Optimizing Renault’s industrial performance
Antoine LEBLANC, IA Industry Expert, Renault Group
“In the same way that we qualify and monitor our critical industrial systems for their start-up and operation over time, a trustworthy
AI system is one that we can qualify and monitor for drift.
The Confiance.ai program has enabled manufacturers to define the technological building blocks essential to the robustness of global industrial data management solutions.
In addition, the phases of building up the state of the art and calling for expressions of interest from other partners also helped us to situate the players in the French AI ecosystem and forge new partnerships.”
Renault’s participation in the Confiance.ai program has led to major advances in the integration of AI into its industrial processes. The lessons learned from this program have helped to improve the performance and competitiveness of its operations.
AI adoption challenges specific to Renault
AI is a lever of the Full POWER 2027 plan to improve the performance and competitiveness of industry and quality.
Products and services affected by the Confiance.ai program
AI is a cross-functional tool used to enhance the operational performance of industry players. It impacts the productivity of production engineers, decision support for industrial site managers, and the operations of production line players.
Confiance.ai’s contribution to the Renault Group’s strategy and challenges
The corporate Industry team’s participation in the Confiance.ai program has helped define the technical expectations for large-scale global industrial data management solutions, with the aim of increasing technical expertise, particularly in the application of AI to critical industrial use cases.
Competitive advantages developed with Confiance.ai
This enabled Renault to gain time in considering and adopting Trustworthy AI issues, and to decide to develop AI solutions for the industry in-house.
Challenges and conditions for success for the next phase of the Confiance.ai program
Renault didn’t have time to delve into the application of the subjects linked to the SHS Call for Expressions of Interest, supported by the Confiance.ai program, nor to develop the requirements for guaranteeing the proper operation of LLMs on industry use cases.
Example of current or future implementation/deployment
In manufacturing :
- Renault has adopted models from the AIX360 explainability brick for missing part detection in a kitting cart.
- The MAIAT method was adopted to assess the risks of social acceptance of AI systems on production lines.
Accelerating AI Act compliance with the Confiance.ai program
The Confiance.ai program has enabled Renault to identify tools and methods that meet certain requirements of the AI Act. The integration of socio-technical criteria is an essential component of this compliance.
