Dataiku Case Studies Harnessing Large, Heterogenous Datasets to Improve Manufacturing Process

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	Harnessing Large, Heterogenous Datasets to Improve Manufacturing Process Dataiku

Harnessing Large, Heterogenous Datasets to Improve Manufacturing Process

Dataiku

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Functions	Discrete Manufacturing Maintenance
Use Cases	Machine Condition Monitoring Predictive Maintenance
Services	Data Science Services
Challenge	Essilor International, a leading ophthalmic optics company, was facing the challenge of improving the processes and performance of their surfacing machines to significantly enhance their production. The surfacing step in lens creation is complex and delicate, as it gives the lens its optical function. The company aimed to optimize this step to correspond to each person’s individual prescription and personal parameters. However, they were dealing with large, heterogeneous datasets from the surfacing machines and needed a scalable way to work with this data. The company was already using continuous monitoring technologies like IoT connected devices, but they wanted to take a step further by employing advanced algorithms and machine learning to take action from real-time insights. Read More
About Customer	Essilor International is the world’s leading ophthalmic optics company. The company designs, manufactures, and markets a wide range of lenses to improve and protect eyesight. Essilor employs 67,000 people worldwide and has 34 plants, 481 prescription laboratories and edging facilities, as well as four research and development centers around the world. The company's core business is the production of ophthalmic lenses. In their dedication to ensure factories are efficient, innovative, and respect high-quality standards, Essilor has a Global Engineering (GE) service that is responsible for the implementation and standardization of production processes. Read More
Solution	Essilor chose Dataiku Data Science Studio (DSS) to help them effectively work with the extensive amount of data from the surfacing machines. The setup and implementation of Dataiku were easy and allowed them to get started quickly. The tool allowed them to explore, analyze, and create predictive models that could be used by everyone, from professional experts to machine operators, data scientists, and IT. Dataiku also allowed them to manage the variations in the data from the surfacing machines efficiently and effectively. The team was able to quickly test and iterate on use cases to arrive at a solution faster. They also appreciated the flexibility to work using code or using the point-and-click visual interface, whichever allowed them to work more quickly. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Functions

Discrete Manufacturing

Maintenance

Use Cases

Machine Condition Monitoring

Predictive Maintenance

Services

Data Science Services

Challenge

Essilor International, a leading ophthalmic optics company, was facing the challenge of improving the processes and performance of their surfacing machines to significantly enhance their production. The surfacing step in lens creation is complex and delicate, as it gives the lens its optical function. The company aimed to optimize this step to correspond to each person’s individual prescription and personal parameters. However, they were dealing with large, heterogeneous datasets from the surfacing machines and needed a scalable way to work with this data. The company was already using continuous monitoring technologies like IoT connected devices, but they wanted to take a step further by employing advanced algorithms and machine learning to take action from real-time insights.

About Customer

Essilor International is the world’s leading ophthalmic optics company. The company designs, manufactures, and markets a wide range of lenses to improve and protect eyesight. Essilor employs 67,000 people worldwide and has 34 plants, 481 prescription laboratories and edging facilities, as well as four research and development centers around the world. The company's core business is the production of ophthalmic lenses. In their dedication to ensure factories are efficient, innovative, and respect high-quality standards, Essilor has a Global Engineering (GE) service that is responsible for the implementation and standardization of production processes.

Solution

Essilor chose Dataiku Data Science Studio (DSS) to help them effectively work with the extensive amount of data from the surfacing machines. The setup and implementation of Dataiku were easy and allowed them to get started quickly. The tool allowed them to explore, analyze, and create predictive models that could be used by everyone, from professional experts to machine operators, data scientists, and IT. Dataiku also allowed them to manage the variations in the data from the surfacing machines efficiently and effectively. The team was able to quickly test and iterate on use cases to arrive at a solution faster. They also appreciated the flexibility to work using code or using the point-and-click visual interface, whichever allowed them to work more quickly.

Impact #1	The GE team at Essilor was able to use Dataiku to execute on a predictive maintenance use case that indicates to operators the right time to change the consumable components so as to optimize their lifespan while also guaranteeing the production quality standards.
Impact #2	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.
Impact #3	The GE team provides value to Essilor as a whole by promoting the use of data to provide insight throughout the rest of the organization - Dataiku is now being used internationally by additional teams.

Impact #1

The GE team at Essilor was able to use Dataiku to execute on a predictive maintenance use case that indicates to operators the right time to change the consumable components so as to optimize their lifespan while also guaranteeing the production quality standards.

Impact #2

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.

Impact #3

The GE team provides value to Essilor as a whole by promoting the use of data to provide insight throughout the rest of the organization - Dataiku is now being used internationally by additional teams.

Benefit #1	Optimized lifespan of consumable components, ensuring production quality standards.
Benefit #2	Promotion of data usage for insights throughout the organization, leading to international use of Dataiku by additional teams.
Benefit #3	Enhanced cross-team collaboration between the GE department, factories, and IT teams.

Benefit #1

Optimized lifespan of consumable components, ensuring production quality standards.

Benefit #2

Promotion of data usage for insights throughout the organization, leading to international use of Dataiku by additional teams.

Benefit #3

Enhanced cross-team collaboration between the GE department, factories, and IT teams.

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Overview

Harnessing Large, Heterogenous Datasets to Improve Manufacturing Process

Operational Impact

Quantitative Benefit