PRESS SHOP INSPECTION

Inline Surface Defect Detection
for Stamped Metal Parts

Detect surface defects on highly reflective stamped metal parts in real time. Robust against challenging lighting conditions and production variability, the system enables early defect detection, reduced scrap rates, and lower internal failure costs.

FEATURES

Key Capabilities of Press Shop
Vision AI Surface Inspection

Automated Surface Defect Inspection
for Every Stamped Panel.

Inspect stamped sheet metal parts directly on the production line with a Vision AI system designed for real-time defect detection, operator feedback, and production quality traceability.

Purple circular icon with a lightning bolt symbolizing high-speed inline defect detection in real-time production environments.

1. 100% Inline Inspection for All Stamped Panels

Inspect every stamped panel automatically as it moves through the press line, without interrupting production flow.

Purple circular search icon representing inspection and detection capabilities in the Robolaunch Vision AI system.

2. Multi-Angle Imaging & Controlled Lighting

High-resolution industrial cameras capture panel surfaces, with the configuration designed around panel geometry and required inspection coverage.

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3. Real-Time AI Detection & Operator Alerts

Images are analyzed at the edge as each panel passes through inspection, providing immediate defect detection, classification and visual alerts for Quality Inspectors.

Purple circular icon with a gear and checkmark symbolizing easy, non-intrusive installation of the Robolaunch Vision AI system.

4. Production Traceability & Reporting

Inspection results are recorded for historical analysis, providing access to defect images, classifications, confidence values and production-level quality trends.

DEFECTS CLASSES

AI Detection for Critical Stamping Defects

Press shop operations face recurring issues such as cracks, wrinkles, thinning, die marks, and surface distortions that often escape manual detection. Robolaunch Vision AI accurately detects key stamping defects at line speed, helping manufacturers prevent scrap, rework, and downstream quality failures.

SYNTHETIC DATA APPROACH

Expand to New Defect Types Faster

Real production defects are often too rare and inconsistent to provide enough training data for every panel and defect type. Robolaunch combines real production references with synthetic defect generation to create realistic defect variations across location, size, orientation and surface conditions.

This enables to develop and adapt detection models for new defect classes and part variants without long and costly field data collection.

Gray irregularly shaped, flat plastic panel with curved and angular edges on a black background.

1.  3D Panel Model

CAD model of the part
to place defects
specific for panel type.

Six black and white images arranged in two rows and three columns showing an object with a trail, possibly a missile or rocket, moving through the sky captured from different angles or moments.

2. Synthetic Defect Gen.

2D and 3D modelling
of defect(s) with
limitless variations.

Metal surface with three highlighted defects: a wrinkle at the top left, a scratch at the top right, and a dent near the bottom left, each labeled with purple boxes.

3. AI Model Training

Detection for
target and new
defect classes.

PAIN POINTS

From Sample-Based Checks to 100% Inline Inspection

Industrial factory interior with a worker wearing a blue helmet and yellow vest inspecting a metal sheet on a table next to a conveyor belt system under overhead lights. Blue storage bins and racks holding metal parts are visible around the area.

Press lines operate at high production speeds, making continuous manual inspection impractical. Quality checks are often performed on selected samples, leaving gaps between inspections where forming or tooling defects can continue across multiple panels before being identified.

Automated visual inspection system scanning leather hides on two parallel conveyor belts, detecting defects labeled as 'trim-crack' and 'scratch' with confidence scores.

Vision AI inspects every produced panel inline at production speed, detecting surface and forming defects as parts leave the press. Continuous inspection enables earlier defect discovery, consistent quality control, and digital defect records for production traceability and analysis.

HOW?

Tailored AI Models for
Your Stamping Defect Detection

We adapt our AI system to your exact stamping line — from defect references to lighting conditions — ensuring accurate detection from day one.

Robolaunch Vision AI Surface Inspection system integrated into a press shop, positioned after a large metal stamping press to inspect freshly stamped panels on the conveyor in real time, with multi-camera coverage and an operator display for immediate defect visualization.

STEP 1 | Capture Your Production Context

We collect your critical defect samples, material details, and lighting conditions to recreate your stamping environment with high accuracy.

STEP 2 | Simulate & Train with Synthetic Data

We generate a photorealistic digital twin of your parts and produce thousands of realistic defect variations to fine-tune the AI model.

STEP 3 | Deploy, Calibrate & Optimize On-Site

We install the camera–lighting setup on your press line, deploy the optimized model on the edge PC, and calibrate it for stable line-speed detection.

Ready to deploy something like this in your line?

REQUEST NOW
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