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5G Era Project Work Published Online In Paper

Wed, 24 April, 2024

Preliminary findings from the 5G-ERA project have been published as part of a paper that is now available online at Science Direct.

The paper, ‘Exploiting Extended Reality under the Manufacturing as a Service Paradigm,’ has been co-authored and includes research from representatives from TWI Ltd as well as CAL-TEK Srl of Italy, the University of Calabria’s Department of Mechanical, Energy and Management Engineering, the Hellenic Telecommunications Organization (OTE) S.A. of Athens, Greece, the University of Bedfordshire’s School of Computer Science, HAL Robotics Ltd of London, England, and Cranfield University’s Centre for Digital Engineering and Manufacturing, School of Aerospace, Transport and Manufacturing.

The advent of Industry 4.0 / Industry 5.0 and novel concepts including Big Data, Blockchain, Digital Twin, the Internet of Things (IoT), and Augmented and Virtual Reality have delivered a wealth of potential new opportunities for the manufacturing sector, along with some new challenges.

These innovations have helped to make Manufacturing-as-a-Service (MaaS) an emerging concept, allowing users to request on-demand manufacturing. In addition, Cloud Computing has increased the flexibility of manufacturing services to create Cloud Manufacturing, while the convergence of Mixed Reality (MR), Augmented Reality (AR), Virtual Reality (VR) has created the umbrella of Extended Reality (XR) to revolutionise training, maintenance, safety and much more.

This paper proposes an XR-based architecture which aligns with the MaaS concept to implement a Mixed Reality application to support on-site operations. The is also an investigation of the potential implementation of Virtual Reality applications for the off-site operator, and the use of the 5G-ERA middleware to exploit the potential of the MaaS paradigm.

You can see the article in full, here.

Find out more about 5G here and discover more about the 5G-ERA Project here.

 

The 5G-ERA project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 856691

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