An open-access testbed to help manufacturers unlock the potential of 5G technology. The smart factory of tomorrow starts today

The Partners

5G Factory of the Future is delivered by a consortium of industrial and academic leaders from the global and UK manufacturing and telecommunications sectors. The project is part-funded by the Department for Digital, Culture, Media and Sport and is part of its 5G Testbed & Trials programme.

University of Sheffield - Advanced Manufacturing Research Centre
BAE Systems logo
IBM logo
Catapult Digital logo
aql logo
Fuuse logo
Machine Tool Technologies

5G Factory of the Future:
Transforming Manufacturing

This ground-breaking project is unlocking the potential of 5G technologies in manufacturing to
accelerate industrial digitalisation and support UK manufacturers on their journey to a smart,
productive and sustainable future.

A Northern Manufacturing Powerhouse

Transformative capability is needed if UK manufacturers are to thrive and survive. 5G Factory of the Future is helping sow the seeds of a 5G-enabled future by helping manufacturers across the North West to better understand the benefits of adopting 5G technologies. These benefits include: better insights, lower costs, higher margins, increased quality, reduced time to market and improved delivery times.

Our open-access industrial testbed is developing integrated solutions to address some of the key manufacturing challenges by deploying 5G technologies, using test cases such as robotic assembly, reconfigurable product assembly lines and distributed and shared virtual reality and augmented reality.

The testbed will help manufacturers unlock and realise the potential benefits that 5G technology can bring to their operations. The smart factory of tomorrow starts today.

  • Demonstration of cost-efficiency
  • Return on investment
  • Compatibility
  • Interoperability
  • Security
  • Tackling lack of 5G understanding and cultural barriers.
Two people reading from a clipboard

Industrial Applications

5G Factory of the Future has developed five use cases for 5G in manufacturing, delivering innovation with measurable outcomes.

Introducing Hybrid Reality Spaces

Challenge: Enabling real-time rich information and AI assistance to be exploited by people at the point-of-use; reducing cost of downtime, interpretation and uncertainty.

Result: Estimated reduction in travel costs (65%) and maintenance time (15%) arising from real-time, worldwide collaboration and increased ease of training and maintenance support.

Introducing Hybrid Reality Spaces

Real-time Monitoring and Adaptive Closed-Loop Control

Challenge: Reduce cost and time associated with defects and quality issues. Create a no-fault forward manufacturing system.

Result: Estimated 15-25% reduction in the number of defects, amount of waste generated and machine downtime arising from improved process precision and predictive maintenance strategies and fewer errors.

Real-time Monitoring and Adaptive Closed-Loop Control

Chain of Custody System (CCS)

Challenge: Increasing visibility across the supply chain network through all tiers for assets and products, guaranteeing operational efficiency and delivery to customers.

Result: Estimated 30% reduction in lost and damaged assets, improved schedule accuracy, and providing supply-chain transparency and real-time condition monitoring for assets tracked by the system.

Chain of Custody System (CCS)

Factory Ecosystem Monitoring (FEM)

Challenge: Reduce infrastructure and through-life operational costs via real-time, agile monitoring of critical production environments.

Result: Estimated 5-10% improved machine utilisation, reduction in energy use (10-15%) and maintenance time (20%), arising from performance optimisation and enhanced resource utilisation.

Factory Ecosystem Monitoring (FEM)

Digital Twin Track and Trace

Challenge: Enable a business-winning paradigm via data-driven digital twins through the product lifecycle.

Result: Estimated 15-20% machine utilisation improvement (reduction in idle time, improved scheduling) and factory efficiency, arising from data-driven decision-making, real-time asset location and inventory accuracy, efficient scheduling, asset performance optimisation, and improved predictive maintenance.

Digital Twin Track and Trace

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Supported By

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