Speaker:Dr Yuan Yao
Time: Sunday, July 20, 14:30 p.m
Venue: Conference Room 1 of the Convention Center
Abstract:
Twin-screw extruders (TSEs) are essential in polymer processing, enabling the handling of diverse materials in manufacturing. However, TSE performance heavily depends on optimized screw configurations and operating conditions. Such optimization is challenging due to two key factors: limited data availability across material–process combinations and the complex, nonlinear relationship between screw configuration, operating conditions, and product quality.
To address this, we propose a recurrent deep embedding network (RDEN)—a data-driven modeling framework designed for TSE optimization under limited data. Inspired by advances in natural language processing, RDEN uses an autoencoder to learn compact representations of screw configurations, which are then combined with operating condition inputs and processed by a GRU-based recurrent neural network to incorporate positional information of screw elements for quality prediction.
We further develop an optimization framework that applies RDEN to jointly design screw configurations and operating conditions. This approach improves process simulation accuracy, integrates both qualitative and quantitative variables, and enhances design efficiency—even in data-constrained scenarios.
Biography:
Professor Yuan Yao received his Bachelor's and Master's degrees in Control Science and Engineering from Zhejiang University in 2001 and 2004, respectively, and his Ph.D. in Chemical and Biomolecular Engineering from the Hong Kong University of Science and Technology (HKUST) in 2009.
From 2009 to 2011, he worked as a Research Associate at the Center for Polymer Processing and Systems, HKUST. He joined the Department of Chemical Engineering at National Tsing Hua University (NTHU), Hsinchu, Taiwan, as an Assistant Professor in 2011 and was promoted to Associate Professor in 2015. Since August 2019, he has served as a Full Professor. Since 2022, he has been serving as an Associate Editor of the Quantitative InfraRed Thermography Journal. He has published approximately 140 SCI journal papers, authored three book chapters, and holds 13 patents. His research interests include process data analytics, nondestructive testing data processing, and intelligent process control.
Prof.Yao has served as the principal investigator (PI) or co-PI on more than 80 projects, including numerous industry-academic collaborations. Recent industrial collaborators include Formosa Plastics Corporation, Formosa Petrochemical Corporation, Chang Chun Group, CTCI Corporation, Advanced Semiconductor Engineering, Inc. (ASE), Zhen Ding Technology Holding Limited, Unimicron Technology Corporation, Delta Electronics, DELmind Inc., Swancor Advanced Materials Co., Ltd., and CoreTech System Co., Ltd., as well as leading research institutions such as the Industrial Technology Research Institute (ITRI).