Nexen Tire, a leading global tyre manufacturer, has announced the development and implementation of its AI-based automated tyre product inspection system. As the first instance in the tyre industry, the system has been developed in a platform format, allowing easy application to new factories or equipment. With the introduction of this automated product inspection system, Nexen Tire, which has been expanding AI applications in the tyre development process, has now extended the scope of AI utilisation to manufacturing processes.
Due to the nature of tyres, which must ensure rider safety even in extreme driving conditions, only products that pass hundreds of tests during the post-production inspection process are sold. Therefore, manufacturers devote utmost efforts to inspection processes in order to detect even minor defects that could prevent defective products from reaching the market.
Nexen Tire’s AI-based automated product inspection system is applied to non-destructive inspection equipment using machine vision technology (Machine Vision, a technology that recognises and analyses visual information through cameras). This includes ‘X-ray inspection equipment’ for detecting structural defects and ‘laser interferometry inspection equipment (Shearography)’ for detecting air bubbles. The AI assists in interpreting inspection images, which previously relied on human visual assessment.
In particular, the system has achieved a defect detection reproducibility rate of up to 99.96%. It detects minute defects that human inspectors might overlook, thereby contributing to enhancing the quality of finished products.
Furthermore, Nexen Tire has enhanced the system’s practicality by automating the entire process of AI training and application. To ensure the system’s practicality, Nexen Tire collaborated with Neurocell Inc., renowned for its AutoML (machine learning automation) solutions, and PDS Solution Inc., specialised in tyre design, analysis, and data processing, from the design phase onward. Beyond simple machine learning automation, Nexen Tire applied Machine Learning Operations (MLOps) technology, which optimises and automates the entire lifecycle of AI models—including selective data collection for AI training, AI model training, model validation, actual application, and post-deployment monitoring—and successfully implemented a platform-based system, marking the first such application in the tyre industry.
This approach reduced the time it took to create a deep learning model creation from 6 to 12 months to as few as two days. The platform-based system also enabled immediate application to new factories or equipment. In fact, the AI trained with data from the factory where the automated inspection system was implemented aided in the the early stabilisation of systems introduced in other factories.
“By introducing AI technology, we have significantly improved the precision and efficiency of our tyre inspection process ,” said Travis Kang, Global CEO of NEXEN TIRE. “We will continue to expand the application of AI technology to the entire development and manufacturing processes, beyond non-destructive testing.”
Source: Tyretradenews
