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AI Software Accelerates Vehicle Development With Data-Driven Modelling

Monolith, artificial intelligence (AI) software provider, is looking to accelerate growth opportunities in the automotive industry with a new addition to its senior management team. The UK based company has appointed Oliver J Walter to head up its automotive division and meet the increasing demand for AI software in automotive R&D. He will lead global sales and account operations with key automotive clients.

Following the successful adoption of AI and machine learning by engineering teams at Honda, Mercedes-Benz, BMW Group, Kautex-Textron and Honeywell, Monolith is now looking to expand its software application across the automotive industry.

Dr Richard Ahlfeld, CEO and Founder of Monolith, said: “Monolith is AI software developed for engineers so they can do less expensive, repetitive testing and more learning from their data to create better quality products. With his extensive experience in the automotive industry and first-hand knowledge of engineering workflows, Oliver will help us gain a wider foothold with OEMs as they increasingly look to use AI to speed up product development.”

On his appointment as General Manager of Automotive, Oliver commented: “It’s a great time to be working in AI. My job is reinforcing Monolith’s continued growth and building on the success stories so far. Our team of machine-learning experts has developed software that can enhance engineering productivity, predict results ahead of time, reduce hardware testing and ultimately accelerate product development.”

His appointment at Monolith comes at a time when corporate and public interest in AI is at an all-time high. The power of AI in automotive engineering lies in its ability to reduce the amount of physical testing time and simulations required to successfully develop products with highly complex physics throughout the design cycle. Using valuable and sometimes limited engineering test data, Monolith makes instant predictions and enables engineers to identify areas where optimisation and development are required without the extensive need for repetitive, time-consuming physical tests.

In June 2022, Monolith announced that BMW Group were using its software to accelerate the development of their vehicles. By training Monolith self-learning models with the company’s valuable engineering test data, engineers can now use AI to solve previously impossible physics challenges and instantly predict the performance of highly complex systems like crash and aerodynamics tests.

Using Monolith, BMW Group engineers built self-learning models using the wealth of their existing crash data and were able to accurately predict the force on the tibia for a range of different crash types without doing physical crashes. Moreover, the accuracy of the self-learning models will continue to improve as more data becomes available and the platform is further embedded into the engineering workflow. This game-changing approach now means engineers can optimise crash performance earlier in the design process and reduce dependence on time-intensive, costly testing, making historical data infinitely more valuable.

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