Gelcoat Defect Detection AI

Add a real-time inspection layer to every hull and panel with vision AI for gelcoat defect detection. Built for the shops where finding defects still means a person, a raking light, and a slow walk around a part the size of a room, where the dark metallic hull hides everything until it is outside, and where the same defect costs minutes at demold and hours after the boat is rigged. Whether you're pulling boat hulls and decks, RV sidewalls and caps, or powersports bodywork, Roboflow inspects every part, and hands the finishing team a mapped defect list rather than a hunt.

Gelcoat Surface Defects:

• Detect porosity and pinhole fields, blisters, craters and fisheyes, and the air voids that show up as the part comes out of the mold
• Flag sags, runs, curtains, dry spray, and orange peel from the spray pass, and separate them from mold-transferred defects that need a different fix
• Catch color variation, mottling, and streaking on metallics and deep colors where the eye adapts and stops seeing the drift

Print-Through, Cure, and Post-Demold:

• Detect print-through and fiber pattern telegraphing through the gelcoat, including the cases that develop days after demold rather than at the mold
• Reinspect the same part at demold, after post-cure, and before rigging, and compare the states so a developing defect is caught while it is still cheap
• Flag alligatoring, wrinkling, and crazing that point at an undercured film rather than a spray problem

Defect Maps, Rework Routing, and Records:

• Position every defect on the part, so the finishing team gets a map of where to work instead of walking the hull with a light
• Trend defects by mold, sprayer, gun, color, and shift, so a systemic problem gets fixed at the source rather than buffed out one hull at a time
• Keep a per-hull image record through demold, finishing, and final, so a dealer claim or a warranty question has evidence behind it

Bring intelligence to every hull today. Stop porosity from becoming a showroom impression, print-through from becoming a rigging-line surprise, or a run from becoming eight hours of somebody's afternoon.

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More About Gelcoat Defect Detection

What is gelcoat defect detection with Vision AI?

Gelcoat defect detection with vision AI uses computer vision models to inspect molded composite parts for the surface conditions that drive finishing labor and warranty claims: porosity and pinholes, blisters and voids, craters and fisheyes, sags and runs, orange peel and dry spray, color variation, and print-through of the reinforcement pattern. Models trained on your own parts learn your gelcoat colors and finishes rather than a generic reference, and every finding is positioned on the part so the output is a defect map the finishing team can work from. Applied at demold, after post-cure, and before rigging, it also shows how a part changes between those points, which is where print-through and cure-related defects actually reveal themselves.

What standards does gelcoat inspection support?

Cosmetic acceptance on a hull is not set by a regulator. It is set by your own finishing standard, by what your dealer network will accept, and by what a buyer notices on a showroom floor. Where formal programs do apply, inspection records support NMMA certification, ISO 12215 build documentation, and ISO 9001 quality management, and they give a defensible evidence trail for dealer prep and warranty disputes. Finishing labor is one of the largest controllable costs in a boat or RV plant, and defects found at demold cost a fraction of what the same defects cost after rigging.

Can it integrate with our MES and rework routing?

Yes. Defect maps, classifications, and severity push into MES and quality systems through REST, MQTT, and direct database writes, keyed to the hull identification number or part serial so a finding follows the part down the line. Results can route a part to a specific finishing bay with its defect map already attached, so the buffer starts on the right areas instead of surveying the whole hull. Trends tie back to the mold, gun, sprayer, color, and shift for process work, and imagery can write to a historian or quality database for dealer claims and warranty investigation. Inference can run on-prem, which matters in plants where the network stops at the office.

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