Sanofi
Sanofi optimizes predictive maintenance with AVEVA PI System
Sanofi Toronto was operating aging assets under a time-based maintenance strategy that regularly caused delays and unexpected failures. The site took four to seven days to identify the root cause of an incident, while data sources remained siloed and manual processes hampered productivity. The pharmaceutical group deployed AVEVA PI System, complemented by Quartic.ai analytics, to adopt a reliability-centered predictive maintenance approach. The platform integrates vibration and ultrasonic sensors on critical assets, feeding anomaly detection models and a risk monitoring dashboard used to assess whether a new batch can start. The results speak for themselves: a 25% reduction in preventive maintenance costs, lower cost of goods sold, productivity hours regained and upskilled engineering teams. Sanofi now aims for a 35% reduction in predictive maintenance costs by 2025 and a global rollout of this data-driven approach.
FAQ
How does AVEVA PI System support predictive maintenance in the pharmaceutical industry?
Sanofi Toronto deployed AVEVA PI System combined with Quartic.ai analytics to move from time-based maintenance to reliability-centered predictive maintenance. The platform integrates vibration and ultrasonic sensors on critical assets, feeds anomaly detection models and gives engineers a real-time view of equipment health. For a pharmaceutical manufacturer where every shutdown directly affects the supply of vital medicines, this predictive transformation becomes strategic.
How can preventive maintenance costs in a pharmaceutical plant be cut by 25%?
Sanofi cut its preventive maintenance costs by 25% thanks to AVEVA PI System and is targeting a 35% reduction through predictive maintenance by 2025. The traditional approach, based on fixed time intervals, generates too much unnecessary maintenance (healthy equipment) or maintenance that comes too late (drifting equipment). Managing by actual condition using real-time data makes it possible to intervene at the optimal moment, neither too early nor too late. Across an aging asset base, these cumulative savings are considerable.
How does AVEVA PI System help validate the start of a pharmaceutical batch?
Sanofi uses a risk monitoring dashboard powered by AVEVA PI System to assess whether critical assets are fit to start a new pharmaceutical batch. The platform consolidates vibration, ultrasound, process parameter and maintenance history data into an operational risk score. This data-driven approach replaces manual assessment (4 to 7 days to identify the root cause of an incident) with an instant, objective decision, speeding up the production rate without compromising quality.
How can data silos be broken down at a pharmaceutical site with AVEVA?
Before AVEVA PI System, operational data at Sanofi Toronto was siloed in separate applications, and manual processes held back productivity. The platform contextualizes and unifies these heterogeneous sources in a common repository accessible to maintenance, quality, production and engineering teams. Breaking down these silos speeds up incident resolution, democratizes analysis and upskills teams. It is both a technological and an organizational transformation.
How does AVEVA PI System support a global rollout in pharma?
Sanofi is aiming for a global rollout of its predictive maintenance approach based on AVEVA PI System. The platform is designed to scale to dozens of industrial sites, with reusable data models and a cloud-ready architecture. For a pharmaceutical group present in dozens of countries, this ability to standardize while respecting local specificities (regulations, equipment, languages) is essential. AVEVA thus becomes the foundation of a large-scale industrial digital transformation in the life sciences.