Renault Group and Atos launch unique data collection service

Renault Group and Atos have launched ID@scale (Industrial Data @ Scale), a new service for industrial data collection to support manufacturing companies in their digital journey towards Industry 4.0. “ID@S” will allow manufacturers to collect and structure data from industrial equipment at scale to improve operational excellence and product quality. Developed by the car manufacturer and already in operation within its factories, ID@scale is now industrialised, modularised and commercialised by Atos.

Throughout the production process, manufacturers generate a phenomenal amount of data. In more cases than not, data is underutilised, owing to its diversity and lack of standardisation as well as operator time shortages. By deploying ID@S, manufacturers will now be able to collect data from a wide range of manufacturing facilities (diverse suppliers, generations, global location, firmware updates, etc.) in a standardised and effective way, then contextualised and made available in the cloud.

As a result, the data corrects and scales up production processes and product quality with immediate effect. Easy access to standardised data via simple to use analytical tools and dashboards facilitates and accelerates the deployment of many kinds of use cases (production, maintenance, quality and energies, etc.), including net zero benefits. Additionally, with ID@scale, manufacturers can target significant energy consumption benefits by monitoring and optimising energy consumed on production lines.

As part of the company’s digital transformation strategy, Renault Group’s IT, digital and engineering teams have developed this solution to capture data from its manufacturing facilities. For each type of manufacturing process, data is collected and structured in a standardised way, enabling a variety of use cases across manufacturing, engineering, quality, CSR and logistics to be addressed. Today, this solution is deployed on a large scale across 22 plants within Renault Group.

More than 7,500 pieces of equipment are connected, with standardised data models representing over 50 different manufacturing processes from screwdriving to aluminium injection, including car frame welding, machining, painting, stamping, in addition to new manufacturing processes for electric motors and batteries. Renault Group is already saving €80 million per year and aims to deploy this solution across the remainder of its 35 plants, connecting over 22,000 pieces of equipment by 2023 to generate savings of €200 million per year.

Atos is strengthening and industrialising Renault’s solution through its combined technology portfolio, services and consulting expertise. The ID@scale service benefits from Atos’ Edge to Cloud offering, enabling real-time analysis of large volumes of complex industrial data while securing it from the Edge to Cloud platforms, as well as optimising the inference of the most complex artificial intelligence models thanks to its Bull Sequana Edge server range.

Jose-Vicente de los Mozos, EVP Group Industry, Renault Group said: “Renault Group has developed a unique technology solution to collect large-scale manufacturing data to improved performance of our production tools and therefore the quality of our vehicles.

“Today, we are pleased to announce a new milestone. Through our collaboration with Atos, we will go one step further in commercialising our expertise as we support manufacturing sector organisations in the scale-up of their digital transformation. This marks a new step in Renault Group’s digital transformation and innovation capacity,” he added.

Rakesh Khanna, Head of Digital, Atos said: “In a market with no equivalent solution, Atos modularises and enhances Renault Group’s initial solution for all manufacturing sectors, on a worldwide basis. By joining forces, Atos and Renault Group are enabling organisations to effectively collect data from their plants to leverage information on a large-scale basis and successfully scale-up and accelerate their digital manufacturing transformation.”