Volvo Group uses LoRaWAN for predictive maintenance in Lyon factory


Fin is a former junior editor at TechForge.

Swedish vehicle manufacturer Volvo Group has built a new Internet of Things (IoT) network for its engine factory in the French city of Lyon.

The network will be used to monitor the health of autonomous guided vehicles (AGVs) being produced in the factory in a bid to reduce operational costs and improve maintenance.

Volvo Group says that AGVs offer more flexibility in the company’s engine manufacturing process when compared to a traditional, fixed production line.

But due to some AGVs relying on 24-volt batteries that can cut short when voltage dips below 22 volts, the factory is currently resulting in a production loss of around two engines per week.

The company’s IoT team attempted to use a wireless technology solution to monitor AGVs’ health and avoid stops that disrupt the manufacturing process. But the team discovered that the 2.4 gigahertz band was already taken up by other critical functions.

The IoT team decided on LoRaWAN, a long-range wide area network built to connect battery-powered IoT devices. Volvo Group said that LoRaWAN works well in manufacturing environments due to its long-range resistance to interference and a secure network architecture.

Julien Bertolini, principal solution architect of IoT at Volvo Group Digital & IT, said: “Implementing a radio infrastructure in our factory was a challenge, and we wanted to have a LoRaWAN network connected directly to our secure Ethernet network to avoid any cloud dependence.”

“So, we have selected a multitech industrial grade LoRa Gateway, with some edge computing capabilities and robust cybersecurity features to successfully qualify it through a complete IT audit.”

The predictive maintenance system utilised LoRaWAN sensors on each AGV, a private LoRaWAN network, and a maintenance platform running on PTC Thingworx that includes a mobile app.

Volvo Group has also added LoRaWAN sensors to its Lyon factory for a range of other use cases, including temperature and humidity checks for painting processes to ensure coating quality as well as detecting filter clogs through pressure difference sensors.

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