PreMa4MM - Predictive Maintenance for Mobile Machinery

Today’s non-road mobile machinery (NRMM), such as agricultural and construction equipment, generates a constant stream of data through numerous sensors. Thanks to the J1939 standard for CAN networks, this information is relatively easy to retrieve, offering enormous opportunities for operational and strategic insights. Yet the practical application of this sensor data remains severely underutilized, and unplanned machine downtime continues to be a critical cost factor that directly puts pressure on margins.

The PreMa4MM project introduces predictive maintenance to the non-road mobile machinery sector, building on the underutilized volume of machine data that such modern machines already generate. By applying knowledge of data capture and probabilistic machine learning to real-world applications and demonstrating the economic benefits, the project aims to enable companies to increase their operational efficiency and minimize unexpected machine downtime.