Thursday, October 16th 2024
(Milan Time) 9:00 -10:00
(Beijing Time) 15:00-16:00
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Biography
He obtained his Ph.D. in Mechanical Engineering at the University of Southern California (USC) in 2012. Dr. Liu’s research interests include design thinking, design methodology, intelligent manufacturing, digital twin, artificial intelligence, and engineering education. Dr. Liu is a Fellow of ASME (American Society of Mechanical Engineers), Associate Member of International Academy for Production Engineering (CIRP), Invitational Fellow of JSPS (Japan Society for the Promotion of Science), Fellow of the PLuS Alliance, and Senior Fellow of the Higher Education Academy (SFHEA). He is Secretary of CIRP STC Dn in 2022-2025. He was Co-Chair of the 10th International Conference on Axiomatic Design (ICAD2016), General Chair of the 13th International Conference on Axiomatic Design (ICAD2019), and Chair of the 2nd Digital Twin International Conference. He chairs the 33rd CIRP Design Conference in 2023. He received multiple prestigious awards such as the Park’s Best Journal Paper Award in 2019, UNSW Vice-Chancellor Award for Outstanding Contributions to Student Learning in 2021, one of the 250 Top Researchers by the Australian’s Research Magazine 2021-2022, Citation for Outstanding Contributions to Student Learning of the 2022 Australian Awards for University Teaching (AAUT), etc. Dr. Liu is an Associate Editor of Journal of Intelligent Manufacturing, and he serves in the editorial boards of multiple prestigious journals such as Journal of Engineering Design, Digital Twin, Scientific Reports, Production & Manufacturing Research, Chinese Journal of Mechanical Engineering, Machines, Green Manufacturing Open, etc.
Title: Digital Twin for Engineering Design
Abstract
In the digital age, data has become the new “oil,” essential for driving innovation and decision-making. Among the transformative technologies, Digital Twin (DT) stands out as a critical bridge between the physical and digital worlds, enabling seamless connection and communication. The integration of AI has significantly enhanced the capabilities of digital twins. Traditionally, engineering design involved extracting information from data, building knowledge, solving design challenges, and gaining insights through experience. However, with the advent of Industry 4.0, the design process is increasingly digitalized, and AI is at the forefront of this transformation. AI-powered digital twins can simulate, predict, and optimize every aspect of a product’s lifecycle. Through advanced algorithms, AI analyzes vast amounts of data to provide real-time insights, driving smarter and more efficient design decisions. This capability allows for rapid adjustments and continuous improvement throughout the design and manufacturing processes, ensuring that products are optimized from concept to completion. In this presentation, we will explore how AI-driven digital twins are revolutionizing engineering design. We’ll contextualize the emergence of digital twins within the broader shift toward data-driven design, highlighting AI’s central role in this evolution. We will also examine the application of AI-enhanced digital twins across various stages of product design and outline a systematic approach to creating functional digital twin systems. Finally, we’ll discuss the impact of AI-driven digital twins in innovative fields, such as the treatment of heart diseases.