646 Big Data in Process Modeling, Estimation and Control


Description:
Contributions are invited on the topic of big data methods for off-line process modeling, on-line process state and parameter estimation and real-time feedback. Applications to industrial processes are encouraged.

Sponsor:
Data and Information Systems


Chair:
Ravendra Singh
Assistant Research Professor
Rutgers, The State University of New Jersey
Department of Chemical and Biochemical Engineering
98 Brett Road
Piscataway, NJ
08854
Fax Number: +17324452581
Email: ravendra.singh@rutgers.edu

Co-Chair:
Matthew J. Realff
Professor
Georgia Institute of Technology
School of Chemical and Biomolecular Engineering
311 Ferst Drive
Atlanta, GA
30332
Email: matthew.realff@chbe.gatech.edu


Papers:
646a
Pipeline Big Data Analysis - Leak Localization
Stevan Dubljevic, University of Alberta; Xiaodong Xu, University of Alberta
646b
Big Data Approach to Fault Detection, Diagnosis and Maintenance Optimization in Batch Processes
Melis Onel, Texas A&M Energy Institute, Texas A&M University; Chris A. Kieslich, Georgia Institute of Technology; Yannis A. Guzman, Princeton University; Efstratios N. Pistikopoulos, Texas A&M Energy Institute, Texas A&M University
646c
An Information Entropy Based Criterion for Variable Selection Performance Assessment
Q. Peter He, Auburn University; Kerul Suthar, Auburn University; Jangwon Lee, Auburn University
646d
Health Monitoring of Multi-Scale Systems Using an Optimal Multi-Rate Wireless Sensor Network
Qiao Huang, West Virginia University; Debangsu Bhattacharyya, West Virginia University; Edward Sablosky Mechanical & Aerospace Engineering, West Virginia University; Katarzyna Sabolsky, West Virginia University; Rajalekshmi Pillai, West Virginia University
646e
Learning Based Automated Identification of Nuisance and Correlated Alarms
Neha Goyal, Starbucks Coffee Company; Yash Puranik, Rockwell Automation; Alexander B. Smith, Rockwell Automation; Bijan Sayyar-Rodsari, Rockwell Automation
646f
Dynamic Latent Variable Regression for Data Modeling and Monitoring
Qinqin Zhu, University of Southern California; S. Joe Qin, University of Southern California
646g
Bayesian Model Averaging for Estimating the Spatial Temperature Distribution in a Steam Methane Reformer
Anh Tran, University of California, Los Angeles; Marquis Crose, University of California, Los Angeles; Andres Aguirre, University of California, Los Angeles; Yangyao Ding, University of California, Los Angeles; Madeleine Pont, University of California, Los Angeles; Helen Durand, University of California, Los Angeles; Panagiotis D. Christofides, University of California, Los Angeles
646h
Adaptive ARX Models for Non-Linear Chemical Processes: An Industrial Application
Zhenyu Wang, Tufts University; Suyash Singh, Air Products and Chemicals, Inc.; Ali Esmaili, Air Products and Chemicals, Inc.
646i
Performance Evaluation of Anomaly Diagnosis System Based on Adaptive Resonance Theory
Yoshinari Hori, Hitachi, Ltd.; Yoshiharu Hayashi, Hitachi, Ltd.; Takaaki Sekiai, Hitachi, Ltd.; Hiroki Yamamoto, Hitachi, Ltd.; Shinji Hasebe, Kyoto University
Abstract Submissions Closed
See more of this Group/Topical: Computing and Systems Technology Division
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