Preparing Students for Successful Industrial Collaborations in Engineering (Work in progress)
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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June 26, 2024
- Conference Session
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College Industry Partnerships Division (CIP) Technical Session 1
- Tagged Division
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College Industry Partnerships Division (CIP)
- Tagged Topic
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Diversity
- Page Count
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14
- DOI
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10.18260/1-2--47867
- Permanent URL
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https://peer.asee.org/47867
- Download Count
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75
Paper Authors
Chun Kit Chan The University of Hong Kong
Mr. Ryan Chun Kit Chan is a Senior Technical Assistant in the Tam Wing Fan Innovation Wing, Faculty of Engineering at the University of Hong Kong after graduation. Before graduation, Ryan served as an undergraduate research assistant in Innovation Wing and has involved in the design and implementation of a world-record-holding robotic fish. Ryan received his Bachelor's degree in Mechanical Engineering from the University of Hong Kong. Ryan's research focuses on robotic systems, navigation, rapid prototyping methods, and integrating project-based learning experiences beyond the regular syllabus.
H.H. Cheung University of Hong Kong
Dr. H.H. Cheung is a Senior Lecturer in the Department of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He obtained his B.Eng., M.Phil., and Ph.D. degrees at the University of Hong Kong. Prior to joining the University of Hong Kong, he has worked in manufacturing and IT industries as a consultant for a number of years. He has gained substantial experiences in developing and managing RFID-based solutions, and the provision of consultancy services to implement RFID applications to various industries/enterprises. Dr. Cheung has also participated in a number of industrial application projects of RFID and IoT technologies, including RFID-based systems for product anti-counterfeiting, food processing management, manufacturing and logistics management of a global printing enterprise, governmental project for inventory management, and baggage management of a major international airport.
His research interests include CAD/CAM, Layered Manufacturing (3D Printing), Virtual Prototyping and Virtual Manufacturing, Smart Manufacturing, Product Development, Digital Twins, AI, IoT and Robotics applications.
Match Ko
University of Hong Kong
orcid.org/0000-0002-1219-213X
Dr. Match Wai Lun Ko is a Senior Lecturer and MSc(Eng) in Mechanical Engineering Programme Director in the Department of Mechanical Engineering, the University of Hong Kong. He is also fractionally appointed in Innovation Academy, Faculty of Engineering of HKU. Dr. Ko obtained his B.Eng and Ph.D. in Mechanical Engineering from the Hong Kong University of Science and Technology. Before joining HKU, he was an Assistant Professor in Nazarbayev University, Postdoctoral Fellow in the Hong Kong Polytechnic University, Visiting Scholar in the Chinese University of Hong Kong, Visiting Professor and Scholar in the University of Warwick. Dr. Ko’s research focused on the engineering education, biomechanics, biomedical image processing, biomechanical properties characterization, finite element modeling, design and fabrication of related medical device to assist the clinicians to preform disease diagnosis and decision making regarding screening of disease and treatment management.
Chun Kit Chui University of Hong Kong
Dr. Chun Kit Chui serves as the Director of the Tam Wing Fan Innovation Wing in the Faculty of Engineering at the University of Hong Kong (HKU). Innovation Wing aims to unleash students' creativity by entrusting them to spearhead ambitious innovation and technology projects that will shape the future. The iconic facility is located at the heart of the campus, offering 2400m2 of space with state-of-the-art resources and a supportive environment to enhance hands-on and experiential learning for undergraduate students.
He also holds the position of Senior Lecturer in the Department of Computer Science at HKU. His research interests include database and data mining, as well as pedagogical research in computing education. Dr. Chui has received several education awards, including the University Outstanding Teaching Award (Individual Award) at the University of Hong Kong for the 2015-16 academic year and the Faculty Outstanding Teaching Award (Individual Award) in the Faculty of Engineering for the 2012-13 academic year. Additionally, he has been honored with the Teaching Excellence Award in the Department of Computer Science for the academic years 2011-12, 2012-13, 2013-14, 2014-15, and 2015-16. Furthermore, he was a shortlisted candidate for the UGC Teaching Award (Early Career Faculty Member).
LEI YANG
The University of Hong Kong
orcid.org/0000-0002-3284-4019
Lei Yang is a lecturer of Innovation Academy of the Tam Wing Fan Innovation Wing under the Faculty of Engineering, The University of Hong Kong. Before that, he worked as a Research Officer at Centre of Transformative Garment Production from 2021 to 2023 and as a postdoctoral fellow at Department of Computer Science, The University of Hong Kong from 2018 to 2021. Dr. Yang received his Bachelor's degree and Ph.D. degree from Dalian University of Technology in 2012 and 2018, respectively. Dr. Yang's research interest includes Computer-Aided Design, Computer-Aided Engineering, and Geometry Modeling and Multimedia.
Abstract
This practice paper introduces a framework for preparing engineering students for industrial collaborations. Engaging engineering students in industrial projects provides them with valuable hands-on working experience in an authentic learning environment. However, industrial collaborations come with challenges among various stakeholders, including discrepancy in expected outcomes, limited support, and shortfall in contemporary technical knowledge and hands-on competency. To establish an effective industrial collaboration, the Faculty of Engineering at the University of Hong Kong has established the Tam Wing Fan Innovation Wing (a.k.a. the HKU Inno Wing) [1]. This center is designed to engage students in real-life projects, providing them with hands-on experience. We propose and implement the Inspire-Equip-Showcase (IES) framework to prepare students for successful industrial collaboration. In the 2023/24 academic year, a cohort of students underwent pre-collaboration training activities under IES with a focus on the theme of AI and robotics. The training covered fundamental competencies such as Robot Operating System (ROS), localization, auto-piloting, computer vision, object recognition, LiDAR control, and GPS. Following this training, these students were then paired with a local railway company, collaborating with professional engineers on the exploration of robotic solutions to address various maintenance challenges in modern railway operation. The practice paper analyzes students' written reflections collected during the pilot run of the IES framework in 2023/24, revealing the impact of the framework and its various learning components in preparing students for industrial collaboration. The insights from this study offer valuable lessons that can be applied to adapt to other technology domains in upcoming cohorts.
Chan, C. K., & Cheung, H., & Ko, M., & Chui, C. K., & YANG, L. (2024, June), Preparing Students for Successful Industrial Collaborations in Engineering (Work in progress) Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47867
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