HF Group’s upcoming range of digital solutions will monitor several parameters in the curing process, like cycle times, movements of the machines etc. One of the exhibitors at the Tire Technology Expo, 2022 that was held in Hannover, Germany was HF Group. Dr Bernd Pape, Digital Solutions, HF Group, threw light on the company’s plans to develop a new product line that will enable its customers to digitally monitor tyre curing machines more effectively, the significance of sharing data and having trusted partnerships.

The global tyre industry is steering more towards digitisation to ensure precision and save production time. And in this effort, HF Group seems to be the frontrunner, banking on data warehousing to produce effective monitoring solutions for tyre curing.

“HF is known as a company constantly extending traditional machine solutions. However, we are very well aware of digitisation, and the solutions will change our previous way of doing business at a global level,” said Dr Bernd Pape, Digital Solutions, HF Group, while we interacted with him at the latest edition of the Tire Technology Expo held this year in Hannover, Germany.

“I joined HF last year in June to build up a new product segment. However, due to the pandemic, I had limited chances to visit customers or talk to potential partners for development, and this conference has been an optimum opportunity to perceive an overview of our industry,” Dr Pape mentioned while he talked about the expo.

Digital solutions
HF’s upcoming range of digital solutions will monitor several parameters in the curing process, like cycle times, movements of machines etc. It will then churn out the alarm messages of the machines and correlate them to identify discrepancies. The new-age solutions will monitor machine data at different stages and have communication modules that will share the data from the machine control software to the internet using IoT gateways.

Extra sensors will be placed on the machines to measure certain component parameters like pressure, temperature, energy consumption etc. Leveraging the combination of cycle time monitoring, alarm messages and specific measurements of the sensor technology, the data will be analysed to bring out in-depth information about the machines’ performance.

Answering whether the sensors are capable of identifying the problems, Dr Pape informed, “In order for them to work efficiently to identify problems, we need quite some data. And when we have that data, we can do two things – analyse that data and see if insights can be derived automatically, or work with experts to derive insights and then transfer the knowledge into the digital solutions. He further added, “The entire research and development process demands a lot of communication and learning together with pilot customers, too.”

It’s important to share data
Initially, HF plans to implement the solution in their own curing press and further develop solutions for other machines. “We may need cooperation from customers to better understand other machines or even the OEM of that specific machine. If you look into digital transformation, it’s all about partnership. And if you don’t share data, you will not be able to flourish. And so far, my gut has been that our industry still has room to improve. We can still learn from each other by sharing data. With every new machine, we will have a growing database and knowledge on how to improve production,” Dr Pape asserted.

Digital benefit
HF strives to keep the cycle time of a machine at a constant low level. The curing process for one tyre may take 14 minutes. With the solutions, it can be reduced by 10 to 20 seconds. This would add up for the customer to produce roughly between 500 and 1,500 tyres per press per year, informed Dr Pape. Moreover, the solutions will enhance machine availability by detecting warnings for errors or repair time.

Trusted partnerships
The new solutions will require huge amounts of data to effectively do its task, but protection of proprietary data is a major concern. Speaking in this context, Dr Pape cited, “Digital transformation is about partnership, and you need to share data. So, partnership is all about trust. You need an initial amount of trust to provide data. There is no way around that.”

“On the other hand, once you give me the data, it is on me to keep it carefully and not to share it,” he further averred and went on, “Because if I do not comply, then the alliance will be harmed. So, there is a great opportunity because we are a long-standing partner for the whole industry. Therefore, we have trusted partnerships and projects with a lot of customers.”

Explaining the timeline from implementation to resumption of services, the executive said, “Once we are up and running with this solution, we just need a couple of days to implement it. But for new machine types that have not been analysed before, a couple of weeks are needed. Once knowledge of the specific machine type, how to adjust the software and how to analyse and interpret the data is known, we can configure same machine types within days.”

Current monitoring landscape
According to the executive, currently technicians might face severe problems while monitoring the machines as the industry has witnessed a generation shift. Experienced technicians retire and new ones have to learn the entire process. With the automation of unloading and loading systems, which are getting more and more automated, there might be no operators available who can point out if the machines have any problems.

“If we get the data from the machine and analyse it, we can redirect technicians to the area that causes the problem, so that they are faster in remedying it. The data will also help us to predict problems in the near future,” Dr Pape pointed out.

Stepping into the Indian market
HF has expanded its footprint across the globe and wants to market its products worldwide. The company’s pilot customers are in the Americas, followed by Europe. It also plans to tap into the Asian market.

Speaking on its plans to enter India, Dr Pape cited, “The country has great companies and some of them might be interested in the solutions. For building up a new product segment in India, we have to know what kind of customers are interested. We will then start operations on a remote basis and develop further.”

Collaborations for the long term
HF Group has also collaborated with Possehl Analytics as its solutions partner, which will also allow it to build a network for digital solutions in the industry. On the reference side, HF refers them as their solutions partner, while Possehl Analytics refers HF as a good operations partner.

Change is the only constant
While the tyre industry itself isn’t one that changes every day, we know that digitisation will have a pivotal role in its growth, including the tyre curing process, making sure the final product is of high quality. At the same time, sharing data and making long-lasting partnerships will only make the process and final outcome more competent.

Hankook Tire revealed the Design Innovation 2020 project, which defines a vision for the future driving and innovation in mobility.

Launched in 2012, the Design Innovation is Hankook’s R&D project held every two years, in collaboration with one of the world’s leading design universities.

Under the theme ‘Urban Reshaping’, professors and students from the Department of Industrial Design at the University of Cincinnati in the U.S. focused on the transformation of cities geared by reconfiguring mobility as part of living spaces rather than stand-alone purpose in the future with augmented automation infrastructure and cutting-edge technologies such as eco-friendly technology, autonomous driving and Artificial Intelligence (AI).

Throughout the project, modular platform of mobility concept named ‘Hankook Platform System (HPS)-Cell’ was proposed with tyre representing the root of mobility. It is applied with ‘Hankook Electric Mobility Technology (H.E.M.)’ which represents Hankook’s passion for future technological breakthroughs. Then a scenario was created which distinguishes mobility as a moving platform and its function as a pod (space), clearly elaborating that tire indeed sits at the center of the mobility.

The tyre of HPS-Cell embodied an airless tyres’ double-layered unit-cell structure to acquire complex rigidity. It is a concept tyre that uses sensor technology to not only identify tire treads and road conditions in real time, but also to respond to wear-out risks and change tread patterns according to the road condition utilizing variable wheels and optimized infrastructure.

The scenario was brought into reality in a concept film and a mock-up. The productions suggest that in 2040 urban population will be able to use this mobility platform combined with pods of various forms to each meet a specific purpose. The modular platform can also be combined with commercial pods such as urban farming to maximize the scalability and efficiency of movement within smart cities of future generation.

The unveiled productions will be exhibited at various global channels and will represent Hankook’s capabilities in design innovation globally.

Jimmy Kwon, Vice President of Hankook Tire Brand Lab said, “Hankook Tire is incorporating new ideas with our cutting-edge technology to explore design concepts for the next generation, as Hankook believes creativity is the first step towards bringing the imagination into the reality. We are more than excited to present this year’s works as they speak for the essence of the future mobility that Hankook envisions.”

TATNEFT has announced the development of a new line of ATV tyres called the KAMA Quadro ATM. The first model has been made in 25x8-12 standard size at its Nizhnekamskshina factory in Russia.

The ATV tyre, which is developed by Kama Scientific and Technical Center, has been specially designed for off-road driving, providing excellent cross-country ability in mud and snow. The tyre’s special rubber composition ensures high reliability and traction performance.

The first batch of tyres will go for pilot testing to TATNEFT subdivisions that operate off-road special vehicles.

The KAMA Quadro ATM range is currently being developed in nine tyre sizes covering 12 to 14 inches diameter, with nine more sizes coming up over the next year. The factory will begin production of 25x10 tyres for the rear axle in addition to the already manufactured  25x8 tyres intended for the front axle.

The KAMA Quadro ATM will meet the needs of the TATNEFT Group’s all-terrain vehicles used in oil fields and will also be used to equip Russian ATV manufacturers and the secondary market. (TT)

Kumho tyres have outperformed 52 rival manufacturers to ace the Auto Bild magazine’s summer tyre test with its ECSTA HS51 high-performance pattern tyre.

The annual test is among the most comprehensive of its type, the results of which are regarded as highly significant by both the European tyre trade and its consumers.

Conducted on both wet and dry surfaces, it left Kumho in a fighting third place overall. However, while the further qualifications caused the two leaders to slide down the order, 33 of the 53 entries were eliminated by the initial braking test. Kumho’s highly competitive and consistent scores in almost every discipline ultimately left it as the sole test winner.

 Awarding the ECSTA HS51 their coveted ‘Exemplary’ badge, the Auto Bild testers commended it for its precise steering response, secure wet grip, well-balanced handling, short braking distance, low wear rate and affordable price.

Unlike some tyre tests, where the products are supplied by the manufacturers, those for the Auto Bild ones are covertly purchased by the magazine from regular retail outlets. The chosen size was 205/55R16, the direct fitment for the bulk of Volkswagen Golfs and Audi A3s etc., and therefore arguably the one most common within the European car market.

UK purchasers currently have the choice of 35 sizes of ECSTA HS51 for wheels of 15 to 18 inches in diameter. The qualification round of the test was carried out at ATP (Automotive Testing Papenburg) in Germany and the other tests were performed at the IDIADA facility in Spain. 

Thus, our newly developed "Tire Leap AI Analysis" utilises advanced AI-based analysis technology to analyse (for example) electron microscope imagery of tyre 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.

Specifically, it is a technology that estimates rubber properties precise from combining data on the individual raw materials contained in a rubber compound with data on its internal structure. In the future, we will continue to develop this technology and develop technology to estimate the future rubber properties from electron microscope imagery of unused rubber.

■ Technology to Precisely Estimate Rubber Properties Based on Structures & Materials

Tire Leap AI Analysis utilises an AI-based image analysis system to analyse the internal structures of rubber in images captured by an electron microscope in order to infer information about the properties of the rubber based on its structural data (i.e. the results of image analysis). By combining this structural data with data about the materials that make up rubber compounds, this technology is then able to derive information about the physical properties of rubber with a high degree of precision.

■ Technology to Detect Changes in the Internal Structures of Rubber After Use & Estimate Resulting Changes in Rubber Properties

By comparing images of a tyre that has never been used (i.e. that is brand new) with images of a tyre that has been used (i.e. after wear over time), this AI-based image analysis system can determine where changes have occurred in the internal structures of the tyre’s rubber and then estimate the physical properties of the rubber in the areas that have undergone these changes. The practical application of this technology will facilitate the design of new rubber compounds that are less prone to performance degradation due to wear and tear, thus contributing to the development and advancement of Performance Sustaining Technology.

Dr. Miki Haseyama, Hokkaido University: We have developed a new AI technology that is able to estimate the extent of changes in the structures based on analysis of images of the internal structures of rubber. As compiling data for this kind of machine learning would otherwise be extremely time-consuming, one of the main merits of this new technology is the fact that this AI does not require prior field data from structural changes in rubber for machine learning. Rather, this AI uses deep learning to learn about the properties of new rubber (i.e. prior to undergoing structural changes) and then estimates the extent of changes in the structure by analysing how data from old rubber (i.e. after undergoing structural changes) compares to the data that it has previously learned about new data. This approach to machine learning allows the AI to automatically detect various types of changes in the structures of rubber.

Kiyoshige Muraoka, Senior Executive Officer, Sumitomo Rubber Industries: We have been working jointly with Hokkaido University to further advance the development of AI technology that can understand how the internal structures of tyre rubber change through use. We have already put this new technology to use in the development of our latest “ENASAVE NEXT III” fuel-efficient tyres, which not only achieve the highest possible “AAA-a” rating for fuel efficiency and wet grip performance (under Japan’s tyre labelling system), but also reduce changes in tyre performance that occur over time as a result of use by half. Moving forward, we will continue to advance our Tire Leap AI Analysis technology to find and analyse slight variations in the internal structures of rubber that human senses and knowhow have been unable to detect so that we can then use the resulting knowledge to develop new technologies that further enhance tyre performance and ensure that this high performance lasts longer. In this way, we will accelerate research and development toward producing high-performance tyres that provide greater safety and peace of mind with the aim of contributing to the realisation of a sustainable mobility society for future generations.

References:

Ren Togo, Naoki Saito, Takahiro Ogawa, Miki Haseyama, “Estimating regions of deterioration in electron microscope images of rubber materials via a transfer learning-based anomaly detection model,” IEEE Access, vol. 7, pp. 162395-162404, 2019.