大象视频

The Yokohama Rubber Co., Ltd., announces that it developed a proprietary tire mold design support system using simulations (FEM: finite element method) and the Company鈥檚 AI technology in April 2026. The new system supplements the knowledge and experience of the Company鈥檚 development staff and makes it easier even for less-experienced staff to design new molds by providing information (such as changes in tire characteristics due to different mold design factors) obtained by conducting a large number of virtual experiments. This system increases mold development speed, while reducing costs and the reworking often required to realize a new mold design. In addition, by facilitating greater understanding of the relationship between mold design factors and tire characteristics from multiple perspectives, this system will provide the Company鈥檚 development staff with new insights and inspirations that will contribute to the development of tires capable of higher-performance levels.

This new system was developed under Yokohama Rubber鈥檚 proprietary HAICoLab* AI utilization concept, which was launched in October 2020 with the aim of creating a more innovative development process. Mold design greatly affects the key characteristics of tires and obtaining a thorough understanding of the relationship between mold design factors and tire characteristics has required a costly and time-consuming trial-and-error process including trial production and follow-up evaluations. In addition, much of this process relied heavily on the know-how of highly experienced staff, which resulted in the mold design鈥檚 accuracy and development time differing based on the individual鈥檚 experience and knowledge. * An acronym for 鈥淗umans and AI Collaborate鈥� for digital innovation. It also refers to a laboratory for joint research by humans and AI.

This tire mold design support system uses automated simulations and AI-based prediction and visualization to resolve those issues. The system initially automatically generates a large number of tire FEM models with different mold shapes and then calculates tire characteristics in a virtual space. Next, the calculation results are used as training data to construct an AI model (surrogate model) that instantly predicts the relationship between mold design factors and tire characteristics. By applying XAI (eXplainable AI) technologies such as SHAP (SHapley Additive exPlanations) and PDP (Partial Dependence Plots) to this newly developed AI model, Yokohama Rubber development staff can quantitatively visualize the impact of mold design factors on tire characteristics, enabling them to easily determine how much they need to alter each mold design factor to achieve the targeted tire characteristics.

Yokohama Rubber previously used its proprietary HAICoLab AI utilization concept to develop a system that predicts the values of key tire characteristics (2021) and a tire design support system (2024), thus realizing an environment where its development staff can easily obtain the most optimal design guidelines. This new tire mold design support system is the latest achievement based on the Company鈥檚 proprietary HAICoLab AI utilization concept. Yokohama Rubber will continue its efforts to enhance its tire development environment and accelerate its development of innovative tires.

Source: