Case Study

Sanofi: Reduce preventative maintenance costs with predictive models

Sanofi: Reduce preventative maintenance costs with predictive models

Pages 4 Pages

Sanofi adopted AVEVA PI System™ and Quartic.ai to shift from reactive, time-based maintenance to a reliability-centered model. This digital transformation helped the company baseline asset performance, detect anomalies early, and use predictive models to reduce equipment failures. As a result, Sanofi cut preventive maintenance costs by 25%, improved productivity, and upskilled its teams. By integrating sensors, automating work orders, and scaling predictive analytics, Sanofi now targets a 35% cost reduction by 2025 and plans to expand its AI-driven maintenance strategy globally.

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