Case Study: Schneider Electric achieves predictive maintenance and reduced downtime with Senseye PdM

Schneider Electric - Customer Case Study

Schneider Electric, a global leader in energy management and automation, faced machine-health and unplanned downtime issues at its Le Vaudreuil “lighthouse” factory in France. The company needed a predictive maintenance solution that could use existing machine data, be simple for operators to adopt, and deliver a fast return on investment. Vendor Senseye, using its Senseye PdM product, was selected to help address the challenge.

Senseye implemented a predictive maintenance setup that combined temperature and current sensors with data stored in Aveva Insight and analyzed it in Senseye PdM using AI and machine learning. This enabled early alerts before failures, improving OEE by 7 points and reducing maintenance costs on a single machine by 20%. The success led to broader rollout across Schneider Electric’s Global Supply Chain business unit, delivering faster uptime gains and deeper collaboration between Senseye and Schneider Electric.

Schneider Electric

Cyril Perducat

EVP IoT & Digital Offers