Case
Data-driven workshop improves decision-making.
The Norwegian public transport organisation Sporveien is on a digitalisation journey. The aim is a fully data-driven workshop, utilising the power of simulation, data analysis and condition-based monitoring to work more efficiently, challenge existing maintenance cycles to increase uptime and use less resources. Knightec Group is supporting Sporveien with expertise ranging from strategic planning, to software development and hardware analysis. And the cooperation is already paying off.
ClientSporveien
IndustryPublic
ServicesSoftware & CloudHardware & MechanicsProject & Change ManagementEmbedded & Electronics
Originally delivered by Semcon, now part of Knightec Group.
Background
A data-driven set-up enables the transition from periodic maintenance to condition-based monitoring. Most of us are used to periodic maintenance – after a predetermined number of miles or years, your car or machine signals that it needs service. However, condition-based monitoring is based on real-time data from sensors that track the condition of the product. The difference? Maintenance is enabled when needed rather than when scheduled.
Challenge
In a first joint project, Sporveien wanted to investigate if they could extend the life of the gearboxes in their underground carriages. This is a component that requires complex maintenance, regarding both specific tools and competencies. Would it be possible to prolong their maintenance cycles? Using sensor technology, the Knightec Group team collected data from the Oslo Metro traffic, which was then correlated with other measurements to create a simulation to understand the wear of gearbox bearings.
Extending asset lifetime through data-driven condition monitoring.
Based on simulation results, the maintenance interval for gearbox bearings could be extended from 16 to 57 years, significantly reducing the need for material usage and resource-intensive replacements. By avoiding scheduled replacements of gearbox bearings in underground carriages, Sporveien is estimated to save between NOK 200–300 million. Beyond challenging traditional lifespan assumptions, Knightec Group and Sporveien are also exploring new ways to monitor system health, including analyzing oil purity using advanced acoustic technology combined with machine learning algorithms.
In parallel, the condition of underground carriage doors—components that typically require frequent maintenance due to wear—is assessed using the same acoustic approach. By continuously monitoring each set of doors, maintenance can shift from reactive or scheduled to truly condition-based, improving both efficiency and reliability across the system.
New opportunities in a data-driven era
There are many benefits to a data-driven workshop set-up. It is a means to upgrade and streamline ways of working as well as challenge traditional maintenance cycles. Just imagine all the different components that could be monitored in a single underground train or tram! In the case of Sporveien, there are many more great possibilities ahead.
Delivered value
The solution enables a transition from time-based to data-driven maintenance, significantly extending asset lifetimes while reducing unnecessary interventions and costs. It improves operational reliability, minimizes downtime, and optimizes resource usage—ultimately creating a more efficient, predictive, and future-proof maintenance strategy.
