News

Sumitomo Rubber Industries, Ltd. is pleased to announce that we have completed the development of a new AI-based technology that utilizes real-world data on tire raw materials, as well as advanced analytical data on the internal structures of rubber, to perform a wide range of tasks, including not only precisely estimating rubber properties, but also detecting structural changes that occur during use in order to predict the properties of rubber after use. We call this versatile new technology "Tyre Leap AI Analysis." Taking full advantage of this groundbreaking technology, the Sumitomo Rubber Group plans to accelerate the development of "Performance Sustaining Technology^*1," one of the key development trends of our "SMART TYRE CONCEPT," which aims to contribute to the realization of a sustainable Mobility Society for the future by developing high-performance tires that provide both safety and peace of mind.
*1. Technology that aims to suppress the degradation of tire performance that occurs due to wear and the passage of time, allowing tires to maintain like-new performance for longer.

The rubber used to make tires is actually a compound composed of many different materials, including polymers (such as natural and synthetic rubber), reinforcing agents (such as carbon black and silica), crosslinking agents and additives. Tire performance depends on many interlocking factors related to the proportions of these various materials, the structures that they form in combination and so forth. As the internal structures of rubber are exceedingly complex, there are limits to what human beings can accomplish when it comes to analyzing them, both in terms of the time required for analysis and the precision of analysis results.
Thus, our newly developed "Tyre Leap AI Analysis" utilizes advanced AI-based analysis technology^*2 to analyze (for example) electron microscope imagery of tire rubber compounds in order to achieve high-precision analysis that far exceeds human capabilities, thereby making it possible to derive accurate estimates of rubber properties from structural data found in this imagery. Meanwhile, combining data on the individual raw materials contained in a rubber compound with data on its internal structure allows for even more precise estimates of rubber properties. Further, "Tyre Leap AI Analysis" is also able to detect structural changes that occur during use by comparing used and unused rubber, meaning that this new technology has enormous potential for such future applications as predicting the properties of rubber after use.
*2. This AI-based imagery analysis technology is the result of joint research between Sumitomo Rubber Industries and Professor Miki Haseyama of Hokkaido University.
 

Acquiring New Structural Data Allows for Precise Estimates of Rubber Properties + Detection of Structural Changes in Rubber