Gypsum Board Inspection AI

Add a real-time inspection layer to every board with vision AI for gypsum board inspection. Built for the operations where a line produces a board every few seconds, the product is white paper on white paper under bright light, a wrinkle and a shadow look the same from the catwalk, and a board that skews on the transfer takes the line down with it.

Paper and Surface:

• Detect blisters, wrinkles, tears, and paper delamination on face and back paper coming off the setting belt and out of the kiln, so the board that will not finish is culled at the line
• Detect scorch and calcined paper at the kiln exit, wet spots, stains, and slurry bleed-through, so a kiln zone or a mixer problem surfaces as a flagged board instead of a shift of them
• Detect print, stamp, and label defects on the back paper, so the board carries the right mark and the right grade

Edge, Core, and Dimensions:

• Detect edge crush, tapered-edge damage, corner breaks, and paper edge tears at the knife, the transfer, and the stacker, so the damaged board is pulled before it is bundled against a good one
• Detect core voids, cracks, soft spots, and exposed core at cut ends and edges, so a forming or setting problem is caught at the board and traced to the mixer
• Verify length, width, squareness, and end cut quality on every board, so the sheet that will not fit the wall never leaves the plant

Line Alignment, Traceability, and Systems Integration:

• Detect boards running skewed, misaligned, or overlapped on transfers, the setting belt, and the kiln infeed, so the line slows or stops before the jam instead of after it
• Trend defects by kiln zone, knife, mixer batch, and stacker, so the drift surfaces before it becomes an off-grade run
• Integrate with line controls, MES, and quality systems, with per-board records tied to lot, line, timestamp, and imagery for claims and audits

Bring intelligence to every board today. Stop paper blisters, crushed edges, and skewed boards from becoming job-site rejections, lost accounts, or the twenty-minute jam.

More About Gypsum Board Inspection

What is gypsum board inspection with Vision AI?

Gypsum board inspection with vision AI uses computer vision models to inspect wallboard at every stage of the line, from the forming table to the bundle: paper blisters, wrinkles, tears, and delamination, scorch, wet spots, and stains, edge crush, tapered-edge and corner damage, core voids, cracks, and soft spots, length, squareness, and cut quality, board skew and misalignment on transfers and the kiln infeed, and print and bundle defects at the stacker. Models trained on your actual boards, lines, and lighting run at line speed on every sheet, with per-board records that support ASTM C1396, ASTM C473 and C1264, GA-216, and ISO 9001.

Can Vision AI see a paper wrinkle on a white board moving at line speed?

White paper on a white board under bright plant light is exactly where wallboard inspection is hardest: a wrinkle, a blister, and a shadow from a guard or a lamp read almost the same from the catwalk, the board is past the camera in a second or two, and the defect that will open up under primer is a low ridge a few millimeters high. Deep-learning models trained on your actual boards, paper, and lighting learn what a wrinkle, a blister, a tear, and a scorch mark look like on your product, and low-angle raking light and line-scan or high-speed imaging give the model the shadow and texture that carry the signal on a flat white surface. Detections come back with the board, the position on the sheet, and the frame, so the operator sees the blister instead of hunting for it, and the record ties the flagged board to the kiln zone, knife, or mixer batch behind it.

Does this replace our thickness gauge and inline scale?

No. The thickness gauge, the inline scale, and the moisture and core sampling program keep their role measuring what ASTM C1396 and C473 require, and the test lab keeps its schedule and its methods. Vision AI adds what a gauge and a scale do not see: the paper and its defects, edge and corner damage, exposed core and cracks at the cut, scorch and stains, board skew and misalignment on the line, and print and bundle faults, plus a picture of every flagged board. Gauge readings, scale weights, and vision detections land in the same per-board record, and the board that would have passed weight and thickness and failed the finisher is culled at the line.

Can it integrate with our line controls, MES, and quality systems?

Yes. Roboflow Inference exposes a standard API and supports common industrial protocols, so inspection results flow into your existing systems: line PLCs, transfers, and stackers, MES and ERP platforms like SAP and Oracle, quality and SPC systems, and SCADA and HMI platforms like Ignition and AVEVA, through REST, MQTT, OPC UA, and direct database writes. PLC-level integration slows or stops a transfer on a skewed board and culls a defective board at the stacker the moment a check fails, and every event carries the line, board, position, lot, defect class, imagery, and disposition, with a full record behind every board for claims, audits, and process improvement.

‍