224 Big Data and Applications in Advanced Modeling and Manufacturing

Tuesday, November 17, 2020: 8:00 AM - 9:00 AM
Next-Gen Manufacturing (T6) (PreRecorded+)

Description:
In this session the importance of utilizing advanced modeling and big data to improve process productivity, reliability, and control will be highlighted. Presentations would cover a wide spectrum of topics from approaches that improve decision making on process safety to how process industries find actionable insights from advanced modeling and Big Data to optimize process operation, and therefore, increase plant reliability and integrity.

Sponsor:
Next-Gen Manufacturing
Co-Sponsor(s):
Information Management and Intelligent Systems (10E)
Chair:
Joel Paulson Email: paulson.82@osu.edu
Co-Chair:
Manjiri Moharir Email: manjiri.a.moharir1@exxonmobil.com
- indicates paper has an Extended Abstract file available on the online proceeding.



(224a) Data-Efficient Probabilistic Model Learning with Embedded High-Fidelity Knowledge for Biomanufacturing in Deep Space Manned Missions
Georgios Makrygiorgos, Aaron Berliner, Adam P. Arkin and Ali Mesbah


(224b) Recognizing and Avoiding Big Data Analytics Traps in Applications
Weike Sun and Richard Braatz


(224c) Data-Driven and Hybrid Modeling of Integrated Paper Production Systems
Jinhyeun Kim, Kamran Paynabar, Christopher O. Luettgen and Fani Boukouvala


(224d) Optimal Operation of Plasma Enhanced Atomic Layer Deposition Via Machine Learning
Yangyao Ding, Yichi Zhang and Panagiotis D. Christofides


(224e) System Visualization Using Real-Time Data-Driven Models Derived from High-Resolution Sensor Profiling
Chenyu Wang, Tianbao Wang, Baikun Li and Matthew D. Stuber


(224f) Towards the Use of Multi-Relational Data Mining (MRDM) in Bioprocess Models
Simoneta Caño de las Heras, Carina Gargalo, Isuru A. Udugama, Krist V. Gernaey and Ulrich Krühne

File available
(224g) The Algorithm to Discriminate Factors of Defects and Determine the Countermeasures from Process Data and Application to Highly-Functional Film Process
Daisuke Yagi, Hidenori Takai and Hiroki Watanabe
See more of this Group/Topical: Topical Conference: Next-Gen Manufacturing
<< Previous Session | Next Session >>