Sumitomo Rubber AI Breakthrough
[Sumitomo Rubber Achieves Breakthrough in Rubber Compound Formulation AI Prediction!]
On December 10th, it was announced that Sumitomo Rubber Industries and NEC Corporation are actively advancing their collaboration to "build a globally competitive R&D platform." Both companies have publicly stated their intention to integrate NEC's AI technology advantages with Sumitomo Rubber's own R&D strengths to tackle several key R&D challenges that need to be addressed before 2030, thereby driving technological innovation in the tire R&D field.
According to a joint announcement released by both parties on November 26th, Sumitomo Rubber and NEC have already established a long-term and stable "co-creation cooperation" partnership. In particular, since 2022, they have jointly built an AI platform for tire development, providing strong technical support for the company's tire design work.
Based on the new strategic agreement, the two parties will further expand the boundaries of their collaboration, focusing on developing an "advanced AI agent system" that integrates the expertise of Sumitomo Rubber's R&D personnel and engineers, laying a solid technological foundation for subsequent R&D work.
According to the Carbon Black Industry Network, in the early stages of their cooperation, the two parties conducted pilot tests on predicting tire material compound formulations using "pseudo-quantum annealing technology." Sumitomo Rubber explained that this phase of work first involved systematically analyzing and precisely extracting a large amount of material performance data accumulated from past experiments.
Then, based on the patterns summarized from the data analysis, and relying on NEC pseudo-quantum annealing technology—which can quickly screen for optimal solutions from massive and complex combinations—the system searches for candidate material types and specific formulations that match the target performance.
During the testing process, the rubber compound formulation generated by the system was compared with a high-end tire formulation previously developed by Sumitomo Rubber. The results showed that the system could "generate rubber compound formulation proposals that meet more than 90% of the target performance."
Furthermore, compared to the time required for non-professionals to complete the same formulation proposal, this technology can shorten the overall R&D cycle by 95%. Sumitomo Rubber stated that the application of this technology is expected to overcome the limitations of R&D personnel's professional level, efficiently developing rubber compounds suitable for all types of tires, from ordinary to high-end tires.
Besides rubber compound formulation prediction technology, another core R&D project for both parties is to discover new materials using artificial intelligence agent systems and materials exploration solutions, and significant results have already been achieved in this field. Sumitomo Rubber points out that the development of high-end new materials requires "searching massive amounts of literature across multiple fields," and it is extremely difficult to discover materials and combinations with application value from different fields.
During the technology verification phase, NEC's artificial intelligence experts and Sumitomo Rubber's materials R&D personnel collaborated to advance the exploration of new materials for high-end tires with stringent performance requirements. They first extracted the thought logic and tacit knowledge in the materials R&D process, and trained a dedicated artificial intelligence agent system based on this knowledge. Subsequently, this intelligent agent system used a materials exploration solution that integrates generative artificial intelligence and graph neural networks to accurately screen candidate materials.
The specific verification work was carried out using a high-end tire material with a "soft surface upon contact with water" as a model. It is difficult to achieve a breakthrough in the development of such materials using only traditional technologies.
The verification results show that the artificial intelligence agent system can integrate and analyze materials R&D knowledge from multilingual open literature, and can also autonomously collect deeper relevant information, thereby broadening the search range of candidate materials.
Sumitomo Rubber stated that compared to manual searches—which often require rework due to failing to cover key needs or having a limited search scope—this system can reduce search time by 60%-70%. This result confirms that the system can improve the accuracy and comprehensiveness of R&D, efficiently uncovering novel material candidates that are difficult to identify using traditional methods.
As an important part of their strategic partnership, Sumitomo Rubber and NEC will further expand their cooperation based on the aforementioned two pilot projects and other related technologies. Their core objective is to build an advanced AI-driven R&D platform by 2030, bringing about a revolutionary change in tire R&D.
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