109 Big-Data for Process Applications

Monday, November 16, 2020: 8:00 AM - 9:00 AM
Computing and Systems Technology Division (10) (PreRecorded+)

Description:
Real-world data can be a valuable asset for improving process design or operations. However, collecting and analyzing this data can be challenging due to data sparsity, heterogeneity, uncertainty, or dimensionality. This session seeks papers on the topic of data analysis and information management. Submissions from industry or collaborations between academia and industry are highly encouraged. Topics can cover both methods for data-analysis and information management, as well as applications.

Sponsor:
Information Management and Intelligent Systems
Co-Sponsor(s):
Pharmaceutical Discovery, Development and Manufacturing Forum (26)
Chair:
Q. Peter He Email: qhe@auburn.edu
Co-Chair:
Kirti M. Yenkie Email: yenkie@rowan.edu


(109a) Optimization-Driven Quasi-Deterministic Monte Carlo Sampling for Accurate Uncertainty Quantification: Applications to the Pharmaceutical Industry
Francesco Rossi, Linas Mockus and Gintaras V. Reklaitis


(109b) Topological Data Analysis: Concepts, Computation, and Applications
Alexander Smith and Victor M. Zavala


(109c) Computational Fluid Dynamics-Based in-Situ Sensor Analytics of Direct Metal Laser Sintering Process Using Machine Learning
Yi Ming Ren, Yichi Zhang, Yangyao Ding and Panagiotis D. Christofides


(109d) A Data-Engineering Approach for Estimating Chemical Releases from Industrial Pollution Abatement Technologies
Jose D. Hernandez-Betancur, Shuyun Li, Fernando V. Lima, Mariano Martín and Gerardo Ruiz-Mercado


(109e) Physics Informed Machine-Learning for Static Security Analysis of Optimal Power Flow Solutions
Zachary Kilwein, Logan Blakely, Anya Castillo, Michael Eydenberg, Carl D. Laird and Fani Boukouvala


(109f) Statistics Pattern Analysis-Based Multiclass Woodchip Moisture Classification System Using Short-Range Iot Wi-Fi
Kerul Suthar, Jin Wang, Zhihua Jiang and Q. Peter He


(109g) Proad (Process Advisor): Health Monitoring Dashboard for Centrifugal Pumps
Arnab Dutta, Iftekhar A. Karimi and Farooq Shamsuzzaman


(109h) Data-Driven Approaches Towards Real-Time Equipment Health Monitoring and Predictive Maintenance in Drug Product Manufacturing
Philipp Zürcher, Sara Badr and Hirokazu Sugiyama
See more of this Group/Topical: Computing and Systems Technology Division
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