12 Sep 2017:
IBM (NYSE: IBM) today announced that Faurecia, one of the world’s leading automotive suppliers, has selected IBM Cloud as a support of a major business transformation designed to accelerate digital manufacturing.
Managing an ever-growing global enterprise of manufacturing and sales, Faurecia’s digital transformation is centered on seamlessly generating and communicating data, including data on production quality and manufacturing processes, to drive efficiency and productivity, while making production processes more visible and controllable. Faurecia selected IBM to build a global cloud solution to collect, manage and analyze data from every production machine across the company. By using the capabilities of cloud and analytics, non-quality can be drastically reduced allowing for better efficiency.
At the core of the solution is a data lake in the IBM Cloud, a massive repository that stores data in its native form until needed and accessed. The data lake stores quality data from every product at different stages of the manufacturing cycle, in order to track product and process quality. The data lake is built with IBM’s Cloud platform and enables Faurecia to capture and store data from its 24×7 worldwide manufacturing environment, which operates in 300 plants across 34 countries. Using IBM Predictive Maintenance and Quality (PMQ), new insights about virtually every aspect of the operation can be accessed on-demand to improve everything from machine productivity to scrap management.
For example, by gathering quality data from every product at different stages of the manufacturing process, together with process data from production sensors and machinery and product traceability data, Faurecia can immediately analyze the data to determine factors that influence product and process quality. Using this analysis, Faurecia can develop strategies to address quality issues, including machine configuration, production modification or tool replacement.
Collecting and analyzing more diverse operational data from connected plants will allow Faurecia data scientists to build better predictive maintenance models. Using IBM PMQ connected to the data lake, the company plans to improve machine productivity and reduce the scrap rate of its products by anticipating potential production issues.
“At the helm of our digital transformation is technology that can capture and analyze data to predict and prevent equipment failures, correct inefficiencies and increase productivity,” said Grégoire Ferré, Digital Transformation Project Director at Faurecia. “The selection of IBM Cloud is contributing to support Faurecia’s industry 4.0 strategy at the forefront of modern-day manufacturing.”
With IBM Cloud, Faurecia has easy access to flexible, security-rich worldwide cloud infrastructure spanning 19 countries. This scalable infrastructure will support future use cases and the company’s strategic ambitions.
“Agile manufacturing systems have become a key component in remaining competitive in the automotive sector,” said Béatrice Kosowski, General Manager, IBM Global Technology Services in IBM France. “With the IBM cloud-based platform and analytics capabilities, Faurecia can leverage structured and unstructured data to quickly address ever-changing customer needs with intelligent solutions.”
Founded in 1997, Faurecia has grown to become a major player in the global automotive industry. With 330 sites including 30 R&D centers, 100 000 employees in 34 countries, Faurecia is now a global leader in its three areas of business: automotive seating, interior systems and clean mobility. Faurecia has focused its technology strategy on providing solutions for smart life on board and sustainable mobility. In 2016, the Group posted total sales of €18.7 billion. Faurecia is listed on the NYSE Euronext Paris stock exchange and trades in the U.S. over-the-counter (OTC) market. For more information, visit www.faurecia.com.
For more information on IBM Cloud, visit www.ibm.com/cloud-computing.
For more information about IBM analytics, visit https://www.ibm.com/analytics/us/en/