Jeremias Neuhaus: “One of the biggest challenges in adopting data-driven solutions in the tyre industry is the availability of data and convincing customers not just of the solution itself but of the value of data transfer and real-time monitoring."

The tyre industry faces a significant challenge in data availability with fragmented supply chains, a lack of standardisation and minimal digital infrastructure limiting operational efficiency. Despite the growing importance of predictive maintenance, many manufacturers still rely on manual processes, while competitive concerns and regulatory restrictions further restrict data sharing. This absence of real-time insights hampers decision-making, making operations reactive rather than proactive. However, digitalisation and advanced data analytics are gradually reshaping the landscape. Solutions like HF Xplore aim to bridge this gap, offering real-time monitoring and predictive capabilities that can drive efficiency, sustainability and cost reduction.

Data availability is a challenge in the tyre industry due to fragmented supply chains, lack of standardisation and limited digital infrastructure. Manufacturers, distributors and recyclers operate in silos, making data consolidation difficult. Many businesses still rely on manual processes, while competitive concerns and regulatory restrictions further limit data sharing. Tracking end-of-life tyres (ELTs) is particularly challenging, impacting recycling efficiency.  

However, data availability is crucial for optimising operations, sustainability and innovation. Real-time data enables predictive maintenance, helping fleet operators reduce downtime and improve safety.

Accurate tracking of tyre usage and recycling supports circular economy initiatives and regulatory compliance. It also enhances research and development initiatives for advanced tyre materials such as electric vehicles and off-the-road (OTR) tyres, ensuring better performance and durability.

Improved data transparency can drive smarter decision-making, cost efficiency and sustainability in the industry. Digitalisation and data standardisation are key to overcoming these challenges.

However, HF Group’s Global Head of Digital Solutions, Jeremias Neuhaus, told Tyre Trends, “One of the biggest challenges in adopting data-driven solutions in the tyre industry is the availability of data and convincing customers not just of the solution itself but of the value of data transfer and real-time monitoring. Many decisions in the industry are still based on gut feeling rather than data-backed insights. Our focus is to bridge this gap by providing transparency into machine performance, enabling customers to make data-driven decisions instead of relying on intuition. By implementing real-time monitoring, we can significantly reduce downtime and help customers optimise processes. Even in the first step of implementation, simply visualising machine health and performance brings immediate value. Customers receive notifications for potential issues, allowing them to take preventive action before costly breakdowns occur.”

“The biggest opportunity in this space lies in the fact that data-driven insights can drastically improve operational efficiency. Once machines are connected and data is flowing, customers gain a much deeper understanding of the equipment, leading to better decision-making and optimised production cycles. Predictive maintenance and AI-driven analytics will further enhance operations by identifying potential failures before they occur. This is particularly crucial as manufacturers aim to reduce carbon emissions and energy consumption while increasing efficiency. Our approach stepwise towards AI-powered predictive solutions bring even greater efficiency and cost savings,” he added.

A critical concern in the tyre industry is data security and confidentiality, given how secretive manufacturers are about the respective production processes. “We address these concerns by focusing strictly on machine data rather than the proprietary tyre-making process. Our solutions do not need the actual process details to provide valuable insights. Additionally, the real, detailed data remains visible only to the customer, ensuring that they retain full control. In cases where AI-driven analytics are implemented, we collaborate closely with customers to develop models tailored to specific needs without compromising sensitive production data,” revealed Neuhaus.

The company launched the HF Xplore few years ago as a condition monitoring solution purely for curing presses. One of the significant developments following the merger of HF Mixing Group and HF Tire Tech Group has been the integration of previous initiatives into a joint project, creating a common condition monitoring solution. As a result, HF Xplore is now available for both curing presses and mixer lines. This expansion allows the company to offer real-time monitoring and predictive insights across two of the most critical processes in tyre manufacturing curing and mixing.

MONITORING TYRE FORMULATIONS

Curing and mixing are fundamentally different processes in tyre making, which presents a challenge in making HF Xplore compatible with both. The solution is to split monitoring into two layers viz-a-viz a common monitoring framework and machine-specific components.

The common framework includes monitoring cycle times, alarms, key performance indicators (KPIs) and production progress – elements that apply to both curing presses and mixer lines. However, each machine type has unique components that require dedicated monitoring.

For curing presses, especially electric-curing, HF Xplore focuses on monitoring hydraulic power unit and the electric curing, which is a crucial aspect of efficiency and quality control. On the other hand, for mixers, the system focuses on critical mechanical components such as the RAM movement, feeding mechanisms and drop doors, which are key areas that directly impact mixing performance and consistency. The drop doors, for instance, play a crucial role   in ensuring a smooth transition of rubber to the downstream process, making their monitoring essential for operational reliability.

The user interface of HF Xplore is designed to maintain familiarity across different machines. The dashboard layout remains consistent, so users who are accustomed to using it for curing presses will find a similar experience when working with mixer lines. This consistency reduces the learning curve and makes the system more intuitive for users handling both curing and mixing equipment.

Behind the scenes, the company is investing heavily in data modelling to refine and improve predictive capabilities. The company is developing individualised, flexible data models tailored to each machine type.

These models analyse operational patterns, detect anomalies and provide real-time insights to minimise downtime. By combining machine-specific expertise with data-driven intelligence, HF Xplore continues to evolve into a powerful predictive maintenance and performance optimisation tool for the tyre manufacturing industry.

INTO DATA MODELS

HF Xplore captures machine data but doesn’t analyse it directly. Instead, the system applies background logic to determine whether values are within acceptable limits. Currently, its primary function is real-time status monitoring, giving users an overview of machine condition. However, future iterations will introduce predictive maintenance capabilities, allowing companies to anticipate and address potential failures before they happen.

“At this stage, HF Xplore detects and predicts issues but does not provide specific solutions. As the technology evolves, it will go beyond identifying potential failures to offering actionable recommendations. This shift will help businesses move from reactive maintenance to a more proactive approach, reducing downtime and improving operational efficiency. To refine predictive maintenance, the system is being trained with large datasets in collaboration with customers. Over time, this will enhance the system’s accuracy, enabling it to not only flag potential issues but also suggest corrective actions,” informed Neuhaus.

AI and machine learning will play a central role in the company’s future roadmap, following a structured three-step approach – visualise, analyse and predict.

The first step will provide real-time machine status and process transparency. In the analyse phase, the company’s solutions will move beyond monitoring to offer deeper insights. The system will evaluate performance trends, identify operational limits and provide status feedback. The final phase will be where AI and machine learning take centre stage by analysing vast amounts of historical and real-time data. AI models will identify patterns, forecast failures and recommend preventive actions.

Commenting on whether implementing HF Xplore for a curing press or a mixing system presents different challenges, he said, “While both require detailed monitoring, mixing systems are more complex due to the interconnected components including upstream and downstream processes. Unlike curing presses, which operate as standalone units, mixing lines require data collection across multiple machines for effective monitoring. However, HF Xplore benefits from deep integration with its own equipment, leveraging PLC data to ensure seamless functionality across different systems.”

But for this to be a reality, different data models are pivotal. “The data model is essential for structuring and standardising the information displayed on the dashboard,” informed Neuhaus.

RETROFITTING HF XPLORE

HF Xplore is compatible with both greenfield and brownfield machines, though older models with outdated PLCs may have limitations. “While we cannot retrofit machines that are using old automation solutions, HF Xplore can be integrated into machines from the past few years, especially for condition monitoring. With electric-curing, it also enables precise tracking of electric curing performance, enabling deeper insights,” informed Neuhaus.

“One key challenge is data governance and security. Traditionally, machine data remained within the plant, but HF Xplore connects operational technology with information technology, raising concerns about data ownership and security. To address this, we have implemented user-based access controls, IP-based security and data encryption,” informed the executive.

For tyre plants with a mix of HF and non-HF machines, HF Xplore offers a custom dashboard creator with low-code functionality, allowing users to integrate and visualise data from different machines in just a few hours. A flexible data model further ensures standardised visualisation, even when machine types vary. While full integration with non-HF machines may require additional work, HF Xplore provides a comprehensive plant-wide monitoring solution for optimising performance.

“HF Xplore can potentially integrate with machines from other companies, but it depends on data accessibility and PLC compatibility”, contended Neuhaus, who highlighted the flexibility and modularity of their solution. 

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Yokohama Rubber has established a new research and development centre in Hangzhou, China, as the Japanese tyre maker seeks to strengthen localised product development and speed up response times in the Chinese market.

The new facility, named Yokohama China Technical Center, began operations in May within the company’s new passenger car tyre plant in Hangzhou, which started production in November 2025.

The company said the centre would enable the local development of products specifically for the Chinese market, from initial research through to completion, helping to accelerate product launches and improve responsiveness to regional demand.

The centre will consolidate R&D functions for Yokohama Rubber’s tyre and multiple business divisions in China, while expanding engineering staff and testing facilities. Its activities will include tyre development, raw material analysis and evaluation, supplier audits, and mould drawing preparation.

Yokohama Rubber said the new operation would also support research into new raw materials and the development of local suppliers in China.

The company currently operates tyre plants in Hangzhou and Suzhou, alongside multiple business plants in Hangzhou and Weifang.

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Chhattisgarh-based technology company Aarika Innovation has introduced KoolWheel, an automated tyre water spray cooling system manufactured in India.

The product is designed for freight vehicles and school buses to manage tyre overheating caused by road surface temperatures.

The system uses IR (infrared) temperature sensors, a 5-bar pump and solenoid valves to spray a mist on tyres when temperatures exceed a threshold. The hardware operates on a 12V setup and includes a controller that requires no driver intervention. Dashboard indicators and buzzers provide alerts regarding system status and temperature levels.

The company has introduced two variants of the product for KoolWheel Freight, which is designed for trucks, trailers and multi-axle vehicles, covering up to 22 tyres across six axles. And KoolWheel SchoolSafe, which is developed for school buses and coaches, featuring a 50-litre stainless steel tank and an automatic shutoff to prevent battery drain.

The company states the system can reduce tyre temperatures by up to 25deg Celsius and extend tyre life by up to 35 percent. The technology is intended to reduce the risk of blowouts and maintenance costs for fleet operators. The product is currently available in markets including Chhattisgarh, Madhya Pradesh, Maharashtra, Uttar Pradesh, Rajasthan and Telangana.

Swayam Agarwal, Founder, Aarika Innovation, said, “KoolWheel has been created to solve a very real problem faced by Indian transporters and school bus operators every day. Tyre overheating is not just a maintenance issue; it directly impacts road safety, operating costs, and fleet reliability. With KoolWheel, our aim is to offer an affordable, intelligent, and Made-in-India solution that helps fleets run safer, longer, and more efficiently.”

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European tyre major Pirelli is starting production of its Cyber Tyre technology at its plant in Georgia. The facility produces tyres for the US market, including products for the motorsport segment.

The announcement occurred during the SelectUSA Investment Summit. Cyber Tyre is a system that collects data from sensors embedded in tyres. This data is processed through software and algorithms to communicate with vehicle electronics. The system is intended to integrate with driving systems to provide functionalities for mobility and safety.

Pirelli is also introducing the Modular Integrated Robotised System (MIRS) at the factory. This manufacturing process uses robots to manage productivity and quality. The system creates a link between product design and application. This update is intended to increase the production capacity of the site.

The Georgia plant has operated for over two decades and includes a research and development centre. The facility uses natural rubber certified by the Forest Stewardship Council.

Claudio Zanardo, CEO of Pirelli North America, said, “The start of Cyber Tyre production in our Rome, Georgia plant is a significant milestone for Pirelli in this country. It reflects our commitment to bringing advanced technologies like Cyber Tyre closer to the market, further strengthening our industrial footprint and innovation capabilities in the United States.”

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The Yokohama Rubber Co., Ltd. developed a proprietary tyre mould design support system in April 2026, integrating finite element method (FEM) simulations and the company’s own artificial intelligence technology. This new tool is designed to augment the expertise of development personnel, enabling even less experienced staff to efficiently design moulds. It achieves this by providing data derived from numerous virtual experiments, which clarify how different mould design factors influence tyre characteristics.

The system accelerates mould development, lowers costs and minimises the rework typically associated with realising new designs. Furthermore, by fostering a multi-perspective understanding of the links between mould design elements and tyre performance, the tool equips Yokohama Rubber’s developers with fresh insights. These discoveries are expected to aid in creating tyres capable of achieving higher performance levels.

Developed under Yokohama Rubber’s HAICoLab AI concept launched in October 2020, the system addresses longstanding challenges. Mould design critically affects tyre traits, but traditionally understanding this relationship required expensive, time-consuming trial production and evaluations. The process also depended heavily on the tacit know-how of highly experienced staff, leading to variations in accuracy and development time based on individual expertise.

The support system resolves these issues through automated simulations and AI-based prediction and visualisation. It first generates numerous tyre FEM models with varied mould shapes and calculates their characteristics in a virtual space. These results train an AI surrogate model that instantly predicts design factor-performance relationships. By applying explainable AI technologies like SHAP and Partial Dependence Plots, the company’s developers can quantitatively visualise each factor’s impact, easily determining necessary adjustments to achieve targeted tyre characteristics.

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