2024 7th International Conference on Computing and Big Data(ICCBD 2024)
.
Prof. Lihui Wang
Academician of Canadian Academy of Engineering, Canada
Lihui
Wang is a Professor and Chair of Sustainable Manufacturing
at KTH, Sweden. He is also the Director of Centre of
Excellence in Production Research (XPRES) - one of the five
national strategic research centres at KTH. He has served as
the President (2020-2021) of North American Manufacturing
Research Institution (NAMRI) of Society of Manufacturing
Engineers (SME), and the Chairman (2018-2020) of Swedish
Production Academy. In 2020, he was elected one of the 20
Most Influential Professors in Smart Manufacturing by
Society of Manufacturing Engineers.
He received his PhD and MSc from Kobe University (Japan) in
1993 and 1990, respectively, and BSc in China in 1982. He
was an Assistant Professor of Kobe University and Toyohashi
University of Technology (Japan) prior to joining National
Research Council of Canada (NRC) in 1998, where he was a
Senior Research Scientist before moving to Sweden in 2008.
His research interests are presently focused on real-time
monitoring and control, human-robot collaboration, brain
robotics, digital twin, cyber-physical and sustainable
production systems. His research work has won one Best
Poster Award in Switzerland (2003), four Best Paper Awards
in Germany (2002), USA (2016), Serbia (2020) and Sweden
(2020), and two Outstanding Paper Awards in Mexico (2008)
and USA (2016). In 2021, he received the Best Paper Award of
Journal of Manufacturing Systems. He is also an eight-time
winner of NRC Institute Awards on Excellence and Leadership
in R&D, Multidisciplinary Collaborative Research, Global
Reach, and Outstanding People.
Professor Wang has published 10 books, 15 conference
proceedings and 32 journal special issues. He has authored
or co-authored in excess of 600 scientific articles in
archival journals, books, and peer-reviewed conference
proceedings in the above research areas. In addition to the
research work, he is actively engaged in various committee
and community activities. He was the Conference Chair of
FAIM 2004 and CIRP CMS 2018, a member of Grant Selection
Committee (GSC-20 for Industrial Engineering) of Natural
Sciences and Engineering Research Council of Canada
(2004-2007), the Chair of the Scientific Committee of
NAMRI/SME during 2016-2018, and a member of Technical
Committee 282 (Machinery Safety) of Swedish Standards
Institute (2014-2017). He is the Editor-in-Chief of
International Journal of Manufacturing Research,
Editor-in-Chief of Journal of Manufacturing Systems,
Editor-in-Chief of Robotics and Computer-Integrated
Manufacturing, Editor of Journal of Intelligent
Manufacturing (2007-2019), Associate Editor of International
Journal of Production Research, and an Editorial Board
Member of other 17 international journals. He is also a
Fellow of The Canadian Academy of Engineering (CAE), a
Fellow of The International Academy for Production
Engineering (CIRP), a Fellow of SME, a Fellow of ASME, and a
registered Professional Engineer in Canada.
Title: A Deep Dive into Human-Robot Collaboration: Status and Trends
Abstract: Human-robot collaboration has attracted increasing attentions, both in academia and in industry. For example, in human-robot collaborative assembly, robots are often required to dynamically change their pre-planned tasks to collaborate with human operators in a shared workspace. However, the robots used today are controlled by pre-generated rigid codes that cannot support effective human-robot collaboration. In response to this need, multi-modal yet symbiotic communication and control methods have been developed. These methods include voice processing, gesture recognition, haptic interaction, and brainwave perception. Deep learning is used for classification, recognition and context awareness identification. Within this context, this seminar provides an overview of the current status of human-robot collaboration including its classification, definition and characteristics. At the end of the seminar, remaining challenges and future research directions will be highlighted.
Prof. Xun William Xu
Auckland University,
New Zealand
Dr. Xu joined the Department
of Mechanical Engineering, The Univeristy of Auckland in
1996 after obtaining a PhD from the University of Manchester
(then, UMIST), UK. He has been working at the University of
Auckland as a Lecturer, Senior Lecturer, Associate Professor
and now Professor. His teaching at the Department of
Mechanical Engineering cuts across a number of fields, e.g,
mechanical engineering design, manufacturing systems,
advanced manufacturing technology, manufacturing information
systems and advanced CAD/CAM/CNC.
Professor Xu's main research focuses are on computer-aided
design, process planning and manufacturing, in particular
STEP-compliant CNC (STEP-NC), cloud manufacturing, smart
manufacturing and Industry 4.0.
Professor Xu set up the first Industry 4.0 laboratory in New
Zealand, Laboratory for Industry 4.0 Smart Manufacturing
Systems (LISMS), and leads one of top research teams (IIMS
research group ) in the world working in the field of
STEP-compliant design and manufacturing. In 2020, Professor Xu was listed as one of the 20 most
influential professors in smart manufacturing in the world.
Title: Digital Twin – the State of the Research
Abstract: The technological fundamentals of Industry 4.0 are unpinned by that of the Internet of Things and exist in various forms of Cyber-Physical Systems, where “systems” can be products and machines. A key element in a Cyber-physical System is Cyber Twin or otherwise commonly known as Digital Twin. This talk gives an overview of the background, concept and major technologies, in particular digital models, digital shadows and digital twins for smart manufacturing solutions. The focus is on digital twin and one of the key elements in a digital twin is the information model. The talk also touches upon the latest development at the International Organization for Standardization (ISO) concerning digital twin framework for manufacturing. Some case studies will be presented with an aim to demonstrate how digital twin solutions can help industry stay competitive.