Modeling, Control, and Optimization of Manufacturing Systems

Chair(s):
Baldea, M., The University of Texas at Austin
Co-chair(s):
He, Q. P., Auburn University

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.

Papers:
8:00 AM
(629a) Real Time Constrained Model Predictive Control for the Continuous Manufacturing of Pharmaceuticals
8:19 AM
(629b) Model Predictive Control of a Rotational Molding Process
8:38 AM
(629c) A Multiparametric Programming Based Approach to Integrate Design, Scheduling, and Control of a Batch Process
8:57 AM
(629d) Multi-Objective Dynamic Optimisation of a Fed-Batch Nosiheptide Reactor
9:16 AM
(629e) Big Data and the Chemical Industry: From Sensor to Value
9:35 AM
(629f) Big Data and Iot: A Demonstration Testbed of Multi-Stage Centrifugal Pumping System
9:54 AM
(629g) Pressure Swing Adsorption Cycle Synthesis Utilizing Artificial Neural Networks As Surrogate Models
10:13 AM
(629h) Continuous Control of a Polymerization System with Deep Reinforcement Learning
Topics: 
Process Automation & Control

Checkout

Paper abstracts are public but to access Extended Abstracts, you must first purchase the conference proceedings.

Checkout

Do you already own this?

Pricing

Individuals

AIChE Members $150.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
Non-Members $225.00