

Add a real-time inspection layer to every tire with vision AI for tire defect detection. Built for the plants where a blister hides in black-on-black sidewall texture until heat and speed find it, the final inspection line depends on how the tenth hour of a spinner's shift is going, and a curing press that started flashing at dawn gets discovered by the day shift's complaints. Whether you're building green tires, curing, or running final inspection, Roboflow inspects every tire's surfaces at line rate, with per-tire records tied to the DOT serial behind every shipment.
Sidewall and Lettering:
Tread, Bead, and Building:
Final Inspection, Presses, and Systems Integration:
Bring intelligence to every tire today. Stop tire defects from becoming highway failures, week-long press problems, or the recall that carries your name on every sidewall.
What is tire defect detection with Vision AI?
Tire defect detection with vision AI uses computer vision models to inspect tires through building, curing, and final inspection: sidewall blisters, bulges, and splice defects, tread underfill and foreign material, bead defects, mold flash, and lettering and DOT code verification. Models trained on your actual tires and molds inspect every unit at line rate, with per-tire records tied to DOT serial that support FMVSS 139 and IATF 16949 documentation.
Can Vision AI find black defects on black rubber?
The tire is the definitive black-on-black case: a blister that's a subtle change in curvature, a splice mark that's a texture shift, raised lettering and mold patterns everywhere, and every bit of it the same light-absorbing rubber. Deep-learning models trained on your actual tires, molds, and lighting learn each tire line's normal surface, curvature, and texture, flag what breaks it, hold that judgment across sizes and patterns, and route borderline tires to an inspector instead of guessing, which is the consistency the tenth hour of a shift can't offer.
How does this fit with our X-ray and uniformity machines?
X-ray keeps seeing what vision can't: cord placement, belt alignment, and internal structure. Uniformity and balance machines keep measuring force variation. Vision AI adds the visual surface layer between them: the blister X-ray doesn't flag, the mold flash no force measurement feels, the splice mark and the DOT read, all on every tire, all feeding the same per-tire record. Three instruments, one record per serial, which is what a warranty adjuster or an investigator actually asks for.
Can it integrate with our building machines, presses, PLCs, and MES?
Yes. Roboflow Inference exposes a standard API and supports common industrial protocols, so tire inspection events flow into your existing systems: building machine and press PLCs from Allen-Bradley and Siemens, MES and ERP platforms like SAP and Oracle, and SCADA and HMI platforms like Ignition and AVEVA, through REST, MQTT, OPC UA, and direct database writes. PLC-level integration routes a flagged tire the moment a check fails, and every event carries DOT serial, press, mold, imagery, and disposition, with a full audit trail behind every tire.