Yansong Chen, senior vice president of strategy and technology at Ricardo, an environmental, engineering and strategic consulting firm, said advanced technologies are fundamentally changing the way the industry views value. “They are changing the way the industry perceives its role in communicating with the customer.”
Beyond Net Zero: Data, Design and Digital Communications
The rise of electric vehicles clearly shows how the auto industry has changed over the past decade. In the year By 2022, global sales of passenger EVs will exceed 10 million for the first time. In the year EVs were one in seven passenger cars sold globally in 2022, compared to just one in 70 cars sold in 2017.
As EV adoption continues to grow, technology and software advances are becoming increasingly critical to digitally connecting customers and improving their experience. “Our ability to access data and apply it to design processes in real-time is how we can transform the industry, reduce costs and carbon emissions, personalize the driving experience and create new value for customers,” says Chen.
However, continued advancements in software require a deeper understanding of how technology applies to the auto industry. Traditional producers especially have to balance heritage works with new tools and designs. “Advanced technology and AI are helping to make cars smarter, but they are also changing the basic behavior of the car, both inside and out,” said Luc Julia, chief science officer of the French automaker Renault.
It is therefore important to bridge the gap between the auto industry and technology providers. For example, Ricardo’s partnership with the Digital Twin Consortium allows it to collaborate with technology firms such as Ansys, Dell, Lendlease and Microsoft. The Open Membership Consortium is a global ecosystem of industry, government and academic professionals shaping digital twin development.
The rise of the digital twin
In recent years, digital twin technology has become an essential tool in auto manufacturing, changing how vehicles are made. For example, Renault has mapped its physical assets into digital twins, and each factory has a copy in the virtual world. This automation is part of its efforts to digitize its production lines and accelerate supply chain information within the organization. “By optimizing data, we can use AI more effectively on the factory floor and increase the efficiency of our work,” says Julia.
Renault’s factories are powered by artificial intelligence (AI) and machine learning with supplier data, sales forecasts and quality data—allowing it to generate multiple predictive scenarios. For example, predictive maintenance for robots involves predicting and processing potential failures at each part of an assembly line.
In addition, Renault’s Refactory initiative, organized around four key activity centers—Re-trophy, Re-energy, Re-cycle and Re-start—uses digital twins to reduce its carbon footprint. “The question is not only electric cars, but also how the batteries are extracted and the recycling of cars and materials,” says Julia.