The Indian Government has set an ambitious target of increasing the contribution of manufacturing output to 25% of GDP by 2025 and providing employment to 100 million people in the manufacturing sector.
Smart manufacturing is the next global revolution in manufacturing, underpinned by self-aware machines that communicate with each other and make decisions to improve system performance. But there are significant challenges in upgrading existing manufacturing equipment with intelligence capabilities and in building a skilled workforce to operate in an increasingly digital environment.
This Newton-Bhabha funded project has developed a 'cyber twin' approach to provide legacy equipment with intelligence. A cyber twin is a digital representation of a piece of manufacturing equipment, and is able to replicate the equipment’s behaviour and make decisions on its behalf through embedded data analytics and optimisation algorithms. The approach used in the project makes it convenient to capture data through a manual but standard and user-friendly interface, making it viable for legacy machines. In addition, data can also be collected through externally mounted sensors, embedded sensors, and/or the machine controllers.
This new approach has been developed and tested in collaboration with Indian manufacturing companies, providing research opportunities for 30 undergraduate and postgraduate students from around India. These smart manufacturing technologies will see benefits to manufacturing industry in both India and the UK, particularly small and medium enterprises embarking on their journey towards Digital Manufacturing.
“There has been tremendous advancement in the area of digital manufacturing. However, small and medium enterprises have been slow in adopting digital technologies primarily due to low level of advanced automation and the legacy nature of their equipment. This project takes a radically new approach to low-cost digitisation that will enable those companies to ensure they get on to the journey towards digital manufacturing and improve their competitiveness and productivity. "
Dr Ajith Parlikad
Building Capacity in Collaborative Research for Advanced Manufacturing
Lead PI: Dr Ajith Parlikad, Institute for Manufacturing at the University of Cambridge
Lead PI: Dr Bhupesh Lad, Indian Institute of Technology Indore in Madhya Pradesh, India
Project partner: Royal Academy of Engineering
Federation of Indian Chambers of Commerce and Industry