Generative AI for PSE

Generative AI for Process Systems Engineering: Potential Applications and Pitfalls
This presentation is an introduction on Generative AI on the field of Process Systems Engineering (PSE). At its core, PSE revolves around the mathematical modeling, optimization, and simulation of chemical and physical processes. With Generative AI, particularly advancements like Large Language Models (LLMs), offer a new avenue to complement and enhance development of these traditional methodologies. In related work areas, the productivity of consultants improved by 25% and the quality of the work increased by 40%. This presentation provides an overview of new Generative AI tools, with applications for workforce development and time-series modeling with Tranformers. AI's capability in conceptual process control design will also be discussed, helping process control engineers develop new systems or revamp existing ones. However, as with any new technology, challenges exist. There is a distinct jagged edge of application beyond which the Generative AI provides incorrect information. There are additional issues of over-reliance, the explainability of the AI outputs, and the repeatability of AI-backed processes. General purpose tools can be adapted to specific company applications with transfer learning to reduce the required data and training requirements.

[@jonathanuis]

John, I consistently find immense value in your videos. Your dedication to providing exceptionally high-quality content for process systems engineers doesn’t go unnoticed. Thank you for your hard work.
Warm regards from Germany.

[@apm]

Thanks for that feedback!

[@sari54754]

Amazing contents for engineer, Thanks.

[@stevezitney8416]

John, very informative presentation with many great recommendations and ideas for exploiting generative AI in process systems engineering!

[@apm]

Thanks for that feedback, Stephen. You do a great job highlighting innovations in the Computer Aids for Chemical Engineering group www.linkedin.com/groups/5126294

[@hubstrangers3450]

Thank you.....take it, some of the above project resources and raw data is available on git repository

[@sarazio3484]

Thanks Sir