Dataiku Case Studies Improving Manufacturing Processes with Essilor
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Improving Manufacturing Processes with Essilor

Improving Manufacturing Processes with Essilor - Dataiku Industrial IoT Case Study
Analytics & Modeling - Predictive Analytics
Healthcare & Hospitals
Predictive Maintenance
Data Science Services

Seeing that one of their goals is to find ways to better answer consumer and business needs, the Global Engineering (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.

"We wanted a data science platform that would allow us to solve our business use cases very quickly. Thanks to Dataiku and its collaborative platform, which is agile and flexible, data science has become the norm and is now used more widely within our organization and around the world," said Cédric Sileo, Data Science Leader at Global Engineering, Essilor.

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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 ed
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The GE team at Essilor was able to use Dataiku for a predictive maintenance use case. The goal was to be able to indicate to operators the right time to change the consumable components so as to optimize their lifespan, while also guaranteeing the production quality standards.

In addition to using Dataiku to predict the optimal conditions under which they will use the consumables completely, the GE team also leverages Dataiku’s web application feature to provide a visual decision tool to help operators make a consistent choice when they have to change the consumables.

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[Efficiency Improvement - OEE]

The solution indicates the right time to change the consumable components so as to optimize their lifespan.

[Efficiency Improvement - Compliance]

The solution guarantees the production quality standards by monitoring the quality of the consumable components.

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