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Artificial intelligence gets to grip with tyres

Electron micrograph of rubber that is used to put into a machine-learning model to detect regions of deterioration in tyres.Reproduced from Togo, R. et al. IEEE Access 7, 162395 (2019) and licensed under CC BY 4.0 © 2021 R. Togo et al.

Tyre manufactures will be able to create products that have more consistent performance and extended usable life thanks to a ground-breaking technology that leverages the power of artificial intelligence (AI) to detect structural changes that occur during a tyre’s use.

Named for its ability to ‘leap’ forward in time by predicting tyre conditions based on past trends, Tyre Leap AI Analysis technology was jointly developed by engineers at the Japanese tyre-manufacturer Sumitomo Rubber Industries in Kobe and researchers in the Haseyama Laboratory of Hokkaido University in Sapporo. It uses advanced AI-based technology to predict the properties of the rubber compounds used in tyres and detects how structural changes in the tyre affect performance throughout its lifespan.

“These structural changes arise from tyre deterioration caused by factors such as heat and stress during driving,” explains Miki Haseyama, vice-president and dean of the Faculty of Information Science and Technology at Hokkaido University, who led the university’s contribution to the project. “The types and degree of deterioration vary widely. Previously, it wasn’t clear to what extent a used tyre’s structure differed from that of a new one.”

To develop tyres with improved durability over a longer operating life, it is vital to clarify the cause of degradation in the tyre and then provide feedback on the choice and composition of the materials used in its manufacture, Haseyama says.

Using AI to unravel the complexity of tyres

Rubber tyres are made from various materials, including natural and synthetic rubber polymers, carbon black and/or silica-based reinforcing agents, cross-linking agents and additives. The proportions of these materials, the structures they form, and the complex interactions between them are among the many factors that determine a tyre’s properties.

Miki Haseyama is excited about the ability of artificial intelligence to predict the effects of wear and tear on tyres and to use that knowledge to optimize the materials used for tyres.© Hokkaido University

By combining structural data with information on these raw materials, the physical properties of the tyre, such as fuel efficiency, grip and wear resistance, can be determined with a high degree of precision. “The properties determine the performance of a tyre and change due to mechanical loading and wear during use,” says Kiyoshige Muraoka, a senior executive officer and general manager of Research and Development (Material Research and Development) at Sumitomo Rubber Industries, who was involved in the development of Tyre Leap AI Analysis. “Understanding the interaction between the rubber compounds and how the tyre’s properties evolve during use is critical to developing tyres that perform better.”

Analysing the complex interactions between the compounds and how they are affected by wear has, until now, proved to be extremely challenging, he says. Using an AI-based image-processing system, Tyre Leap AI Analysis analyses the internal structures of the rubber compounds from electron microscopy images. From the patterns of ageing and wear found in the electron micrographs of used tyres, it can then accurately estimate the tyre’s properties after use.

“The technology can ‘learn’ the properties of the tyre,” says Haseyama. “By comparing the properties of an old tyre with those of a new one, it can determine where structural changes have occurred and estimate the physical properties of the rubber in the areas that have undergone these changes.”

Kiyoshige Muraoka believes that understanding the connection between rubber compounds and how a tyre’s properties evolve during use is the key to developing better tyres.© Sumitomo Rubber Industries, Ltd.

Tyre Leap AI Analysis can precisely detect the various changes in the rubber properties, such as how much the rubber has deformed due to external forces during use. It can then predict how the tyre’s internal structure will change over time.

Feeding more data to the AI-based technology, will allow it to continue to learn and develop, increasing the number of properties it can estimate and allowing it to predict the characteristics of the rubber compounds with even greater accuracy, Haseyama says.

The technology could lead to the design of new rubber compounds that are less prone to performance degradation due to wear and provide more consistent performance over an extended period, leading to improved wear rates and increased safety over the tyre’s lifespan.

Producing smart tyres

It has already been used to develop Sumitomo Rubber Industries’ Enasave Next III tyre, which is more fuel efficient, more wear resistant and provides more consistent tracking during its life than other tyres on the market. “Not only did the tyre achieve the highest possible rating (AAA-a) under Japan’s tyre labelling system for fuel efficiency and wet grip performance, but it also reduced by half the deteriorations in tyre performance that occur over time,” says Muraoka.

The technology has allowed the company to accelerate research and development as part of its Performance Sustaining Technology programme, which aims to minimize the deterioration in tyre performance due to wear and time, enabling tyres to maintain a ‘like-new’ performance for longer.

“The initiative is a critical component of our Smart Tyre Concept, which seeks to contribute to a sustainable mobile society,” says Muraoka.

Sumitomo Rubber Industries' Tyre Technical Center in the port city of Kobe.© Sumitomo Rubber Industries, Ltd.

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