Automated Tire Inspection and Classification

The TireTech inspection system guides each tire via conveyor belt into the center of the machine, where it is positioned horizontally for scanning. Three modular C6 2040 compact laser profilers from AT Sensors then scan the rotating tire using laser triangulation, capturing a complete 3D point cloud within just ten seconds.

This point cloud delivers precise data on all relevant tire characteristics: profile depth, contour, height, shape, and volume. Based on this data, the system classifies each tire by manufacturer, size (width, aspect ratio, diameter), season (summer or winter), DOT number, special markings such as ContiSeal and ContiSilent, and original equipment identifiers including AO, MO, TO, NO, AR, and MOE. The result is a fully automated sorting decision – retreading, recycling, or granulate processing. Without any manual intervention.

The choice of AT Sensors for this application was not coincidental. TireTech’s developer and Sales Manager Marcel Staudinger explains the decision: “We were recommended AT’s sensors and were immediately impressed by the modular principle of the product range. We were able to configure the sensors exactly to our requirements – like a modular system – choosing both the triangulation angle and the required laser power ourselves. The large field of view and accuracy of the 2040 3D laser profile sensors were also convincing.”

This modularity is a key differentiator. As AT’s Senior Sales Manager Armin Jehle points out: “With the modular 3D compact sensors, AT overcomes for the first time the problem that triangulation sensors have always been associated with high NRE costs and long development times due to resolution, speed, and flexibility requirements. Based on the MCS concept, AT can deliver the optimally tailored sensor for every application as an individual solution with the reliability of a series product – without additional costs for customer-specific developments, without minimum order quantities, and without long delivery times.”

The 3D data captured by the AT laser profilers is evaluated by aku.automation’s image processing software, the aku.visionManager®. The software uses AI-supported deep learning algorithms trained on thousands of tire images, enabling reliable classification even across the wide variance of tire types, manufacturers, and markings found in the field.

Integration between hardware and software is straightforward: thanks to the GenICam-standard interfaces of the AT 3D laser profile sensors, the aku.visionManager® can be connected to the hardware with minimal programming effort.

“When we built the first prototype of this system together in 2019, working with AT’s products was the only option for us. We have been cooperating for years and know both the reliability and the longevity of the sensors”, explains Christian Merten, Key Account Manager at aku.automation.

The software also includes extensive statistics modules, allowing customers to monitor the efficiency of their tire inspection via daily and monthly reports providing a reliable basis for continuous process optimization.

One of the most demanding aspects of the development was handling the sheer variance of tires on the market. Many manufacturers place information such as the DOT number at different positions on the tire sidewall, requiring the inspection system to be highly flexible in its reading approach. Building a comprehensive database covering all relevant tire classifications was another time-intensive prerequisite before the system could reliably identify and sort tires at the required level of detail.

Some classification decisions also carry direct safety implications. TireTech’s system can detect, for example, whether a tire contains a specific adhesive compound in its rubber. If it does, the tire must not be processed into granulate – as the adhesive can interfere with the shredding blades and create a fire hazard. Identifying this characteristic automatically and reliably is a capability that manual inspection simply cannot guarantee at scale.

To date, TireTech has delivered various systems in Germany and the Netherlands. Each system enables customers to process used tires sustainably, eliminate disposal costs, and contribute to a measurable reduction in environmental impact through intelligent rubber material reuse.

The next development stage is already in planning: a compact, AI-supported mobile inspection station aimed at smaller businesses such as garages and tire dealers, designed to bring the same classification capability to a wider market. With AT Sensors’ modular sensor concept as its technological backbone, the system is built to scale and to evolve alongside the demands of the market.