Automate regulatory compliance, serialized tire traceability, and conveyor sorting at line speed. YAFE 360° Sidewall OCR unwraps curved tire surfaces to read embossed DOT, TIN, plant codes, and mold IDs in under 400ms — eliminating manual inspection bottlenecks with 99.8% read accuracy.
Reading embossed, black-on-black rubber characters on a rapidly spinning curved tire sidewall is one of the most demanding challenges in industrial computer vision. YAFE Quality Inspection AI solves this with synchronized multi-angle strobe illumination and proprietary polar unwrapping neural models.
Engineered for high-volume tire manufacturing plants to automate regulatory compliance and guarantee 100% serialized batch traceability before shipment.
Reads low-contrast, raised rubber characters across curved sidewalls under continuous rotation at line speeds up to 120 tires per minute with 99.8% read rate.
Automatic parsing and verification of Plant Code, Tire Size Code, Optional Manufacturer Code, and Week/Year Date Code (WWYY) compliant with US DOT FMVSS 139, ECE, and BIS.
Sub-15ms direct PLC communication via Profinet, EtherNet/IP, or Modbus TCP commands pneumatic flippers and diverters to isolate non-compliant tires instantly.
Every inspected tire generates a permanent digital record containing high-resolution sidewall imagery, timestamp, curing mold ID, and serial code synchronized into SAP MES.
Seamlessly integrates with automatic centering rollers and spin rigs up to 320 RPM, eliminating line pauses and manual tire reorientation.
Automatic optical zoom and focal distance compensation inspects passenger car, commercial truck, bus, and massive agricultural OTR tires without mechanical re-tooling.
Seamlessly retrofits into final finish lines, uniformity testing machines, and automated barcode sorting conveyor cells.
Mechanical conveyor rollers automatically center and spin the tire to optimal RPM for multi-camera synchronous capture.
High-intensity polarized dome lighting highlights embossed rubber edges while eliminating glare from mold release wax.
On-premises edge neural network unwraps the curved sidewall, segments characters, and validates alphanumeric TIN syntax in <400ms.
Deterministic fieldbus signals route compliant tires to automated warehouse stackers and divert non-compliant tires for inspection.
Robust hardware and software parameters designed for harsh curing and finishing plant conditions.
| Parameter | Industrial Specification |
|---|---|
| Tire Rim Sizes Supported | 13 inches to 54 inches rim diameter (Passenger, Commercial Truck, Bus, Agriculture & OTR) |
| Cycle Time / Throughput | Under 400ms per tire inspection (up to 120 tires / minute continuous line speed) |
| Supported Code Standards | US DOT (FMVSS 139), TIN, E-Mark, Plant Code, Size Code, Mold Number, Date Code (WWYY) |
| Optical Hardware | Industrial high-speed GigE Vision multi-camera array with polarized dome illumination |
| PLC & Fieldbus Protocols | Profinet, EtherNet/IP, Modbus TCP, Discrete 24V Optoisolated I/O (Siemens, Rockwell, Omron) |
| On-Premises Edge Compute | 100% on-premises NVIDIA RTX / Jetson AGX Orin industrial edge controller (Zero Cloud Dependency) |
| Read Accuracy | > 99.8% read rate across vulcanized black rubber with active mold flash tolerance |
Schedule a live factory demonstration or speak with our automotive machine vision engineers to plan an on-site line retrofit.