Zebra Aurora Vision Studio offers a rich library of Deep Learning tools to check trim quality in real time. Deep Learning anomaly detection tools highlight subtle issues that conventional tools miss on patterned or textured surfaces, such as scuffs, flash, warping, scratches, or tears on interior surfaces. Zebra Aurora Vision Studio Anomaly Detection trains quickly using only good examples—no exhaustive defect library required—making it ideal for variable molded trims and fabric components. The result is lower false rejects, less rule tuning, and faster changeover, with clear overlays that guide operators directly to problem areas.
With Aurora Design Assistant, teams can standardize inspection across stations and plants. Aurora Design Assistant can incorporate both 2D and 3D inspection inputs to give universal pass/fail judgments on clip presence/absence and other automotive trim inspection processes. Aurora Design Assistant’s flowchart-based environment streamlines deployment, I/O mapping, recipe and variant management, and HMI creation. Run on Zebra smart cameras or industrial PCs, connect to PLCs and MES, publish pass/fail and measurements, and present guided operator prompts and overlays for faster resolution.
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