Renault gana velocidad gracias a la IA

Renault has accelerated its vehicle development times through an aggressive strategy that utilizes artificial intelligence (AI). The automaker aims to cut development time for new models by half, from what was previously required. This strategy aligns with the approach used by Chinese brands, which launch models quickly, reducing costs and keeping the latest technology in the market.

AI plays a crucial role in Renault's development process, applied across the design of vehicles from brands Renault, Alpine, and Dacia. The digitalization of the design process enables designers to run thousands of simulations and tests digitally, eliminating the need for time-consuming physical prototypes. Renault's plants in Palencia and Valladolid integrate AI into vehicle development and industrial processes.

The company highlights that AI tools enhance designers' creative capabilities, enabling the generation of thousands of designs, forms, and structures from a simple proposal. AI also aids in early identification of technical limitations and streamlines communication between design and engineering departments. The Technocentre in France employs over 70 simulation engineers to conduct immersive digital simulations for new models, providing detailed insights into vehicle characteristics virtually, without the need for physical prototypes.

Additionally, AI is used to manage the supply chain, monitoring risks in logistics through a "Control Tower" that detects disruptions like industrial accidents, strikes, or natural disasters, enabling timely decisions to mitigate these risks and ensure smooth production. Renault also created Askrnlt, an AI platform for customers to ask questions about different models, providing personalized recommendations.

Renault's "Plant Connect" program uses real-time data from its plants in Valladolid and Palencia, processed through AI, to provide a comprehensive view of production indicators, including logistics, manufacturing, quality, and delivery. By analyzing over 3 million data points per minute, the system enables end-to-end control of industrial processes, reducing production failures and improving overall efficiency.