When we discuss about a motorcycle's performance, we generally speak about its engine power, torque, top speed, how fast it can accelerate, vehicle sound etc. Nevertheless, all these are meaningless if a driver cannot control the machine and/or is not comfortable while riding. There comes the importance of tyres. Tyres are the most crucial parts of a vehicle suspension system.  Tyres are the only component in a motorcycle that constantly stays in contact with the road. The part of tread which is in contact with road surface is called ‘contact patch’ & Is about half the size of a post card.  The overall suspension system (including tyres) ensures the right contact between the tires and the road surface at every stage of driving, thereby ensuring stability and good handling of the vehicle.

As tyres are the only contact with the road, they are responsible for multiple functions, such as –

Transfer the engine power to the road- meeting the demands of acceleration and braking

  Provides right hold (grip) on different surfaces like dry, wet, snow, loose soils etc.

  Helps the rider to steer the vehicle by responding to the handle movements

  Carry the weight of the vehicle & rider

 Ensuring the comfort of the rider by absorbing and dampening shock

Apart from the above aspects, tyres play a vital role in vehicle aesthetics, safety, fuel efficiency etc. These and several other challenges make Motorcycle tyre design a very interesting and responsible subject.

Apart from being a crucial part of a vehicle suspension system, tyres are the only contact between vehicle & road. Motorcycle vehicle dynamics and control characteristics are highly influenced by the tyre design. It is therefore highly imperative for a vehicle chase/suspension designer & tyre designer to work together in tandem. This will ensure that the part designs will complement each other and deliver the characteristic target performance of a motorcycle. A robust interaction mechanism between the R&Ds of OEM [Original Equipment Manufactures] and tyre manufactures is a growing necessity to cater to the ever‐increasing demands of performance entrusted upon the tyre of today. In case of tyres getting designed exclusively for aftermarket, a tyre designer work closely with the vehicle dynamics team to ensure that the retrofit design delivers desired target performance of the vehicle

Some of the major steps involved in motorcycle tyre design are

 Product planning & Tyre “Size” finalization: During this stage a vehicle designer & tyre designer jointly review the vehicle performance requirements and decides the parameters specific to tyre performance. This includes:

Defying the application /terrine: Depending on application, 2 wheelers maybe broadly classified as Sport, Cruiser, Choppers, Touring, scooter, Step through, Sport touring, Enduro etc. Different OEM’s follow different terminologies, but a for a tyre designer to understand the final use by the user is of utmost importance. Demands from a tyre varies with each vehicle category, for example, for a cruiser the tyre is designed to be robust so as to hold up the weight of such heavy bikes and deliver long tyre life, whereas for a Sport touring /super sport bike, tyres are  designed to deliver quick and precise handling with superior grip. These tires are lighter and made by using softer compounds for Superior grip.

Selection of Bias /Bias belted / Radial:   At this juncture, I am not going to delve deeper into a detailed comparison of these constructions – however, it is important to acknowledge that both these construction types have their respective advantages and disadvantages. Each of these constructions has few specific applications where one performs better than the other. The selection of construction type mainly depends on vehicle category (application), vehicle Speed, load on the tyre, stability requirements, handling requirements, etc. for example Bias tyres are used in medium speed but heavy weight vehicles owing to their sturdy sidewalls, whereas Radial tyres are the ideal choice for high speed , vehicles because of their superior dimensional stability.

Selection of Tube type Vs Tubeless:  Functionally both types of tyres have a proven track record for almost all applications. Hence this choice mainly depends on vehicle Rim design, which is decided by the overall aesthetic demand & application of the motorcycle.For high speed application, tubeless is always preferred

Finalizing the Tyre size / Tyre Geometry:  In general, we may call it as tyre “size” – which includes tyre width, tyre diameter, rim diameter etc. Tyre geometry affects the vehicle dynamics like caster, trail, vehicle Center of gravity [CoG], etc. It also influences the area of contact between vehicle and road surface under different riding conditions & load-carrying capacity of the tyres. Furthermore, tyre size significantly influences vehicle aesthetic as well.  Tyre “size” and vehicle rim size are always interconnected. Decision on one influence the decision on the other.  Usually motorcycles have different front and rear tyre sizes depending on vehicle geometry & load distribution. Tyre “sizes” are decided considering all these parameters & the designers ensures that it follows the standards’ guidelines applicable in target countries.

Tyre tread profile design:

Contrary to the passenger car tyre designs which have almost flat tread surface, motorcycle tires have a U-shaped profile and a contact patch that changes size and shape during cornering. There is a major difference in the way lateral force is built up in passenger car and two wheelers.  In case of passenger car, mechanism of lateral force builds up is due to slip angle whereas in two-wheeler it is mainly because of the camber or the leaning of the vehicle.  Hence you see a flat tread area for passenger car tyre and U-shaped profile for Motorcycle tyre

This U-shaped profile is an important design factor having a direct influence on vehicle performances such as drivability (handling) durability, ride comfort, noise and wear resistance etc.

These tread contours are designed as the arc of one radius, or a combination of arcs with two or more radii. These profiles ensure the required contact patch availability at different lean angles & are controlled by the lean characteristic of the vehicles. It is very critical to balance the performance of front tyre & rear tyre of s motorcycle for precise handling of the vehicle. The contour designs play an important role in front /Rear tyre balance.

Tyre tread pattern design:

Patterns are molded in the tread area of tyre by repeated arrangement of ‘Groves’ or ‘Blocks’ & are generally referred to as “tread pattern”.

Significance of tread pattern: 

Tread pattern plays a vital role in tyre performance such as:

Optimizing the traction on the riding surface

Eliminating aquaplaning

Optimizing the” Wear” of tread area·  

Ensuring the continuity of tyre performance at different wear Stages [ wear %] of tyre.

Rolling resistance of the tyre

Noise generation

roviding a measurable clue to the owner on time for removal /suitability for continuous usage. etc.

Tread patterns not only helps in achieving the target performance, but also impart unique look to tyres and enhance aesthetics

Tyre patterns are broadly classified into 4 Major headings

• Rib patterns
• Directional
• Block [ Knobby]
• Slick tyres [Pattern less]

Selection of which group of patterns is mainly controlled by the terrain of application, e.g. Directional patterns are preferred in paved roads and knobby pattern ae mainly used on off-road applications. Pattern less tyres are normally used in racing track applications to provide maximum traction.  Vehicles are designed to work in a combination of different terrains – similarly, tread patterns also have subgroups– which are optimized to operate in different combination of terrains. E.g. Semi knobby patterns for on – off allocations, High land – minimum grove patterns for Supersport highway applications etc.

Designer alter the direction of the grove, depth of the grove, number of groves, the ratio between Grove area & non grove area [ Land- sea ratio] , shape of the grove, the width of the grove etc. to optimize the performance of tread pattern. These patterns are designed to perform under different dynamic conditions. Nowadays designers seek the help of computer-aided simulations to predict the performance under different loading /riding conditions to optimize the pattern design.

Tyre as an Aesthetic component

The visual appeal of tyre is significant contributor in the overall aesthetics of a motorcycle. Hence in addition to performing all the functional requirements discussed so far, tyres ought to look good too.

The tread pattern should complement the overall styling language of a motorcycle. This attracts the attention of OEM’s vehicle styling studios towards tyre tread designs as well. In fact, most of the new tyre designs are done first at styling studio and then technically optimized by the tyre engineer to guarantee the functionality.

Material design

Tyre is a composite material made of different rubber compounds and reinforcing materials. Right compound and reinforcing material selection are crucial to achieve the target performance of tyre.

• Reinforcing materials:

Reinforcing materials provides the required strength and stiffness for tyre body [carcass]. This includes “tyre cords” used in tyre body ply & “bead wires” used in bead construction of tyres. Most used tyre cord materials are Nylon 6, Nylon 6-6, Polyester, Aramid, Rayon, Steel, etc.

These materials differ in their chemical composition, tensile strength, elongation properties, impact strength, temperature resistance, rubber adhesion, etc. Tyre engineer must choose the right tyre cords depending on the performance demands of the tyre like load carrying capacity, durability, impact resistance, drivability, speed of operations etc. Cost & availability also are few decisive parameters during selection of reinforcing materials.

Tyre Cord denier, cord style, EPI (Ends Per Inch), angle of cords and number of plies affect the strength of a tyre and are chosen based on engineering, and design criteria.

structural durability of a tyre is Primarily determined by the reinforcing material

• Rubber compound design

Each part of the tyre must dispense different functions and are thus designed with different rubber compounds like tread compound, sidewall compound, carcass compound, bead wire coat compound, etc.  Though all these compounds have their own importance, but tread compound selection is the most critical, as it has a direct impact on tyre traction, handling, wear performance, durability, rolling resistance, etc.

• • Trends of tread compound design:    

Even though smaller number of components are used in a motorcycle tyre, than as compared with passenger car tyres, but performance challenges involved in compounding are far more complex considering less area of tyre in contact with road. 3 major performance requirements in motorcycle tread compound are (1) Grip (2) Rolling resistance [fuel efficiency] and (3) Tyre life which is generally referred as the magic triangle in tyre rubber compounding. This is due to the contradictory response of these 3 performance characteristics to rubber compounding approach. For example, improvement in Grip normally comes with an increase in rolling resistance with conventional compounding as both are related to energy loss. It is always a challenge for tyre compounder to improve all three performance requirements together and this calls for the incorporation of advanced polymers and fillers.

Performance priorities for tread compound changes based on operating terrain, type of vehicle, etc. e.g. Street two-wheeler tread compound designs primarily focus on high grip and high-speed capabilities, whereas an on-off application tyre require higher cut and chunk resistance tread compound.

Demand for lower rolling resistance tyre is showing a steady increase Year-on-Year. Major divers for this growing demand are Electric vehicle introduction & increased focus on vehicle fuel efficiency, in few segments. Tread compounds are expected to deliver lower rolling resistance, without compromising the Grip – typical “magic triangle” puzzle for any tyre compounding engineer. Tyre industry can address this challenge by usage of new generation materials like SSBR, functionalized SSBR, high molecular

Design for manufacturing

For success of any product – Design & manufacturing sync is a must. While designing, to accommodate all functional requirements, a designer cannot ignore the significance of manufacturing process. Hence every tyre design is optimized to satisfy both functional & manufacturability needs. This if not done properly may result in suboptimal performance of the product,

Product Performance Testing

It’s important to review and verify the product performance before releasing it into the market. There are a set of Indoor & Outdoor tests for performance review. A few of them are listed below,

Indoor tests: High-speed drum test, Endurance test, Rolling resistance test, Force and moment testing, Stiffness test, Footprint etc.

Outdoor tests: Ride and Handling testing (track, off-road, public road etc.], Braking test [wet, dry], tyre wear test etc.

Blend of Engineering & Art

Being an integral part of vehicle suspension system & only contact point with road, a tyre plays significant role in motorcycle performance [safety, drivability etc.]. In addition to these performance parameters, tyres have significant influence on the overall styling of the vehicle. It complements the primary theme of the vehicle. A right blend of engineering and art is essential for a successful tyre design. One cannot substitute the other. Amongst different steps of tyre design like, dimension finalization, tread design & martial design etc. the most critical step is tread design (profile, pattern & compound)

Few areas designers are focusing today to  meet the near/middle future demands are

• Lowering the rolling resistance – without compromising grip
• Shortening the time to market.
• virtual simulation of tyre performance

 

References

1.  ‘’The pneumonic tyre’’, National Highway Traffic Safety Administration, Feb 2006
2. T. French, Tyre Technology, Hilger, New York, 1989.
3. Mechanics of Pneumatic Tires, S. K Clark, ed., University of Michigan, US Department of Transportation, National Highway Traffic Safety Administration, Washington, DC, 20590, 1891.

     4.  Handbook of vehicle-road interaction: vehicle dynamics, suspension design, and road damage / edited by David Cebon. p. cm. - (Advances in engineering), ISBN 9026515545

    5. “Tyre and Vehicle Dynamics” , Hans B. Pacejka,  Professor Emeritus Delft University of Technology, Consultant TNO Automotive Helmond

     The author is General Manager - Product Development,2&3-Wheeler tyres, CEAT Tyres

As generative AI transforms the way consumers and businesses discover products, tyre manufacturers face a fundamental shift in digital marketing. Roshan Mohan, Co-Founder and CMO at FlowBlinq, and Founder of PCG argues that the next battle will no longer be fought on search engine rankings but on whether AI systems choose to recommend a brand in the first place.

For more than two decades, tyre manufacturers have refined their digital strategies around a familiar formula: optimise websites for search engines, invest in paid advertising, strengthen dealer networks and build visibility through reviews and comparison platforms. Success depended largely on securing a prominent position on Google’s search results.

That formula, however, is beginning to change.

The rapid adoption of generative artificial intelligence (AI) platforms such as ChatGPT, Gemini and Claude is reshaping how consumers search for information, compare products and make purchasing decisions. Rather than browsing multiple websites, customers are increasingly asking AI assistants to recommend the most suitable product based on their specific requirements.

For tyre manufacturers, this represents far more than another digital marketing trend. It fundamentally changes how products are discovered.

According to Roshan Mohan, Co-Founder and CMO at FlowBlinq, and Founder of PCG, companies that continue treating AI as simply another marketing channel risk missing a much larger transformation. “The customer journey for tyres has already started bending around AI, and the change over the next three to five years won’t be a redesign of the funnel; it’ll be a shift in where the funnel begins,” he says.

FROM SEARCH ENGINES TO AI CONVERSATIONS

Historically, buying tyres has been an information-intensive process. Consumers often compare technical specifications, dealer recommendations, user reviews, pricing and compatibility before making a purchase. Search engines have traditionally served as the starting point for that journey.

Generative AI is simplifying this process dramatically.  Instead of opening multiple browser tabs and manually comparing products, motorists can simply ask an AI assistant for recommendations based on vehicle type, budget, driving conditions and performance priorities. The AI then synthesises information from numerous sources into a single response. “What changes for the buyer is effort, not intent. They still want the right tyre for their car and budget, but instead of researching options and making the final comparison themselves, they are increasingly describing their needs to AI and letting it identify the best solution,” Mohan explains.

This shift effectively transfers much of the research process from the consumer to the AI model.

Industry forecasts suggest this transition is already underway. Gartner predicts traditional search engine volume will decline by 25 percent by 2026 as generative AI absorbs many queries that previously began with conventional search engines. Meanwhile, Checkout.com’s research indicates that consumers are embracing AI-assisted purchasing faster than many businesses are preparing for.

For tyre companies, the implication is profound: visibility may increasingly depend not on appearing first in search results but on being recommended within AI-generated answers.

THE RISE OF AI VISIBILITY

Search engine optimisation (SEO) has long centred on improving rankings through keywords, backlinks and domain authority. AI discoverability, Mohan argues, follows a very different logic.

“Traditional SEO was about ranking, winning a position on a page of 10 blue links. AI visibility, or Generative Engine Optimisation (GEO), is about being the answer rather than a link to the answer,” he says.

Unlike traditional search engines, large language models evaluate whether product information is sufficiently trustworthy, structured and complete before referencing it. If they cannot confidently interpret a manufacturer’s data, the brand may simply disappear from the recommendation altogether.

This places far greater importance on machine-readable product information than on conventional search optimisation. At the same time, AI systems are looking beyond a company’s own website to understand whether a brand is trustworthy. This makes it important for brands to have a presence across credible, independent sources, where editorial PR and genuine reviews can play a key role, rather than advertisements or advertorials. AI systems bring together these trust signals from multiple sources and present them to users in one place. This means the decision-making journey is increasingly shifting to the AI chat, where consumers can get a more comprehensive view before making a choice. Brands that build credibility across trusted sources will therefore be better placed to influence how AI systems recommend them.

Structured specifications, consistent product descriptions, schema markup and clearly organised technical information become essential because AI systems rely on these elements when generating responses.

FlowBlinq has developed what it describes as 17 Generative Engine Optimisation pillars to assess whether brands are sufficiently prepared for AI discovery. These include structured data quality, technical completeness and AI crawlability.

Perhaps more significantly, Mohan believes many companies have little understanding of how frequently AI platforms mention their products – or whether they are mentioned at all.

“Our citation tool runs a brand across ChatGPT, Claude and Gemini and shows, prompt by prompt, whether the brand gets cited, where it loses out to a competitor and where it’s simply absent from the answer altogether,” he adds.

TECHNICAL ACCURACY BECOMES A COMPETITIVE ASSET

Tyres differ from many consumer products because purchasing decisions depend heavily on technical specifications. Load index, speed rating, rolling resistance, wet grip, tread pattern and vehicle compatibility all influence suitability. Inaccurate recommendations can have genuine safety implications.

Mohan believes this makes structured product information particularly important for the tyre industry. “When product data is thin, a model doesn’t refuse to answer; it defaults to the brand it has the most confident, well-structured information about,” he adds. He warns that this tendency naturally favours manufacturers with richer digital product catalogues rather than necessarily those with superior products.

FlowBlinq’s research suggests considerable room for improvement. According to the company’s findings, 62 percent of Indian brand websites provide product descriptions that are insufficiently detailed for AI systems, while more than half lack product codes needed for accurate identification.

For tyre manufacturers, the solution is relatively straightforward but frequently overlooked.

Rather than embedding specifications within downloadable PDF brochures or image-based catalogues, companies should publish technical information directly on webpages in formats that AI systems can easily interpret.

Equally important is the broader digital reputation surrounding a brand. Mohan notes that AI systems increasingly rely on trusted third-party sources – including established news publications, Wikipedia and community platforms – to validate manufacturer claims before making recommendations.

AI ENTERS FLEET PROCUREMENT

The implications extend well beyond retail consumers. Business purchasing decisions often involve lengthy comparisons of performance, lifecycle costs, regulatory compliance and operational efficiency – precisely the type of structured analysis that generative AI performs well.

According to Mohan, procurement teams, fleet operators and original equipment manufacturers (OEMs) may adopt AI-supported purchasing even faster than retail buyers. “B2B tyre buying was never going to be immune to this, and it may move faster than consumer purchasing because procurement teams are exactly the audience generative AI tools were built to serve,” he says.

A fleet manager could ask AI to compare total cost of ownership across several tyre brands. An OEM purchasing team might request suppliers meeting specified rolling resistance or durability thresholds.

In such scenarios, manufacturers lacking accessible technical documentation risk exclusion before human procurement teams even begin formal evaluation. “The practical response isn’t a new sales deck. It’s making sure spec sheets, compliance documentation and comparative data exist in formats a model can read and trust,” Mohan says.

AI WILL ADVISE, BUT HUMANS WILL STILL DECIDE

While AI is poised to transform product discovery, Mohan believes the actual purchase decision will remain firmly in human hands – at least for high-value, safety-critical products such as tyres.

“I’d separate ‘AI helping me decide’ from ‘AI deciding for me’, because consumers still are the final decision makers,” he says.

Recent consumer research supports this view. While surveys indicate growing confidence in AI agents handling routine shopping tasks, willingness declines sharply when AI is expected to complete purchases autonomously. Most consumers remain comfortable with AI conducting research, comparing alternatives and shortlisting products but prefer to approve the final transaction themselves.

Tyres, Mohan argues, naturally fall into the category where human oversight will continue to matter.

“It’s a purchase people make infrequently, it carries real safety implications, and it typically involves a meaningful amount of money,” he says.

Consequently, AI is likely to dominate the research phase – evaluating specifications, warranty terms, prices and dealer options – while the final purchase decision remains with the customer.

However, one area where agentic commerce could quickly gain traction is in connecting customers directly with dealers. Rather than merely recommending a tyre, future AI assistants may also identify nearby retailers with available stock and book installation appointments automatically.

BECOMING AI-READY STARTS WITH THE BASICS

One of the most striking aspects of Mohan’s assessment is that the industry’s biggest challenge is not technological sophistication but digital housekeeping.

“It’s data, overwhelmingly, and it’s more basic than most companies expect,” he says.

FlowBlinq’s audits suggest that many corporate websites still lack the fundamental structure AI systems require. According to the company’s research, 91 percent of audited websites failed to provide clear information explaining their product catalogues in a way that AI could

understand. Even more concerning, nearly half were unintentionally preventing ChatGPT’s web crawler from accessing their websites because of security settings or plugin configurations.

“These aren’t strategic gaps; they’re operational oversights, and they’re fixable in weeks, not years,” Mohan claims.

For tyre manufacturers, this means that substantial improvements may not necessarily require major investments in new technology. Instead, they require a systematic review of how product information is organised, published and made accessible to AI systems.

Mohan also believes the next phase of digital readiness will involve preparing websites for agentic commerce by enabling real-time inventory visibility and ensuring AI systems can interact directly with product databases.

MEASURING RETURN BEYOND TRADITIONAL SEO

Digital marketing budgets have historically focused on search advertising, social media campaigns and marketplace optimisation. As AI-driven referrals grow, Mohan argues that businesses should begin allocating dedicated budgets towards AI discoverability.

“Yes, and the case for it is measurable rather than speculative now,” he says. Rather than relying solely on website traffic or keyword rankings, he believes organisations should monitor a different set of performance indicators.

Among the most important are how frequently AI systems cite a brand when responding to relevant queries, whether those citations are accurate and whether visitors arriving through AI recommendations convert differently from those originating through conventional digital channels.

Adobe’s Digital Insights research suggests AI-generated referrals are not only increasing rapidly but also producing stronger conversion rates than traditional referral sources. According to Mohan, this reflects the higher purchase intent of consumers who have already completed much of their evaluation through AI before visiting a manufacturer’s website.

TRUST WILL DETERMINE INFLUENCE

The emergence of AI recommendations inevitably raises questions about transparency. If AI systems become influential in shaping purchasing decisions, how can brands improve visibility without manipulating results?

For Mohan, the answer lies in accuracy rather than optimisation. “The honest answer is that AI-powered recommendations only work for a brand in the long run if they’re accurate, because these systems increasingly get checked,” he explains.

He believes manufacturers should resist the temptation to game AI systems through exaggerated marketing claims.

Instead, success will depend upon providing complete, verifiable product information that allows AI to make fair comparisons based on genuine performance characteristics.

“So the lever isn’t gaming a model into over-recommending you. It’s making sure that when a model compares your tyre honestly against a competitor on wet grip, rolling resistance or price, your data is complete enough that you win the comparisons you’re actually built to win,” he says.

In his view, transparency is not a constraint on AI marketing but its most durable competitive advantage.

FROM RECOMMENDATIONS TO TRANSACTIONS

The next evolution extends beyond recommendations. Emerging protocols are enabling AI systems to communicate directly with commerce platforms, inventory databases and pricing systems, allowing them to perform increasingly sophisticated purchasing tasks.

According to Mohan, this represents a significant opportunity for tyre manufacturers and dealers.

“The interesting shift is that AI agents are starting to interact with commerce systems directly... rather than just reading a webpage and stopping there,” Mohan says.

Once connected to live inventory systems, AI assistants could recommend the exact tyre that fits a customer’s vehicle, confirm stock availability at nearby dealers and compare prices in real time. Now, it can also make purchases directly from the chat window. This is something FlowBlinq is uniquely positioned to address as well.

Rather than generic recommendations based on previous purchasing patterns, personalisation could become highly contextual – considering vehicle compatibility, driving conditions, current inventory and even maintenance priorities.

However, Mohan cautions that these benefits will only be realised by organisations whose internal systems can support such interactions. Manufacturers and retailers will need modern, connected back-end infrastructure capable of sharing real-time inventory and pricing information with AI platforms.

ENGINEERING PRODUCTS – AND ENGINEERING DISCOVERABILITY

Looking ahead, Mohan does not believe AI will replace product quality as the defining competitive factor. Instead, he sees AI readiness becoming an equally important complement to engineering excellence.

“Product quality will always be table stakes; nobody wins on AI visibility with a mediocre tyre,” Mohan says. Yet he argues that superior products alone may no longer guarantee commercial success.

As purchasing journeys increasingly begin with AI conversations rather than search engines, brands that fail to present their technical information in formats AI systems can retrieve and trust may simply disappear from consideration.

“The winners will be the manufacturers who treated AI readiness as seriously as they treat product engineering,” Mohan says. He returns to Gartner’s prediction of declining traditional search volumes not as a warning but as an indication of how rapidly digital discovery is evolving.

“The discovery layer is moving to AI faster than most manufacturers’ data infrastructure is moving with it,” he says.

His concluding observation perhaps best captures the industry’s emerging challenge.

“A brand can make the best tyre in its category and still lose the sale simply because it was invisible in the one conversation the buyer had before deciding. That’s a genuinely new way to lose, and avoiding it is now a core marketing responsibility, not a technical footnote,” Mohan says.

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.