AI Inspection of Stamped Metal Parts

Classification and positioning of metal surface defects

Stamping process of electronic and mechanical products

Stamping is a metal processing method that relies on pressure tools and molds to deform or separate metal pieces to required shape and size. During stamping, the surface of the metal cannot be damaged so that it remains suitable for spray painting, electroplating and other processes. However, the production environment and random factors can create minor imperfections on stamped parts such as corner burrs, dirt, water stains, indentation, and scratches that need to be detected immediately to facilitate subsequent processes.

Quality control and obscure defects

There are many types of defects that may appear differently each time on the stamped parts, in particular oil or water stains, which are not easily detected. Brightness levels during image acquisition can also vary, which makes implementing traditional inspection systems challenging.

AI enabled defect detection with SolVision

Using SolVision’s Segmentation tool, an AI model can be trained using images of different defects in varying brightness to develop an inspection system that can easily detect defects on stamped metal parts, and improve the surface quality before further processing.

AI Inspection

Defect classification

Blue Oil stains, water stains

Green White defects

Orange Scratches 

Yellow Burrs and dents

Original

Metal processing defect detection case

Result

Metal processing defect detection case

Result

Metal processing defect detection case

Result

Metal processing defect detection case
Related Posts
  • AI Visual Inspection of Socks

    After being trained with a small set of sample images, Solomon SolVision can identify defective products in real-time.
  • Inspecting Packaged Semiconductor Chips

    The Anomaly Detection tool uses deep learning technology to teach the AI model sample images of “perfect” wafers.
  • Defect Inspection of Metal Casings Using AI

    SolVision elevates quality control in electronics with AI capable of defect detection and classification of metal casings that have reflective surfaces.
  • Deep Learning Inspection of Liquid Biotech Medicines

    SolVision’s deep learning facilitates the recognition of varying colored liquids and sedimentation levels for accurate classification and quality control