Client Profile:
A large-scale tire recycling company in Europe processing over 1.2 million used tires per year, with growing demand from resale and retread clients but facing limitations in manual sorting accuracy and speedChallenge

The client was struggling with:

• Lack of employees to recruit

• Manual sorting inefficiencies: Workers had to visually inspect and categorize each tire, one by one, leading to inconsistencies and errors.

• Limited knowledge retention: Operators could not memorize the thousands of possible brand/model/size combinations.

• Lack of traceability: The client had minimal data on tire inflow, outflow, and quality control metrics.

Solution

They chose to adopt the REGOM system, which enables the automatic identification and sorting of tires at a rate of 1,200 tires per hour, thanks to its AI powered identification machine combined with its expertise in engineering and installing customized sorting lines, including adapted conveying systems (splitters, buffers, etc.). The machine detect brand, model, dimensions, speed index, load index, DOT, and remaining tread depth.

The AI-powered identification and sorting machine, is capable of:

• Real-time tire recognition

• Automated classification into categories and batches such as reusable, retreadable, shred-ready, etc.

• Connected dashboard for tire flow tracking, performance analytics, and traceability.

Results

• Increased volume of tires processed: + 10% tires sorted per year

• Increased volume of reusable tires: Thanks to improved accuracy in tire identification.

• Reduction in sorting time per tire, from over 20 seconds manually to 12 seconds with REGOM.

• Improved resale margins, as high-value tires were no longer miscategorized.

• Data-driven operations: Real-time dashboards allowed the client to optimize processes and respond to market demands with agility.