Dow Inc.

The industry is challenged to innovate faster than ever while also delivering sustainability improvements that require profound change through the value chain. Simultaneously with that pressure, digitalization and AI are advertised as revolutions that has caused many to fear becoming obsolete. This dichotomy of extreme pressure and emerging, revolutionary technologies is causing fast, significant change in the industry and the innovation process. In this talk, I would like to share my view on what this impact will be, what risks exist, and what, in my view, will drive long-term success.

Digital Twins & Smart Manufacturing - Where Data Analytics Meet Modeling & Optimization

Efstratios N. Pistikopoulos, Artie McFerrin Department of Chemical Engineering, Texas A&M University

Modeling and Optimization constitute core competencies of process systems and chemical engineering fields, and play pivotal role in the analysis, simulation, design and operational activities that we perform daily in order to improve the performance and sustainability of energy and manufacturing processes and supply chains. The re-emergence of AI and Big Data revolution that we are all witnessing at the moment, also provide an opportunity and a platform toward real-time decision-making. While often perceived as different fields, in the context of Smart Manufacturing, Data Analytics and Modeling/Optimization can in fact be viewed as ‘two sides of the same coin’.

In this lecture, we will attempt to elucidate this argument through the lenses of hybrid modeling and digital twins, which bring together the advantages and power of high-fidelity modeling & optimization and AI/machine learning technologies and tools, and their synergy. A central theme will be that the evolution/revolution in data-driven methods in the context of process modeling and automation is becoming a critical component in advancing the energy & manufacturing transition agenda toward clean energy, increased process/energy efficiency, sustainability and resilience, and ultimately economic and societal prosperity.