ABSTRACT

PHILIPS DRACHTEN: A LEADER IN PREDICTIVE MAINTENANCE

Philips Drachten provides an excellent real-world example of successfully implementing predictive maintenance. Founded in 1950 as a small shaver factory, Philips Drachten has grown into one of Philips’ biggest manufacturing and innovation sites in Europe. The highly automated factory now produces millions of shavers, mother and childcare products, and oral healthcare items per week.

With such high production volumes, reliability is crucial. Maintenance is at the core of Philips Drachten’s operations. To optimize maintenance, Philips transitioned from traditional reactive approaches to proactive predictive and forward-looking techniques. A key tool in this shift is the predictive maintenance platform Sibyl, developed by Atlantis Engineering.

Sibyl has been implemented across Drachten’s complex cold forming production lines and its 270 robots. By analyzing real-time sensor data, Sibyl gives operators, technicians, and engineers helpful insights to avoid downtime. Examples include monitoring cold forming machinery to detect problems early and tracking robot torque/position to pinpoint mechanical issues before they happen.

When Sibyl predicts a potential breakdown, it sends alerts to maintenance teams up to 72 hours in advance. With precise data on emerging issues—even down to specific robot joint coordinates—technicians can proactively fix problems with minimal effect on production.

Philips Drachten provides a model for manufacturers seeking to enhance reliability through data.