2024 AIChE Annual Meeting

Session: Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency

Applied Artificial Intelligence, Big Data, and Data Analytics Methods for Next-Gen Manufacturing Efficiency

Chair

Joel Paulson, The Ohio State University

Co-Chair

Wentao Tang, University of Minnesota

Presentations

08:00 AM

(664a) Translating Process Flow Diagrams to Piping & Instrumentation Diagrams (P&IDs) with Artificial Intelligence
Dominik Goldstein, Lukas Schulze Balhorn, Edwin Hirtreiter, Artur M. Schweidtmann

08:21 AM

(664b) Developing a Framework for Enhanced Troubleshooting with Large Language Models
Jihan Abou Halloun, Anh Tran, Helen Durand

08:42 AM

(664c) Accelerated Process Optimization for a Circular Economy Using Full Flowsheet Neural Network Models
Ville Kaerkaes, Tim Kircher, Maximilian Hungsberg, Martin Votsmeier, Bastian Etzold

09:03 AM

(664d) Prompt Engineering-Directed in-Context Learning of an LLM with Integrated Automated Simulation for Generative Chemical Process Design
Donghyeon Lee, Dongil Shin

09:24 AM

(664e) Geometry-Informed Deep Learning Surrogate Models for Flow Prediction and Optimisation of Flow Reactors
Nausheen Basha, Mosayeb Shams, Sibo Cheng, Rossella Arcucci, Omar Matar

09:45 AM

(664f) Dynamic Graph-Based Distributed Estimation and Control of Fast-Evolving Complex Process Networks
Amirmohammad Ebrahimi, Davood Babaei Pourkargar

10:06 AM

(664g) Active Learning and Symbolic Regression for Interpretable Modeling of Laser Power Bed Fusion (L-PBF) Additive Manufacturing Processes
Alexander Summers, Q. Peter He