Rubber presents a challenge for optical-based measurement sensors. By nature, the black surface is difficult to capture reliable data from and accurately measure. This challenge is often intensified by the complex shapes into which rubber derivatives are extruded or molded.

As a solution to this challenge, 3D laser sensor manufacturers have optimised the design of their sensors to successfully implement scanning and quality control functions for both in-process and final product inspection applications in rubber and tyre manufacturing.

3D laser scanning

Rubber material comes in two forms on the production line, either as fresh and uncured from an extruder or a calender, or as a finished product (e.g., vulcanised tyres). Non-contact 3D laser scanning offers the most practical solution for inspection of both of these rubber material types.

Here’s why:

1. The soft, gummy nature of the rubber makes contact-type measurement ineffective. This measurement approach is also too slow to keep up with the high-speeds of continuous web material production.

2. 2D sensors require complex lighting to see black-on-black contrast. In some applications the lighting is placed underneath the material (e.g., when measuring the width of a strip), and hot sticking rubber can contaminate the lights. In addition, 2D can’t produce measurements related to object geometry (i.e., 3D shape), which means they are unable to measure critical features such as object flatness, surface angles, or part volumes, and are limited to contrast-based inspection. This makes 2D sensors a poor solution for scanning complex shape-based features on dark surfaces, or for operation in low lighting conditions.

          3. In comparison, 3D laser sensors are contrast invariants and generate high-resolution scans regardless of the material or lighting conditions. They also capture the complete 3D geometry of the scan target, including critical depth measurements on surface features such as grooves in a tyre tread. 3D laser sensors are also able to achieve the high speeds required for continuous web material scanning.

Laser profile sensors provide an ideal solution to both in-process and final rubber and tyre measurement and quality control applications. Built-in measurement tools for strip positions, including multiple groove location and depth measurement monitoring with automated alignment enable engineers to configure setup parameters––without requiring any measurement software development.

In addition, the ability to store multiple geometry configurations in the sensor makes changes between different recipes quick and simple, which is critical in minimising downtime for operations that make model changes multiple times per shift.

Application examples

1. In-Process Inspection

Extrusion Profiling with High-Resolution Gocator® 2440 Laser Profiler

Extruding rubber in a specific shape makes up the tread portion of a tyre. Measurement of the extrusion profile is carried out in-process, correcting the extrusion parameters in real-time to maintain the required shape. Key measurement parameters include thickness, width, and profile. Another required sensor capability is monitoring the position of surface features, such as ridges, center lines, and edges.

Profiling these tread extrusions is done by using 3D laser sensors to scan across the extrusion, generating a profile to which built-in measurement tools and pass/fail decision-making logic can be applied.

In this example, two Gocator 2440 laser line profilers are used to measure the rubber web’s extrusion groove pattern, geometry, and location with an X resolution down to 13 microns. Gocator 2440 sensors are able to inspect multiple grooves in a single setup, and groove measurements are unaffected by changes in surface angle relative to the sensor.

Most importantly, Gocator 2440 sensors generate critical 3D height data for robust shape measurement. 2D solutions are limited to contrast-based inspection.

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3. Final tyre inspection

Tyre Sidewall Inspection with High-Speed Gocator 2530 Laser Profiler

Traditional methods for measuring tyre sidewalls for defects such as bulges and dents suffer from too many false rejects (i.e., classifying a good tyre as defective). Due to measurement system limitations, many manufacturers have no choice but to “oversensitise” their sidewall bulge and dent measurement systems, resulting in costly manual inspection requirements for all rejected tyres.

In fact, some measurement systems cannot even distinguish between bulges or dents. However, with state-of-the art laser measurement precision and advanced built-in software analysis, false positive rates can be substantially reduced and, in many cases, eliminated altogether.

Using a Gocator 2530 laser profiler the engineer is able to generate full surface point cloud geometry data in order to detect small defects (down to 28 microns X resolution) anywhere on the sidewall surface. The sensor also delivers complete scan, measurement, and control at 4 kHz, allowing engineers to meet stringent cycle time requirements––with no need for industrial PCs or external controllers.

In this configuration, two profile sensors are typically used, one for each sidewall (top and bottom buddy system). A third sensor is often used to monitor radial runout of the tread.

Leveraging 3D Laser Scanning and Inspection

Laser-based laser triangulation sensors meet the high speed and high resolution requirements for accurate rubber and tyre measurement. These sensors are used in a variety of in-process and final inspection applications, including extrusion profiling and tyre sidewall inspection.

Adding 3D laser sensors for automated quality control is vital to reducing scrap and rework, and improving final product quality by maintaining consistency throughout the tyre manufacturing process.

Courtesy of LMI Technologies www.lmi3d.com

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Vaculug has released VMS Pro Max, the next generation of its fleet management application. The product, developed over a three-year period, pairs a redesigned interface with AI-enhanced software intended to make commercial fleet management faster and more intelligent. The app is now available for download through the Apple App Store and Google Play Store.

The upgraded platform offers clear, real-time access to tyre and vehicle data, accelerates background report uploads to reduce driver time and allows measuring tools to be connected for automatic tread depth capture. It also incorporates an embedded VAN Driver Guide and can instantly flag vehicles left uninspected across 30, 60 or 90 days. Existing users must sync all pending inspections and confirm cloud upload before updating to prevent data loss.

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The Yokohama Rubber Co., Ltd. and dotData, Inc. have announced joint development an AI agent to help engineers form hypotheses, interpret findings and make decisions in manufacturing R&D. Before full deployment, the initiative will validate the agent's required capabilities and technical feasibility.

The solution combines technical documents such as design specifications and experimental reports with engineers' accumulated expertise and features extracted from measurement data via dotData's Signal Intelligence technology. It will provide insights tailored to each project's objectives, circumstances and constraints.

The agent is not meant to produce a single correct answer. Operating in a human-in-the-loop framework where engineers retain decision-making authority, it will present multiple possibilities, perspectives and risks to broaden thinking and support professional development.

Manufacturing R&D generates diverse data through experiments, simulations, production and evaluation. Developing hypotheses requires specialised knowledge and context. Since new technology R&D rarely has one predetermined answer, abductive reasoning plays a key role. AI can add value by using data and organisational knowledge to widen engineers' perspectives rather than replace judgment.

The agent will explore measurement and experimental data patterns beyond factors engineers previously identified, combining quantitative insights with design documents and expert knowledge to reveal difficult-to-spot relationships. It will offer input from materials, design, analysis, production and evaluation perspectives, challenge existing hypotheses and raise questions about alternative interpretations and conditions. Engineers will then test hypotheses and feed results back into further dialogue, guiding Signal Intelligence processes so non-specialists can explore data features as needed.

Yokohama Rubber has advanced HAICoLab since 2020, using dotData as a foundational technology in tyre design and rubber mixing. This joint development expands those efforts, with engineers interpreting and evaluating the agent's suggestions using their own expertise rather than accepting them unquestioningly. The companies aim to transform R&D processes while strengthening engineers' creativity and judgment, establishing a new model for human-AI collaboration in manufacturing R&D.

Motoji Fujita, Head of Research & Advanced Development Division, The Yokohama Rubber Co., Ltd., said, “Since 2020, we have conducted research and development under the HAICoLab framework, drawing on the complementary strengths of people and AI to create a collaborative environment. We believe AI agents will give engineers access to perspectives beyond their own experience and enable them to evaluate hypotheses from multiple angles. Through this development initiative, we aim to advance our R&D capabilities while supporting the continued growth of our engineers.”

Ryohei Fujimaki, CEO, dotData, Inc., said, “Success in manufacturing R&D depends heavily on an organisation’s ability to connect its proprietary data and knowledge with AI. The quantitative context generated from data through automated Signal Intelligence provides a foundation for AI agents to engage engineers in practical, data-driven discussions. Together with Yokohama Rubber, which has many years of experience in advanced data utilisation, we intend to establish standards for using AI in highly specialised business domains.”

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Bridgestone Aircraft Tire (Europe), a Bridgestone Corporation subsidiary, has announced the deployment of its ‘easytrack’ tyre management system at SR Technics Spain SAU, the tyre and wheel maintenance hub of global maintenance, repair & overhaul (MRO) provider SR Technics. The scalable digital platform is accessible on desktop and mobile devices.

Designed for airlines and MROs, ‘easytrack’ manages inbound and outbound tyre and wheel flows across single- or multi-site operations. It delivers real-time identification, tracking and documentation throughout each asset’s lifecycle. The project follows the solution’s first airline implementation in 2025, becoming its second customer rollout and first MRO application.

MRO providers handle large tyre and wheel volumes for multiple airlines, complicating operations. ‘easytrack’ simplifies asset management and improves traceability, accuracy, safety and productivity. At SR Technics Spain SAU, it digitalised paper-based processes, cutting processing time by 45 percent, reducing data-entry and identification errors and improving flow management across Palma de Mallorca and Madrid.

From left: David Sautois, ‘easytrack’ Product Manager, Bridgestone Aircraft Tire (Europe) S.A.; Antonio Colella, General Manager, SR Technics Spain SAU; Jean-Philippe Minet, Managing Director, Bridgestone Aircraft Tire (Europe) S.A.; Eugenie Baradzina, Commercial Director, SR Technics Spain SAU.

The results stem from a Bridgestone and SR Technics Spain SAU co-creation initiative built on long-standing partnership. ‘easytrack’ was adapted to support tyre and wheel combinations for the hub’s wheel and brake operations. Bridgestone’s expansion of airline and MRO solutions aligns with its E8 Commitment, emphasising efficiency and ecology.

Antonio Colella, General Manager, SR Technics Spain SAU, said, "The successful implementation of easytrack is a significant achievement for SR Technics Spain SAU and our teams in Mallorca and Madrid. From the very beginning, the collaboration with Bridgestone was built on trust, openness and a shared vision for innovation. Together, we have developed a solution that not only improves efficiency and traceability but also creates lasting value for our operations. We are proud to be the first MRO in the world to adopt this technology and look forward to continuing this journey with Bridgestone Corporation.”

Jean-Philippe Minet, Managing Director, Bridgestone Aircraft Tire Europe, said, “I’d like to thank SR Technics for their trust and another fruitful collaboration with Bridgestone. What the teams have jointly achieved is remarkable: co-creating through efficient teamwork and customising the Bridgestone easytrack application to digitise SR Technics tyre and wheel tracking operations. This is a brilliant example of how Bridgestone amplifies the value created at our partners.”

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Michelin Connected Fleet, a subsidiary of Michelin North America, has entered into a collaboration with Doran to integrate the latter’s tyre pressure monitoring hardware with its own Smart Predictive Tire solution. This combined offering is now accessible through the Platform Science Virtual Vehicle Marketplace, marking the first retail platform to host the integrated system.

The partnership merges Doran’s commercial tyre pressure and temperature monitors with Michelin’s predictive analytics software, creating a unified tyre management ecosystem. By fusing real-time sensor data with connected vehicle intelligence, the solution aims to enhance fleet visibility into tyre health, thereby enabling more informed maintenance scheduling and operational strategy. This development follows Michelin Connected Fleet’s recent launch of Smart Predictive Tire on the same marketplace, now broadening access to a fully bundled hardware-software package.

Utilising advanced data analytics, Smart Predictive Tire identifies emerging tyre issues through pressure and temperature readings, allowing fleets to pre-empt costly roadside failures and minimise unplanned downtime. Doran’s sensors supply the critical digital inputs that feed this predictive model, delivering comprehensive tyre oversight. The joint effort underscores both companies’ dedication to progressing connected fleet capabilities via synergistic hardware, software and data integration.

Willem Moore, President, Michelin Connected Fleet, said, "Doran provides the signal, and our Michelin Smart Leak algorithm helps translate tyre data into actionable insights that support informed maintenance decisions. By providing visibility into potential tyre conditions, fleets can evaluate issues sooner and take appropriate action based on their operational needs. Our focus is on delivering information that helps fleets manage their tyre assets more effectively and helps to support safe, efficient operations.”

Jim Samocki, President, Doran, said, “Fleets do not just need more data. They need accurate and reliable information that they can trust to reduce tyre-related repair and maintenance costs, improve uptime and keep vehicles operating safely. By combining Doran’s proven TPMS technology with Michelin’s Smart Predictive Tire solution, fleets can move beyond simply reacting to tyre issues and take a more proactive approach to tyre maintenance.”

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