The automotive industry is increasingly leveraging artificial intelligence to enhance efficiency and improve customer experiences. Manufacturers are using AI for supply chain optimization, predictive analytics, and safety enhancements in advanced driver assistance systems (ADAS). AI is also transforming customer interactions through personalized services and intelligent virtual assistants, while predictive maintenance helps ensure timely vehicle servicing. As the industry faces challenges like regulatory compliance and cybersecurity, AI provides practical solutions for adapting to evolving market demands. This integration represents a strategic shift toward a more efficient automotive sector.
S&P Global Mobility’s Matthew Beecham spoke to chief technology officer of Yanfeng Technology, Patrick Nebout. Yanfeng is a global automotive supplier specializing in interior, exterior, seating, cockpit electronics and passive safety, while actively exploring new business opportunities.
The following is an edited transcript of the conversation.
S&P Global Mobility: How is Yanfeng integrating AI technologies into automotive solutions, and what specific areas are showing significant measurable improvements in efficiency, performance, and customer interactions?
Patrick Nebout: In an automotive industry that is becoming increasingly digital and data-driven, applying AI technologies is positioning Yanfeng at the forefront of the competition. AI has the potential to revolutionize our operations by optimizing manufacturing operations, improving product quality and enhancing supply chain management.
Yanfeng is integrating AI technologies across multiple domains from engineering to manufacturing and has been using computer vision systems for complex interior modules for years. This technology can detect incorrect assembly connections, avoiding non-quality costs far more quickly and efficiently than human eyes. This way, we protect our customers, the car manufacturer, from receiving faulty modules with weak electrical connections.
Additionally, Yanfeng is exploring the design and simulation of new parts and systems using specific AI technology called “generative design.” These algorithms, combined with traditional CAD tools can explore a wide range of design alternatives based on predefined constraints (e.g., weight, material, cost), enabling us to quickly test innovative ideas and ensure cost-effective solutions.
What emerging AI technologies or trends do you foresee shaping the future of the automotive industry, and how is your company preparing to address these changes while enhancing user experience?
Artificial intelligence is not a new technology per se; AI has been around for more than 40 years. In recent years, the increased application of AI has stemmed from advancements in computer processing capacity, which allow for faster algorithms at a competitive cost on large databases. Some of the most popular AI technologies are the large language models (LLM), which essentially perform data mining on a vast array of text documents and other information, such as pictures.
Yanfeng is starting to apply these technologies to improve our knowledge-based activities, both internally and externally, particularly when addressing complex RFQ analysis.
In parallel, Yanfeng has established its “Advanced Engineering Group” around the Yanfeng Technology Smart Cabin. This group includes various functions, such as consumer research, user-experience, user interface and industrial design. The AI technologies mentioned are helping to analyze large databases that describe customer preferences and habits, as well as design and market trends across the three main automotive regions. This approach is very useful for creating bespoke products tailored to specific customer needs.
AI is rapidly transforming the user experience in the automotive industry, enhancing both the driving experience and life on board. AI technologies enable automotive interiors to become smarter, more personalized, and safer, ultimately providing drivers and passengers with an intuitive and highly connected experience.
What role does Yanfeng play in integrating AI for safety systems, particularly in ADAS and cybersecurity measures for connected vehicles, and how do these innovations contribute to regulatory compliance?
Yanfeng’s Safety activities are mainly focused on passive safety technologies and products, such as airbags, seat belts and systems, and steering wheels. For the past few years, Yanfeng has been developing XBU products, which combine safety products with other products like seats and interior components. One of the notable examples is the “Safe Unit,” which Yanfeng introduced to the public last summer. Yanfeng is developing the first market application for this unit for a Chinese customer.
Another application of XBU is the Hover Adaptive Seat, which was presented at CES 2024. For this innovation, we collect extensive data from the seat occupants using sensors and run our proprietary algorithm integrating AI technologies to detect occupant positions. These positions can address safety concerns, such as the “out of position” scenario, which is critical for the efficiency of the safety restraint system.
Focusing more on ADAS, Yanfeng has developed a comprehensive camera monitoring system combined with interior displays to replace the traditional mirrors. In these systems, AI technologies are applied to improve safety by enhancing the detection of blind spots and potential dangers in the car’s environment. Of course, all these innovations comply with the laws and regulations of our customer´s markets.
What primary challenges do you face in implementing AI solutions within the automotive sector, especially regarding data management and analysis, and how are you addressing these?
When applying AI technologies, all companies face several challenges, such as dealing with the collection of data from connected vehicles and onboard sensors. These activities generate massive amounts of data from a variety of sources, including sensors (cameras), onboard diagnostics and connected systems. Managing this high volume of data is necessary for training, validation and real-time operation. These databases often integrate personally identifiable information, making it essential to implement strict data privacy policies. Additionally, the data anonymization is mandatory to comply with privacy laws.
Data ownership is another complex issue. These questions must be addressed through data governance frameworks that clarify data ownership, access rights and usage policies. Technologies like blockchain will be used to create transparent and secure data-sharing between Yanfeng and OEM customers, tier 2 suppliers and tech companies.
