Nexen Tire has announced the development and implementation of an AI-based automated tire inspection system.
Nexen‘s system, which it states is an industry first, has been developed in a platform format, enabling easy application to new factories or equipment. The tire maker has been applying AI across the tire development process and now, with this AI implementation, has extended the scope of AI use to manufacturing processes.
Nexen’s AI-based automated product inspection system is applied to non-destructive inspection equipment using machine vision technology. This includes ‘x-ray inspection equipment’ for detecting structural defects, and ‘laser interferometry inspection equipment (shearography)’ for detecting air bubbles. The AI can interpret inspection images, a process which previously relied on a human.
Nexen says that the system has achieved a defect detection reproducibility rate of up to 99.96%. It can also detect minute defects that human inspectors might overlook, thereby improving the quality of tires.
Nexen has also enhanced the system’s practicality by automating the entire process of AI training and application. The company collaborated with Neurocle Inc, which is renowned for its AutoML (machine learning automation) solutions, and PDS Solution Inc, a specialist in tire design, analysis and data processing, from the design stage onward.
Beyond simple machine-learning automation, Nexen Tire applied machine-learning operations (MLOps) technology, including selective data collection for AI training, AI model training, model validation, actual application and post-deployment monitoring, marking the first such application in the tire industry.
This approach reduced the time it took to create a deep-learning model from six to 12 months to as little as two days. The system also enabled immediate application to new factories or equipment.
