Leverage Esri's platform, the leader in geographic information systems, along with Dataiku’s end-to-end data science platform to address real-world issues.learn more
Today, predictive maintenance is widely considered to be the obvious next step for any business with high-capital assets, harnessing machine learning to control rising equipment maintenance costs. Predictive maintenance takes data from multiple and varied sources, combines it, and uses machine learning techniques to anticipate equipment failure before it happens.
Essilor is the world’s leading ophthalmic optics company which designs, manufactures, and markets a wide range of lenses to improve and protect eyesight. Essilor employs 67,000 people worldwide; it has 34 plants, 481 prescription laboratories and edging facilities, as well as four research and development centers around the world. In its dedication to ensure factories are efficient, innovative, and compliant with high quality standards, Essilor has a Global Engineering (GE) service that is responsible for the implementation and standardization of production processes.
Seeing that one of their goals is to find ways to better answer consumer and business needs, the GE team was facing the challenge of improving processes and performance of the surfacing machines to significantly improve their production by using the increasing volume of data.