With around a dozen tire plants and 18,000 employees, Bridgestone’s EU arm has a strong emphasis on sustainability, quality, and advancing tire innovation. To improve Plant IT while benefiting from opportunities in digital manufacturing, Bridgestone EU was on a Smart Factory journey, looking to embrace the capabilities of Industry 4.0. To achieve that, it needed flexible, scalable, and cloud-native data and AI solutions. As with any large-scale manufacturing of data, the main challenge here was security. With numerous plants streaming data continuously, it needed a way to store data on-premise before sending it securely to the cloud.
We kicked off the project by rolling out our Azure Data Hub based on reference architecture from Microsoft and provided training and handover to accelerate the transformation. In order to meet the complex demands of the organization, the planned Data Hub needed to be scalable while including data warehousing and real-time data streaming capabilities.
We looked at every production chain step from raw materials to the finished product to see where data could bring the most value. Since tires go through several different machines that test for defects or irregularities, we set up several data pipelines at a Spanish plant to optimize this process by feeding information about the status and quality of the products in near real-time.
Bridgestone Corporation is a global leader in providing sustainable mobility and advanced solutions. It develops, manufactures, and markets a diverse portfolio of original equipment and replacement tires, tire-centric solutions, mobility solutions, and other rubber-associated and diversified products that deliver social and customer value. These best-in-class offerings are sold to consumers and fleet customers around the world under the trusted Bridgestone and Firestone brand names.
Within 2 months we had already delivered an Azure cloud-native, scalable Data Hub that had streaming and data warehousing capabilities. To facilitate innovation and tackle complexity, we set up the Data Hub with a ‘sandbox environment’ which allows different teams to automatically request and receive their own isolated and secure environment within the Data Hub where they can experiment, log data, and build use cases which can then be validated and streamlined across the whole organization faster and easier.
On top of that, using sensor data from the quality assurance machines, we developed and deployed a model that is able to predict and benchmark tire quality across plants. Tires were classified into ‘pass’ or ‘fail’ attending to a threshold of several quality measurements which included seasonal patterns. The solution was developed incrementally and deployed using MLflow within Databricks.
The Data Hub solution, which Eraneos specialists developed, helps Bridgestone EU accelerate their digital transformation and brings them one step closer to creating a Smart Factory. By enabling the use of their manufacturing data and adding advanced analytics and A.I. capabilities, we help them deliver not only operational excellence but also increase the scalability and speed of deployment in a connected and secure way.