14 July 2026, 2pm - 5pm
Workshop 2
Workshop 2
Smart Manufacturing: From Predictive, Prescriptive, to Agentic Decision
This workshop introduces smart manufacturing, a multi-objective decision-oriented system that leverages computational intelligence and self-learning capabilities to autonomously optimize manufacturing resources and processes. The talk identifies common challenges and 7 myths of AI applied to manufacturing practice. Four-phase digital transformation is proposed to provide a guideline for ITxOT integration and resource reproposition. The talk also demonstrate several use cases in real practice.
Workshop 2
Why Attend:
This workshop helps manufacturing leaders understand that how AI and data science technology can be used to predict machine failures, optimize processes, and reduce production downtime. Participants will learn the fundamentals of digital transformation and see how the manufacturers are creating “factories of the future” with AI as the central nervous system.
Workshop 2
Learning Outcomes:
what you will learn from this workshop?
Identify challenges
of digital transformation in business terms and ROI context.
Connect AI projects
from point, line to plane for supporting business roadmap.
Learn how:
to engage vendors and partners with the right strategic questions.
Dr. Chia-Yen Lee
is Professor in Department of Information Management, Associate Dean in College of Management, and Director for Entrepreneurship and Innovation MBA (EiMBA), National Taiwan University. He temporarily transferred as Deputy Director in Taiwan Semiconductor Manufacturing Company (tsmc). He received Ph.D. degree from Dept. of Industrial and Systems Engineering at Texas A&M University, USA.
His research interests include manufacturing data science, productivity and efficiency analysis, with applications to semiconductor manufacturing, TFT-LCD, motor drive, energy and pollutant, petrochemical industries, etc. He serves as associate editor for IEEE Transactions on Semiconductor Manufacturing, and IEEE Transactions on Automation Science and Engineering.
His research works appear in European Journal of Operational Research, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Engineering Management, Journal of Environmental Management, IEEE Robotics and Automation Letters, etc. He received 2025 AI Award Best Solution of Academic Industrialization, the 2021 Outstanding Research Award from Ministry of Science and Technology (MOST) of Taiwan, the 2018 Kwoh-Ting Li Technology & Literature Lectureships Award of Distinguished Young Scholars from NCKU-Delta Electronics, the 2017 Ta-You Wu Memorial Award of Distinguished Young Scholars from MOST, Outstanding Young Scholar Grants (2014, 2017, 2022) from MOST, the 17th Best Practice Paper Award from the Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS 2016), the 2016 Outstanding Young Industrial Engineer Award from the Chinese Institute of Industrial Engineers (CIIE 2016). (http://polab.im.ntu.edu.tw/Bio.html)