Artificial intelligence (AI) is steadily moving from experimentation to practical deployment in tyre manufacturing, where complex processes and variable raw materials often limit the effectiveness of fixed production standards. By analysing large volumes of plant data and responding to real-time process conditions, AI-driven optimisation systems are helping manufacturers improve efficiency, reduce waste and stabilise product quality. In an interaction with Tyre Trends, Vincent Barjaud of Braincube explains how such systems are transforming key production stages including mixing, extrusion and curing while complementing operator expertise.

The tyre industry indeed depends heavily on raw materials with significant variability, particularly those derived from natural sources and petrochemicals. These materials change over time and therefore are not always consistent in terms of quality and performance. Because industrial processes operate under constantly changing conditions, fixed production standards often create a hidden performance ceiling. Systems capable of adapting to real-time conditions allow plants to consistently reach the best achievable operating point.

Artificial Intelligence (AI) is helping manufacturers move beyond fixed production standards towards more adaptive approaches. Real-Time Process Optimisation (RTPO) processes historical and real-time plant data to continuously adjust operating setpoints based on live process conditions. By responding to variability in raw materials, equipment behaviour and operating environments, RTPO enables plants to consistently operate closer to their optimal performance point.

Speaking exclusive to Tyre Trends on the integration of AI, Technical Partner Manager at France-based Technology firm Braincube, Vicent Barjaud, said, “Our AI-driven solution provides real-time process optimisation by recommending the exact action operators should take, on which actuator and at what moment. Instead of suggesting a broad operating range, the system recommends the precise optimal value in real time. Because operating context evolve during production, this optimal value may change within hours. The system continuously adapts to these changes to maintain optimal performance.” The company devises solutions to address the entire tyre manufacturing process, but the software is particularly effective in compound mixing, extrusion and curing, where material transformation through machine actuation makes these stages highly process-oriented and suitable for optimisation.

The implementation typically takes six to twelve weeks from project kick-off to go-live. During this phase, plant data sources are connected and structured for AI analysis without requiring access to confidential compound formulations.

Since most industrial players maintain historical data through data historians, this data is injected into the system, enabling real-time optimisation and recommendations from day one, and in rare cases where no historical data exists, a few weeks are required to gather sufficient operational data.

The solution can be implemented in any plant equipped with PLC-based automation systems, while additional digital systems such as MES, ERP or LIMS improve recommendation accuracy, although valuable real-time operator guidance can still be delivered with only historian data and basic inputs.

ROOM FOR IMPROVEMENT

According to Barjaud, one of the biggest opportunities for improvement lies in the uniformity of the final tyre, particularly during quality control at the end of production. This is largely due to the curing stage.

“Plants often operate dozens of different curing moulds. Each mould functions as an individual asset, but many manufacturers treat them as if they were identical. In reality, each mould behaves slightly differently, which can affect tyre uniformity. Recognising and optimising these individual differences can significantly improve efficiency and product consistency,” he added.

It is considered beneficial to treat each curing mould individually because every mould has distinct characteristics including differences in lifetime, behaviour, wear patterns, maintenance history and the time since its last servicing.

When moulds are treated as identical, these variations are overlooked. By managing each mould separately rather than as part of a uniform group, process optimisation can be achieved more precisely, resulting in improved efficiency and performance.

“Strong optimisation results have also been observed in extrusion, where start-up phases of new process orders typically generate scrap as the first few metres of material are discarded before reaching a steady state. By adjusting process parameters more precisely, the time required to reach this steady state can be reduced, thereby lowering start-up waste,” noted Barjaud.

Braincube’s optimisation approach works similarly to navigation apps such as Waze or Google Maps, which continuously adjust routes based on real-time traffic conditions to reach a destination faster.

In the same way, Braincube dynamically updates manufacturing parameter recommendations as process conditions change. Similar to navigation applications such as Waze or Google Maps, the system continuously adjusts the optimal ‘route’ for the process as new conditions emerge.

The approach also applies to extrusion processes, where significant material waste often occurs during machine ramp-up. By helping operators set the correct parameters from the first seconds of operation, the company reduces the amount of material that must be scrapped at start-up.

INTO MANUFACTURING

Braincube works with tyre plant engineering teams to define ideal performance targets such as acceptable tyre uniformity ranges. It analyses production data to identify the actuators and operating conditions that drive optimal results and provides real-time insights to operators so processes can be adjusted to keep tyres within the desired ‘super zone’ of uniformity.

In mixing, its system addresses inefficiencies during product changeovers. Since the first batch after a changeover starts under different conditions such as temperature, roll distance and machine state, it separates the recipe for the first batch from subsequent batches, ensuring consistent viscosity and composition while reducing the higher scrap rate typically seen in the first batch.

For curing, Braincube performs real-time optimisation by adjusting parameters such as steam injection, temperature and curing duration based on the specific mould and its operating conditions. It also helps extend mould lifetime by identifying moulds that can safely operate beyond the usual maintenance threshold of around 3,000 tyres, potentially extending their life by 20–50 percent.

Overall, waste reduction comes from replacing fixed production standards with dynamic optimisation, where the system continuously analyses real-time conditions and recommends adjustments to recipes and operating parameters, improving efficiency while lowering scrap and environmental impact.

“In one case with a top-five global tyre manufacturer that deployed Braincube across its factories, we observed waste reduction of around 70 percent during the extrusion start-up phase. This level of improvement can significantly reduce both material losses and production costs,” noted Barjaud.

MACHINE NEEDS MAN

Braincube approaches root-cause analysis by identifying the drivers of success rather than only analysing defects. Instead of focusing solely on scrap and deviations, the system studies past production data to determine the conditions under which the best tyres were produced.

By analysing the highest-performance production runs including machines, operators, raw materials and process conditions, it identifies the key factors behind superior performance and recommends settings that help replicate those results consistently.

Installing Braincube mainly involves resolving material traceability across the plant. During a six-to-twelve-week integration phase, the system connects to existing data sources and reconstructs where each product was at specific times in the factory.

Once this mapping is completed, Braincube can continuously process data and perform automated optimisation. Plants with strong traceability systems integrate more easily, while others may require certain assumptions during setup.

“Our solution’s recommendations typically achieve more than 90 percent accuracy, but the system is designed to assist operators rather than automatically enforce actions. Operators receive recommendations but remain fully in control of whether to apply them. If a recommendation is rejected, the system immediately recalculates a new suggestion based on the updated operating conditions,” explained Barjaud.

He added, “This human oversight is important because some real-world conditions may not be captured in the dataset. For example, a lower operating temperature may have produced good results in the past because a machine door was open, affecting process conditions. If that factor was not recorded by sensors, the system may initially recommend the same temperature again even though the door is now closed. In such cases, operators can reject the suggestion, ensuring that AI insights are balanced with practical judgment.”

Barjaud contended that operator expertise remains essential when using AI systems. While the system provides data-driven recommendations, experienced operators play a critical role in deciding whether to apply them.

Their deep understanding of the process ensures that AI insights are used appropriately, making the combination of human expertise and AI analysis key to achieving the best production results.

IMPLEMENTATION AND SAFETY

The company also partners with machine manufacturers through white-label agreements, allowing them to offer Braincube-powered optimisation services alongside their equipment. This enables customers to benefit not only from the machinery itself but also from continuous performance optimisation.

In the tyre industry, Braincube currently focuses on mixing, extrusion and curing and still sees major opportunities to expand optimisation in these processes. Even when analysing a specific stage such as curing or tyre uniformity, the system incorporates data from upstream operations like building and other production steps to understand the factors affecting final performance.

The emphasis on optimisation ultimately centres on the final KPI, since this reflects what customers pay for, which is finished tyre quality and uniformity. By integrating data from across the entire plant including upstream processes and raw materials, Braincube helps manufacturers consistently meet required product performance standards.

Also, many tyre makers have more than one manufacturing unit. Integrating Braincube’s solution across each one requires a simple collaborative excursive involving the French company’s team and a ‘Champion’.

“Most companies appoint a champion or a dedicated engineer responsible for replicating successes across plants. This person ensures that the best practices identified in one plant are standardised and implemented across other facilities,” explained Barjaud.

He added that companies usually deploy Braincube as a technical solution while also establishing a human organisational structure to drive replication and standardisation. The combination of technology and internal leadership ensures that improvements are scaled across multiple plants.

Besides, data security is a top priority for Braincube, especially because industrial manufacturing data is highly sensitive. The system complies with major cybersecurity standards such as ISO 27001 and SOC 2, and in its 18 years of operation, it has never experienced a data breach.

The company regularly conducts external penetration tests, maintains a dedicated cybersecurity team and operates under the supervision of a Chief Information Security Officer (CISO) responsible for vulnerability management and system protection.

Regarding concerns about job replacement, Barjaud reported little resistance from engineers or operators. “Industrial environments have evolved through successive technological stages, from manual decisions to PLCs, closed-loop control, advanced process control and now AI. In this context, AI is generally viewed as the next step in improving efficiency, helping people make better decisions rather than replacing them,” he noted.

MARKET VIEW

Braincube operates globally with a full operational office in Europe but also has offices in United States and Brazil, which has supported the Latin American market for about 15 years.

From Europe, the company manages both European and Asian markets and works with several software distribution partners worldwide including in Thailand, India, Poland, Germany, Spain, Switzerland, UK and Italy, collaborating with firms such as Ematica to deliver and integrate its solutions.

In Asia, particularly in India and Southeast Asia, Braincube mainly relies on local partners rather than establishing its own offices. These partners, often industrial software distributors already working with automation systems, MES platforms and data historians such as AVEVA, handle integration and customer engagement.

The company is also engaging with new tyre manufacturers in Asia, typically through those partners who add Braincube’s AI-driven optimisation to their existing portfolios of PLC, SCADA and MES solutions.

Concluding the interaction, Barjaud pointed out that one of the biggest challenges for AI providers in the tyre industry is balancing multiple objectives such as throughput, energy consumption, material usage and product quality. n

AI mobile data capture company Anyline has released the latest version of TireBuddy, a smartphone-based system for automotive tyre inspections. Version 1.8 introduces fully automated sidewall capture that removes human variability from data collection. The tool has already helped service teams achieve faster, more uniform inspections over the past year, leading to increased tyre sales and stronger customer trust.

The automated mechanism uses on-device guidance that evaluates each image against four criteria: full sidewall detection, sharpness, proper distance and angle and overall clarity. This real-time feedback minimises redo scans by guiding technicians to capture optimal images immediately. The system addresses common challenges in busy service bays where accuracy often suffers due to varying experience levels.

Standardisation of inspection quality is a primary benefit, as consistent results are achieved regardless of who holds the phone. This removes dependency on technician skill or training duration. New or seasonal staff can perform scans confidently from day one without extensive instruction. The automated capture now serves as the standard protocol for all inspections across locations and shifts.

Additional features include tyre mismatch alerts that flag size discrepancies, automated email reports to back-office systems and a redesigned results screen consolidating sidewall information and tread measurements. With hundreds of thousands of annual inspections, this update reinforces TireBuddy's role in modernising tyre service operations.

Lukas Kinigadner, CRO, Anyline, said, “A shop is only as consistent as its least experienced inspector. Automated sidewall capture gets every scan to the same standard, so teams can stop treating inspection quality as a variable.”

Epson, a global leader in SCARA robot manufacturing, has unveiled its next-generation industrial robotics portfolio at Automation Expo Mumbai 2026. The newly introduced lineup features the high-end CX-A Series 6-axis robots, the LS-C Series SCARA robots, the RC+ 8.0 programming software and the advanced SafeSense safety technology, all designed to address diverse manufacturing applications such as pick-and-place, precision assembly, parts transfer and material handling.

The new offerings significantly expand Epson’s existing industrial robotics family, which already includes the 6-axis C-Series and SCARA T-Series and LS-Series models with payloads ranging from 3 to 20 kilogrammes. With the addition of the CX-A and LS-C Series, manufacturers across various sectors can achieve heightened productivity, flexibility and operational efficiency. The CX-A Series is engineered for complex tasks with a payload capacity of up to seven kilogrammes and a reach of 900 millimetres, available in IP67, cleanroom and ESD variants, while the LS-C Series provides a compact SCARA platform with a 50-kilogramme payload, a 1,000-millimetre reach and cycle times as fast as 0.298 seconds.

Complementing the hardware, the RC+ 8.0 software offers an integrated environment for programming, simulation and system management, facilitating faster automation deployment with support for Visual Studio and C++ development. Additional efficiency features include enhanced diagnostics, OPC UA, GUI builder and safety functions, alongside co-creation tools like Library Builder and RC+ Extension. Meanwhile, the SafeSense technology promotes safer human-robot collaboration by incorporating Safety Limited Speed and Safety Limited Position functions, which can potentially reduce the need for extensive safety fencing and thereby increase operational flexibility.

With over four decades of industrial robotics expertise and more than 200,000 robotic arms deployed globally, Epson continues to drive operational excellence for businesses. Attendees at Automation Expo Mumbai 2026 have the opportunity to view live demonstrations of these solutions and consult with Epson specialists about transforming their manufacturing operations.

Siva Kumar, Sr General Manager – Sales and Marketing, Epson India, said, "India is rapidly emerging as a global manufacturing hub, and automation will play a pivotal role in shaping its future. With our new industrial robot lineup and RC+ 8.0 platform, Epson is delivering the speed, precision and intelligence manufacturers need to compete in an increasingly dynamic marketplace. We remain committed to enabling businesses to accelerate automation adoption and build smarter, more agile and globally competitive manufacturing operations."

A consortium of Fraunhofer institutes has reached a key milestone in the Technology Platform for Tire Abrasion and the Identification of its Emissions in Road Traffic (TERIS) project, moving closer to establishing standardised laboratory methods for generating, analysing and predicting tyre wear.

The project, led by the Fraunhofer Institute for Structural Durability and System Reliability LBF, together with Fraunhofer ICT, Fraunhofer IGD and Fraunhofer IWM, aims to provide the tyre industry, testing organisations and environmental agencies with reliable and practical laboratory procedures for assessing tyre abrasion emissions.

The first project milestone has been completed following a successful review by an advisory board comprising industry experts.

The consortium has developed reference methods for tyre abrasion, particle analysis, tribological modelling, artificial intelligence-based surface analysis, a laboratory test bench concept, accelerated ageing techniques and volatile organic compound (VOC) detection.

According to the consortium, combining different particle collection and measurement techniques enables more precise analysis of both airborne and deposited tyre wear particles. At the same time, tribological models have been developed to better understand the relationship between loading conditions, material properties, surface structures and particle formation, allowing real-world tyre wear processes to be replicated under laboratory conditions.

Researchers have also developed a specialised test chamber for accelerated ageing, enabling tyre samples to be exposed to controlled environmental conditions before evaluating their abrasion behaviour.

Another development is an optical detection system that uses artificial intelligence to identify and classify surface structures. The system has been validated using substitute materials and is expected to be applied to rubber samples during the next phase of the project.

The consortium has also designed a laboratory test bench that combines multiaxial loading, controlled generation of tyre wear particles, targeted particle collection and integrated optical sensors within a single testing platform.

In addition, the project combines accelerated weathering with chemical analysis of volatile organic compounds released from tyre abrasion to assess the environmental impact of tyre wear particles.

The researchers said the work will provide the foundation for faster and more practical laboratory evaluation of new rubber compounds. The resulting methods are intended to help tyre manufacturers reduce emissions, accelerate product development and support compliance with the requirements of the Euro 7 standard.

At Fraunhofer IWM, researchers focused on refining tribological wear models and friction surface concepts to simulate particle formation under controlled laboratory conditions. The institute designed a parameterisable wear test that studies friction between plate materials and model surfaces with different structures, enabling researchers to investigate the mechanisms responsible for particle generation.

Initial findings indicate that tyre wear results from multiple interacting mechanisms rather than a simple relationship between particle emissions and factors such as speed, contact force or temperature. The researchers collected and analysed particles across a wide range of sizes during the study.

ZF has secured a significant milestone in the Indian automotive sector, receiving three major orders for its advanced test systems. The contracts, which encompass battery, tyre and e-axle testing, position the global driveline and chassis technology leader at the forefront of the nation’s drive to enhance road safety and establish more robust vehicle certification processes. This development aligns with India’s accelerating regulatory efforts to ensure that vehicle testing becomes more independent, rigorous and comprehensive, marking a critical step forward for the industry.

A key aspect of ZF's strategy involves a strong commitment to local manufacturing, with the company emphasising high levels of domestic content for its test systems in support of the ‘Make in India’ initiative. The firm’s extensive background in the field is underscored by its experience in testing over 100 million transmissions, a testament to the proven global reliability of its technology. This foundation of expertise is now being applied to address the specific safety and performance demands emerging in the Indian market.

With the rapid adoption of electric vehicles, battery safety has become a paramount concern, and ZF’s solutions cover the complete spectrum from individual cells to complete packs. These systems evaluate performance, endurance and environmental factors, including rigorous mechanical abuse testing, while adhering to a wide array of international and Indian standards. Furthermore, the company’s tyre testing capabilities are poised to play a crucial role as India prepares to enforce new mandatory regulations, including the BNVSAP and the AIS 142 TPMS Mandate. The ZF Tyre Efficiency Tester (TET.lab), recognised for its precision, offers a modular platform capable of testing everything from motorcycles to heavy commercial vehicles.

The company’s e-mobility test benches feature a high-performance drive module with a flexible, modular architecture designed to accommodate both conventional and electric drivetrains. These systems can be configured for various operations, integrating frequency converters and precision measurement technology for comprehensive testing. ZF’s deep expertise, already deployed by manufacturers and testing authorities worldwide, positions it as a key technology partner for India. As regulatory requirements tighten and the demand for quality escalates, the company is set to support the nation's ambition of building a safe and sustainable automotive ecosystem.

Akash Passey, President, ZF Group India, said, “Testing agencies are the final arbiters of vehicle safety, the bodies whose certification regulators and the public trust. Being chosen across three independent and Government agencies, for three distinct testing disciplines, is a powerful validation of ZF's accuracy, reliability and deep understanding of India's regulatory and testing landscape. ZF Group is proud to provide the technical foundation that makes world-class automotive safety infrastructure possible in India, not just for our OEM customers but also for Government and independent testing agencies.”

Thomas Trebitsch, Vice President, ZF Test Systems and Testing, said, “Over the past years, we have been focusing on the tyre industry in India and introducing our complete product portfolio to India. As the market develops rapidly towards regulations and safety, there is a strong need for robust and world-class testing technology. ZF brings its global competence and a deep understanding of the Indian auto industry to address its specific needs.”