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06 Apr 2022

Ford MPN

Ford MPN

 

 

 

 

 

Challenges

  • Speeding up EV manufacturing
  • Handling welding data
  • Transforming its vehicle production line

Solution

  • Use of image capture and AI during welding
  • Connection of the machines to process data
  • Use of SIMs on all devices to ensure monitoring

Results

  • Elimination of downtime and delays
  • Real-time support from 5G-connected experts
  • Possibility to detect and correct errors during welding

5G-enabled EV manufacturing: Ford and Vodafone create the car factory of the future

The customer and the challenge

The future is green and digital 

Ford Motor Company is committed to leading the way for the automotive industry towards a more sustainable future and the use of 5G to set the stage for its digital transformation.  The company wanted to connect and improve its production techniques to move away from internal combustion engine technology and adopt plug in and fully electric vehicles. “In the future, we’ll need more flexible facilities to be able to quickly reconfigure as there is likely to be a lot more customisation in cars” says Chris White, Electrification and Global Engineering Alignment Manager at Ford. 

More data bring new challenges

Ford has decided to introduce a new laser welding technology to support the manufacturing of electric vehicles. The main challenge was handling the vast amount of data collected during the welding process. The motors and batteries used for EVs require thousands of welds and the whole process can generate up to half a million pieces of data per minute. Ford needed reliable high-speed wireless connectivity to ensure continuous monitoring and maintenance by connecting these machines to process the data.

Revolutionising EV manufacturing with 5G

Vodafone has already helped Ford build a pilot line with 5G to allow the company to get an insight into its potential in EV manufacturing. Vodafone, The Welding Institute and other partners are now helping Ford co-create the "Factory of the Future" using a 5G Mobile Private Network (MPN) at Ford’s Dunton Technical Centre in Essex as part of the 5G Testbeds & Trials programme supported by the UK government. Our goal is to help Ford redeploy their assets into factories ready to speed up EV manufacturing.

How we helped them

Creating a data-driven welding process

Ford can now capture images and use AI during and after the welding process. If a weld isn’t particularly good, the system can easily re-weld the affected part whilst it’s still in the machine. As this process creates terabytes of data, our high-bandwidth, ultra-low latency 5G MPN is essential for Ford to send or restore the data, speed up the assembly and bring greater precision. 5G will make it possible for the company to deploy automated guided vehicles and AI systems in the future.

No time for failures

Vodafone 5G MPN helps Ford optimise maintenance to eliminate unnecessary downtime in the production line and delays in manufacturing. The data collected during the laser process allow the operators to identify build-up of heat in their lenses and replace them before they fail. Ford uses the HoloLens system to get real-time support from 5G-connected experts to diagnose and fix the problem. 5G also enhances security by allowing Ford to use SIMs on its devices to ensure continuous monitoring of its dedicated network and protect it from external threats.

 Using 5G to turn your ambitions into reality

Our solution relies on Ford’s existing technologies and helps it enhance collaboration between its teams, assets and suppliers. “The manufacturing engineering team is at the centre of the change of EV Powertrain in Europe, and this team needs to work with people like Vodafone, so we can do that as efficiently as possible” says Lee Turner, Powertrain Manufacturing Engineering Director at Ford. Our partnership combined with the power of 5G, edge computing and AI will help Ford transform their vehicle line-up over the next 10 to 15 years.

Why choose us?

High-bandwidth, ultra-low latency 5G MPN

Secure connection thanks to a dedicated network

Data-driven predictive maintenance

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