Ensuring high-quality performance in industrial engineering environments remains a cornerstone of competitiveness in modern industries. This special session focuses on quality engineering and intelligent quality for contemporary industrial systems, bridging classical quality control methodologies with advanced data-driven and AI-enhanced techniques. Topics include intelligent quality inspection, statistical process control with machine learning, quality risk management under uncertainty, robust quality engineering, and practical case studies from manufacturing and service industries. By bringing together researchers and practitioners, this session aims to highlight both theoretical advances and practical applications that enhance quality performance, process robustness, and data-supported decision-making in industrial engineering systems.
Topics covered include (but are not limited to):
Prof. Cheng-Fu Huang, Feng Chia University
Biodata: Cheng-Fu Huang received his B.S. degree in Industrial Engineering from Feng Chia University, Taichung, Taiwan, in 2004, his M.S. degree in Industrial Engineering and Management from National Chin-Yi University of Technology, Taichung, in 2006, and his Ph.D. degree in Industrial Management from National Taiwan University of Science and Technology, Taipei, Taiwan, in 2010. He is currently a Professor in the Department of Business Administration at Feng Chia University. His research interests include multi-state flow network modeling, network reliability evaluation, quickest path reliability analysis, Monte Carlo–based simulation algorithms, and quality management. He has authored more than 60 papers in refereed international journals and actively serves as a reviewer for leading journals in reliability engineering and operations research.
Assoc. Prof. Shih-Wen Liu, National Chin-Yi University of Technology
Biodata: Shih-Wen Liu is currently an Associate Professor in the College of Management at National Chin-Yi University of Technology (NCUT), Taiwan. Dr Liu received his Ph.D. degree in Industrial Management from National Taiwan University of Science and Technology (NTUST) in 2016. Dr Liu was honorably subsidized by Ministry of Science and Technology (MOST) of Taiwan to Rutgers University for research purposes. Before he joined NCUT, Dr Liu was an R&D engineer in the contact lens industry which expands his horizon of the Industrial Engineering field. Also, Dr Liu was a member of Quality Management Lab in National Tsing Hua University (NTHU), Taiwan as a Postdoctoral Researcher. His research interests include quality engineering and management, statistical process control, process capability analysis, applied statistics, and data analysis.
Assoc. Prof. Zih-Huei Wang, Feng Chia University
Biodata: Zih-Huei Wang is an Associate Professor in the Department of Industrial Engineering and Systems Management at Feng Chia University, Taiwan. She currently serves as the Director of the Professional Master's Program for Intelligent Manufacturing and Engineering Management. She received her Ph.D. from National Tsing Hua University in 2018. Her research interests mainly focus on quality engineering, process capability analysis, design of experiments, and data analysis. She received the 2025 Distinguished Young Scholar Award from the Operations Research Society of Taiwan (ORSTW) and the 2024 Outstanding Young Industrial Engineer Award from the Chinese Institute of Industrial Engineers (CIIE). In 2017, she was a visiting scholar at Georgia Tech, collaborating with Piedmont Heart Institute to produce several conference papers and posters. She was also invited by Dr. Zhen Qian to co-author a 2020 book chapter on advanced analytical techniques for medical image analysis.
Delegates are encouraged to submit their full papers/abstract to the special sessions. Please submit your electronically article in PDF format before the submission deadline.
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