Nissan has extended its strategic partnership with Monolith through 2027 to harness the power of artificial intelligence (AI) in reducing physical vehicle testing and speeding up product development.
The collaboration combines Nissan’s 90 years of R&D expertise with Monolith’s advanced AI technology to predict performance outcomes earlier in the design process. By cutting the need for multiple physical prototypes, Nissan can bring vehicles to market faster while improving quality and sustainability.
This initiative forms a key part of the company’s RE:Nissan global recovery plan, aimed at reducing vehicle development time, driving operational efficiency, and accelerating innovation across its product lineup.
First used to validate testing on the new, Sunderland-built Nissan LEAF electric vehicle, Monolith’s AI technology will be applied to more tests for Nissan’s future range of models in Europe.
Using more than 90 years of vehicle testing data, engineers at Nissan Technical Centre Europe (Cranfield, United Kingdom) will use Monolith’s AI technology to accurately predict the results of physical tests. This reduces the reliance on physical prototypes, streamlines the development process and allows engineers to focus on hands-on problem solving and decision making.
The decision to extend the partnership follows the successful collaboration between Nissan and Monolith using AI to test the performance of bolt joints in vehicle chassis. The AI technology recommended the optimal torque range for bolts to be tightened and reliably prioritised additional tests for engineers to carry out.
This resulted in an overall 17% reduction in physical testing compared to the non-AI process. Applying the same approach across the development of all Nissan’s European vehicle range could cut testing time by half.
Commenting on the partnership, Emma Deutsch, Director of Customer Orientated Engineering and Test Operations, Nissan Technical Centre Europe, said: “By integrating Monolith’s advanced AI-driven engineering software and decades of testing data, we’re able to simulate and validate vehicle performance with remarkable precision.
“Their machine learning models, trained on a combination of historical test data and digital simulations, allow us to reduce reliance on physical prototypes – cutting development time and resource use significantly. This approach not only accelerates our time to market but also supports our commitment to innovation and sustainability. As we look to the future, AI will play an increasingly central role in how we design, test, and deliver the next generation of vehicles to our customers sooner.”
Monolith’s platform enables engineers to harness historical test data and simulations to predict outcomes, reduce reliance on physical prototypes, and improve product quality. Tools like the Next Test Recommender and Anomaly Detector illustrate how Monolith’s commitment to cutting development cycles in half, all while maintaining quality and performance of its vehicles and technologies.
Dr. Richard Ahlfeld, CEO and Founder of Monolith, added: “Our mission is to empower engineers with AI tools that unlock smarter, faster product development. The results of our work with Nissan demonstrate how machine learning can drive efficiency and innovation in automotive engineering. We’re thrilled to continue this journey together.”
First used to validate testing on the new Nissan LEAF, Monolith’s AI integrated testing will be applied to more tests for future models due to hit the market in the years ahead.