Verifying Correct Gap and Flush


Vehicle quality depends on how panels meet. Manual feeler gauges are slow, subjective, and hard to scale across stations. The result is rework, noise, leaks, and warranty cost. Automated 2D vision checks gap width reliably, but proving panels sit flush—the same plane across the seam—requires precise 3D measurement. A contactless, in-line system profiles edges, applies real-time rules, and feeds accurate results to production systems. These systems confirm gap and flush at the line pace (takt time), reduce escapes, raise first‑pass yield and finish quality, and maintain a complete audit trail. 

Zebra 3S Series Scanner for Automotive Gap and Flush

In-line 3D gap-and-flush inspection that keeps pace with the line and delivers consistent, first‑pass quality

3s80 Gap Flush Inspection Animation Screencap

Automate gap and flush verification

Zebra 3S80 3D sensors capture complete seam geometry in a single, calibrated view, enabling precise measurement of gap width and flush height at full production rate. The sensors deliver high‑density profiles, onboard filtering, and straightforward alignment tools, which shorten setup time on doors, hoods, and lamps. Results stream in real time as pass/fail and numeric values for immediate corrective action.

Aurora Design Assistant software used for extracting profiles obtained after projecting multiple laser lines onto a surface.

Unify inspection logic and control

Zebra Aurora Design Assistant facilitates gap and flush verification by allowing users to create machine vision applications with metrology tools.  Take accurate, non-contact measurements of features like the distance and alignment between surfaces. Users can create and customise inspection workflows through an intuitive flowchart system, incorporating tools for image capture, edge detection, and detailed 3D data analysis. Aurora Design Assistant also translates measurements into real-world units, like millimetres, and compares them against set tolerances to deliver simple pass or fail results, perfect for fast-paced environments like assembly lines. 

A robotic arm in the manufacturing environment uses an Iris GTX to measure a vehicle's gap and flush. This image was generated with the assistance of AI tools and may not depict real people, places, or events.

Add 2D context and traceability

Iris GTX smart cameras add 2D context that complements 3D profiling. They locate edges, confirm clip and fastener presence, and read labels to position each 3D scan precisely. The same station can also surface related issues for faster diagnosis. Iris GTX cameras provide supplemental verification using machine vision and deep learning, such as confirming component presence, verifying colour and appearance, classifying parts on mixed production lines, and guiding robots. Additionally, the high-resolution imaging capabilities (up to 16 MP) enable detailed documentation for traceability and quality assurance, ensuring a robust and reliable inspection process.