Spatio-temporal synchronisation for human-cyber-physical assembly workstation 4.0 systems

Abstract

Assembly workstation converges various resources, typically including humans to carry out parts combination activities with the performances determined by the interactions among the resources. In the Industry 4.0 (I4.0) era, the penetration of emerging technologies leads to the intelligent networking of hyper objects with hyper-automation and hyper-connectivity that fundamentally change the organisation of an assembly workstation and brings it into the era of ‘Assembly Workstation 4.0 (AW4.0)’. However, the volatile market demands and the autonomy of the hyper objects with human integration bring new challenges in reducing the uncertainty and complexity of AW4.0 systems. In order to achieve an effective and efficient orchestration among hyper objects by fully harnessing enabling technologies of I4.0, a humancyber- physical system (HCPS) framework for AW4.0 systems is proposed to support the intelligent networking of hyper objects and to leverage the strengths and compensate the limitations of humans. Based on this, a spatio-temporal synchronisation (ST-Sync) strategy is introduced to achieve coordinated decision-making with consideration of customer requirements and spatio-temporal constraints of hyper objects with enhanced flexibility and responsiveness. Finally, a full-scale prototype is developed, and a real-life case is used to validate the potential benefits of AW4.0 systems in the overall performance improvement.

KEYWORDS:

• Smart Manufacturing
• cyber-physical system
• human-cyber-physical system
• spatio-temporal synchronisation
• assembly 4.0
• assembly workstation 4.0

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by the National Key Research and Development Program of China (2019YFB1705401), the 2019 Guangdong Special Support Talent Program-Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), and the National Key Research and Development Program of China (2018YFB1702803).

Notes on contributors

Shiquan Ling

Shiquan Ling received the B.Eng. and M.Sc degrees in mechanical engineering from Shenzhen University, Shenzhen, China, in 2009 and 2013, respectively. He is currently working towards a Ph.D. degree in industrial and manufacturing systems engineering from the University of Hong Kong. His research interests include Industry 5.0, Human-Cyber-Physical System, manufacturing synchronization and smart factory.

Daqiang Guo

Daqiang Guo received the B.Eng. and M.Sc degrees in mechanical engineering from Southwest Petroleum University, Chengdu, China, in 2013 and 2016, respectively, and the Ph.D. degree in industrial and manufacturing systems engineering from the University of Hong Kong, Hong Kong, in 2021. His research interests include the Internet of Things and digital twin-enabled intelligent manufacturing systems, and Operations Research (mixed-integer programming, constraint programming, reinforcement learning) for complex industrial systems.

Yiming Rong

Yiming Rong received Ph.D. degree in mechanical engineering from the University of Kentucky, Lexington, KY, USA, in December 1989. He is the Chair Professor and the Head of the Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China. He was a tenured Professor with Worcester Polytechnic Institute (WPI), Worcester, MA, USA, and was voted “John W. Higgins Professor of WPI” due to his outstanding contribution to scientific research. From 2010 to 2015, he was a Professor of Mechanical Engineering with Tsinghua University. He has presided over 50 scientific research projects, funded by the National Science Foundation, the Air Force Basic Research, the Department of Energy and other federal agencies and major manufacturing companies (GM, Ford, Caterpillar, P&W, GE, and Ingersoll). He has presided (joined) over ten major scientific research projects which are from the Natural Science Foundation of China, 973 Project, 863 Project, National Major Projects, and Industrial cooperation projects. He has published two academic books, and more than three hundred technical papers. His research area includes precision machining technology, modeling and simulation of metal materials processing, production planning, and tooling technology for optimization and manufacturing system. Dr. Rong is a Fellow of ASME.

George Q. Huang

George Q. Huang received the B.Eng. degree in mechanical engineering from Southeast University, Nanjing, China, in 1983, and the Ph.D. degree in mechanical engineering from Cardiff University, Cardiff, U.K., in 1991. He is the Chair Professor and the Head of the Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong. He has conducted research projects in the field of physical Internet (Internet of Things) for manufacturing and logistics with substantial government and industrial grants. He has published extensively, including over two hundred refereed journal papers in addition to over two hundred conference papers and ten monographs, edited reference books, and conference proceedings. His research works have been widely cited in the relevant field. Dr. Huang serves as an associate editor and an editorial member for several international journals. He is a Chartered Engineer, a Fellow of ASME, HKIE, IET, and CILT, and a member of IIE.