Case Study: Essilor International achieves predictive maintenance and optimized component lifespan with Dataiku

Using Artificial Intelligence in a Predictive Maintenance Process to Improve Industrial Performance

Essilor International, the world’s leading ophthalmic optics company, needed to improve the performance of its complex surfacing machines and manage large, heterogeneous datasets to enable predictive maintenance across its Global Engineering service. To address this, Essilor International partnered with Dataiku and adopted Dataiku Data Science Studio (DSS) to rapidly explore, clean, and model varied machine data and accelerate development of ML-driven maintenance use cases.

Using Dataiku, Essilor International developed predictive maintenance models that indicate the optimal time to replace consumable components—extending component lifespan while preserving production quality—and deployed a Dataiku web application as a visual decision tool for operators. The initiative also spurred broader, international adoption of Dataiku across teams, improved cross-team collaboration, added a dedicated data-science resource, and paved the way for production model deployment, lab dashboards, and future deep-learning enhancements.

Essilor International

Cédric Sileo

Data Science Leader, Global Engineering