Event link: bit.ly/ai4g_day2


Manufacturing is fast moving towards smart factories adopting Industry 4 technologies.
AI/automation is one of the 4 grand challenges stated in the UK Industrial Strategy White Paper
(2017). It was reported that AI and automation could increase industrial efficiency by up to 30% and
mitigate disruptions (‘The Future of Manufacturing’, The Telegraph, 2018). Robots, simulation and
digital twins could keep production operating and remotely controlled when employees are ill or not
able to be on-site during disasters like Covid-19. In this presentation, Prof Gao will present data to
show the trends, opportunities and challenges of smart factories, focusing on the application of AI,
robotic automation and information/knowledge management in high value manufacturing industry.
He will also introduce some research and innovation projects carried out by his Group with industry.
Prof Gao will discuss with delegates the future implementations of Industry 4 technologies, through
the introduction of a proposed large-scale collaborative project ‘Smart-Factory’, which focuses on
the manufacturing of low volume, high value and/or specialised products. Manufacturing of these
high-end products still very much relies on manual operations which are the main causes of high
cost, low productivity and obstacles to digitisation. The overall objective of the Smart-Factory
project is to develop, implement and test advanced digital, robot, Internet of Things (IoT) and AI
technologies to automate current manual processes, in order to increase efficiency, productivity,
high value knowledge-intensive jobs, improve competitiveness, safe operations and resilience in
times of disruptions. Comments and recommendations from the delegates will be discussed for
future research, development and industrial applications.

Speaker Bio:
James Gao holds the Medway Chair of Manufacturing Engineering at the University of Greenwich
(UK). He is currently the director of research (School of Engineering) and leads the Mechanical,
Manufacturing and Management research group. Prior to his current position, he was a
lecturer/senior lecturer at Cranfield University (1993-2006), and a research fellow at Loughborough
University (1989-1993). He obtained BSc in mechanical engineering from Dalian Institute of
Technology in 1984, MSc and PhD from the University of Manchester Institute of Science and
Technology (UMIST) in 1987 and 1989 respectively. He published over 250 papers in international
journals and conferences, and directed a large number of research and innovation projects in
automation, AI and robots in smart manufacturing, information and knowledge management, digital
manufacturing and product life-cycle management. Prof Gao chaired/co-chaired several international
conferences and is an associate editor/member of the editorial boards of several international