Big Data Analytics and Smart Manufacturing


Description:
We seek contributions that reflect the use of new information streams (e.g., real-time asset tracking, large numbers of wireless sensors and actuators, big data analytics), ubiquitous distributed computing and cloud-based computational resources, to enhance decision making, both in process design and in process operations. Theoretical developments and applications of interest include (but are not limited to) the use of high-fidelity (e.g., computational fluid dynamics) models in real-time operations, integration of operations and supply chains across multiple industries (including industrial demand response) and methods for tighter coordination between the control, scheduling and planning functions of the chemical supply chain.

Sponsor:
Topical A: 3rd Big Data Analytics


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

Co-Chair:
Tom Xu
Scientist
DuPont
Wilmington, DE
Phone Number: 302-695-8052
Email: Tom.Xu@dupont.com


Papers:
Enterprise Manufacturing Intelligence (EMI) at the Dow Chemical Company
Bradley J. David, Dow Chemical Canada ULC; Mary Beth Seasholtz, The Dow Chemical Company
Visualization and Visual Analysis of Batch-Continuous Process Data
Ray Wang, The University of Texas at Austin; Michael Baldea, The University of Texas at Austin; Thomas F. Edgar, McKetta Department of Chemical Engineering, The University of Texas at Austin
Regression Strategies for Large Data Sets
James Cross III, The MathWorks, Inc.
Performance Monitoring of Global Chemometric Models in Manufacturing Plants: New Approaches for Efficient Model Maintenance
Nikos Petzetakis, Dow Chemical; Birgit Braun, The Dow Chemical Company; Jackie Hunt, The Dow Chemical Company; Leslie Frederick, The Dow Chemical Company; Brenda Colegrove, The Dow Chemical Company; Serena Stephenson, The Dow Chemical Company
Knowledge Discovery and Explanation from Industrial Process Data Using Clustering and Subspace Search
Wenbo Zhu, Louisiana State University; Jose Romagnoli, Louisiana State University
See more of this Group/Topical: Topical A: 3rd Big Data Analytics