Advances in Intelligent Manufacturing and Robotics (eBook)

This book presents selected peer reviewed articles from the International Conference on Intelligent Manufacturing and Robotics (ICIMR 2023) held on 22-23 August at the Xi'an Jiaotong-Liverpool University in China. The book deliberates on the key challenges, engineering and scientific discoveries, innovations, and advances in intelligent manufacturing and robotics that are non-trivial through the lens of Industry 4.0. In this book, traditional and modern solutions that are employed across the spectrum of various intelligent manufacturing and robotics contexts are discussed. The book provides an insightful view on the current trends, issues, mitigating factors as well as proposed solutions.

Dr. Andrew Tan received his MEng in Mechanical Engineering in 2013 from The University of Nottingham. Developing a measurement tool for the Water-Energy-Food Nexus of Malaysia based on systems thinking, he has successfully obtained his PhD from the same university in 2018. Andrew was a manufacturing engineer in Agilent Technologies and Motorola Solutions, where he ensured the smooth development and sustenance of product manufacturing lines. In these positions, he has led extensive manufacturing projects across different teams, time zones, and varying concurrent engineering phases.

Dr. Fan Zhu received her Ph.D. degree in Computer Science from The University of Hong Kong in 2021. In 2016, she obtained her B.Eng. degree in Computer Science and Technology from Shandong University. She does research in intelligent robotic grasping and manipulation via sensor fusion. which includes robotic manipulation and human-robot interaction. Her current research interests include computer vision, AI-driven robotic manipulation, autonomous navigation, and sensor fusion in robotics.

Dr. Haochuan Jiang is currently an assistant professor at the School of Robotics in the Xi'an Jiaotong-Liverpool University Entrepreneur Collage (Taicang). He received his Ph.D. degree from the Department of Electrical Engineering and Electronics at the University of Liverpool. In 2013. Dr. Haochuan JIANG took the role as the new-tech researching engineer at the Commercial Robotic R&D Center of the ECOVACS Robotic (Suzhou) Co. Ltd., in 2013. He also served as an algorithm and model researcher in the Platform and Content Group of the Tencent Tech., Shenzhen in 2019. Before joining XJTLU, he worked as a post-doctoral research associate at the School of Engineering of the University of Edinburgh from 2019 to 2020. 

Dr. Kazi Mostafa is an assistant professor in the School of Intelligent Manufacturing Ecosystem at Xi'an Jiaotong-Liverpool University, China. He received his BSc. in Mechanical Engineering from Chittagong University of Engineering and Technology, Bangladesh, in 2006 and his MEng degree in Manufacturing Management from the University of South Australia in 2009. He received his PhD (Mechanical and Electro-Mechanical Engineering) from National Sun Yat-sen University, Taiwan (ROC) in 2015. His research interests include image processing and robotics.  

Dr. Eng Hwa Yap is the Dean of the School of Intelligent Manufacturing Ecosystem and the School of Robotics at Taicang Campus. He leads the strategic development of both schools. Eng Hwa also leads the initial School of CHIPS as Acting Dean. He was formerly an Associate Dean in the Faculty of Transdisciplinary Innovation (now TD School) at University of Technology Sydney in Australia, where he provided strategic leadership in, and oversight of, teaching and learning management and operations in the faculty. He received his PhD in Mechanical and Marine Engineering from University College London and completed his undergraduate degree in Marine Technology at the University of Plymouth, both in the United Kingdom. He has held academic leadership positions across several institutions in Australia and Malaysia. His research focuses on curated multidisciplinary and mixed approaches of inquiry to understand and address complex problems surrounding technology, environmental sustainability, and future energy systems.

Dr Leo Chen obtained his PhD in Mechanical Engineering from University of Glasgow, in 2010. He has been leading a few research grants in artificial intelligence, industry 4.0, high-performance computing, robotics and autonomous systems, and their applications in multi-disciplinary contexts. His research interests are in the areas of robotics, digital manufacturing, and industry 4.0, which demonstrates significant research and grant potential in engineering and cross-disciplinary applications.

Dr Lillian J. A. Olule received her PhD in Electrical and Electronic Engineering from University of Nottingham Malaysia. Her current research interests are in the areas of antennas and microwave systems and their energy harvesting applications, energy harvesting for biomedical applications and energy harvesting applications of sustainable structural materials.

Dr. Hyun Myung obtained his PhD in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST). He was a Senior Researcher with the Electronics and Telecommunications Research Institute, Daejeon, from 1998 to 2002, CTO and the Director with the Digital Contents Research Laboratory, Emersys Corporation, Daejeon, from 2002 to 2003, and a Principle Researcher with the Samsung Advanced Institute of Technology, Yongin, Korea, from 2003 to 2008. Since 2008, he has been a Professor with the Department of Civil and Environmental Engineering, KAIST, and he has served as the Chief of the KAIST Robotics Program. From 2019, he is a Professor with the School of Electrical Engineering. His current research interests include autonomous robot navigation, SLAM (simultaneous localization and mapping), spatial AI, machine learning, and swarm robots.

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This book presents selected peer reviewed articles from the International Conference on Intelligent Manufacturing and Robotics (ICIMR 2023) held on 22-23 August at the Xi'an Jiaotong-Liverpool University in China. The book deliberates on the key challenges, engineering and scientific discoveries, innovations, and advances in intelligent manufacturing and robotics that are non-trivial through the lens of Industry 4.0. In this book, traditional and modern solutions that are employed across the spectrum of various intelligent manufacturing and robotics contexts are discussed. The book provides an insightful view on the current trends, issues, mitigating factors as well as proposed solutions.