629 Modeling, Control, and Optimization of Manufacturing Systems


Description:
This session includes papers related to modeling, control, and optimization of manufacturing systems. Industrial contributions are highly encouraged. Abstracts containing use of big data for manufacturing systems control are highly desirable.

Sponsor:
Systems and Process Control
Co-Sponsor(s):
Technology Transfer and Manufacturing (12C), Next-Gen Manufacturing (T6A)


Chair:
Michael Baldea
Associate Professor
The University of Texas at Austin
McKetta Department of Chemical Engineering
200 E Dean Keeton St. Stop C0400
Austin, TX
78712-1589
Email: mbaldea@che.utexas.edu

Co-Chair:
Q. Peter He
Associate Professor
Auburn University
Chemical Engineering
Auburn, AL
36088
Fax Number: 334-724-4188
Email: qhe@auburn.edu


Papers:
629a
Real Time Constrained Model Predictive Control for the Continuous Manufacturing of Pharmaceuticals
Kelly Nocon, University of California Los Angeles; Omar Sheikh, University of California Los Angeles; Niraj Mehta, University of California Los Angeles; Vasilios Manousiouthakis, University of California Los Angeles, Los Angeles
629b
Model Predictive Control of a Rotational Molding Process
Abhinav Garg, McMaster University; Felipe P.C. Gomes, McMaster University; Prashant Mhaskar, McMaster University; Michael R. Thompson, McMaster University
629c
A Multiparametric Programming Based Approach to Integrate Design, Scheduling, and Control of a Batch Process
Baris Burnak, Texas A&M University; Efstratios N. Pistikopoulos, Texas A&M Energy Institute, Texas A&M University
629d
Multi-Objective Dynamic Optimisation of a Fed-Batch Nosiheptide Reactor
Alistair D. Rodman, University of Edinburgh; Dimitrios I. Gerogiorgis, University of Edinburgh
629e
Big Data and the Chemical Industry: From Sensor to Value
Flor Castillo, SABIC; William Hollar, SABIC
629f
Big Data and Iot: A Demonstration Testbed of Multi-Stage Centrifugal Pumping System
Devarshi Shah, Auburn University; Jin Wang, Auburn University; Q. Peter He, Auburn University
629g
Pressure Swing Adsorption Cycle Synthesis Utilizing Artificial Neural Networks As Surrogate Models
Karson Leperi, Northwestern University; Daison Yancy-Caballero, Northwestern University; Randall Q. Snurr, Northwestern University; Fengqi You, Cornell University
629h
Continuous Control of a Polymerization System with Deep Reinforcement Learning
Yan Ma, Louisiana State University; Wenbo Zhu, Louisiana State University; Michael G. Benton, Louisiana State University; Jose A. Romagnoli, Louisiana State University
Abstract Submissions Closed
See more of this Group/Topical: Computing and Systems Technology Division
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