The longer version of the closing event can be found here
Project “Digital Twin Modelling for Automation, Maintenance and Monitoring in Industry 4.0 Smart Factory” is now completed with a final event, the Workshop on Digital Twin and Industrial Automation on the 12th January 2022. The hybrid workshop is being jointly organised by the two partners London Digital Twin Research Centre (Middlesex University London, UK) and Indian Institute of Information Technology (IIIT) Sci city (India). Key outcomes of the project include a developed digital twin of the Festo/Siemens smart factory, 4 dissemination workshops, 2 panel/special sessions and 2 keynote speeches at conferences, 16 research papers and 16 postdoc RAs and students being trained from the project, as well as new partnerships formed with industrial partners and organisations. For more details please join us at the event via this direct link
Structural health monitoring and digital twin modelling are the timely research areas in structures that attract interests worldwide. The Newton Fund project teams from the London Digital Twin Research Centre and the University of Transport and Communications (Vietnam) continue to extend the impact beyond the project by organising the 2nd International Conference on Structural Health Monitoring and Engineering Structures (SHM&ES 2021) during 13th-14th December 2021.
The London Digital Twin Research Centre has been successful in two further bids to the British Council’s Going Global Partnerships programme. The two projects focus on DT research and knowledge transfer that is strongly located in our University strategy themes and have at their core, the UN sustainability goals.
The new projects are:
Project 1 (Vietnam, 2022-2024): “Urban Resilience in Agriculture Through Highly Automated Vertical Farming in Vietnam and the UK”
Challenges in agricultural product supply during COVID-19 pandemic brought the idea of adapting a highly automated vertical farm system to the urban context. This project is international research that is aimed at sustainability issues arising from food resilience needs. The project will install two greenhouses to support vertical farming and use DT/IoT smart solutions to control and monitor production. Alongside the technical work, there is a substantive piece of educational work on vertical farming with young people. The project is also an example of collaboration with the Business School. We are collaborating with Van Lang University from Vietnam.
Following the success of the Newton Fund project on Digital Twin for Structural Health Monitoring , the project team between London Digital Twin Research Centre and University of Transport and Communications (Vietnam) have teamed up again to extend and advance the developed DT model for improving the monitoring and maintenance of important infrastructure in Vietnam and the UK.
The project will again be led by the two investigators: A/Prof. Thanh Bui (UTC) and Prof. Huan Nguyen (LDTRC) and will last between 2022 and 2024. The funder is the VinGroup (Vietnam) under the VinIF funding scheme
By Huan Nguyen, William Davis, and Ciaran Sinclair
Formula 1 (F1) is a billion-pound sport that blends between entertainment (a show) and competition. It is arguably the most advanced, high-tech sport in the world. Each F1 team’s factory consists of 1000+ employees who works day and night to just produce two cars that only two drivers can drive them. It costs millions of pounds to produce a racing F1 car and the costs of development and operations throughout the year add up to further hundreds of millions. As many as 3000+ car parts are produced each week by each team. Teams invest heavily to just happily outpace other teams’ cars by a tenth of a second a lap when racing in a circuit of over 5km.
The two key things for a winning team: i) produce a very good racing car; and ii) be slick and efficient in operation as a team. Both of these can be decisively supported by one key technology: Digital Twin, because of its largely data-driven environment and the decision making is often made in real-time manner (in pressurised racing conditions).