Automated Surface Inspection

Cut from a different cloth

Thursday 9th March, 2017

Here are some snippets from our feature ‘Cut from a different cloth’ in the latest edition of Imaging & machine vision, Europe’s only dedicated magazine for design and production engineers working in the scientific imaging and machine vision market.

“A textile factory with 200 looms will have around 20 dying machines, three heat setting machines, and then one or two automatic high-speed fabric inspection systems. The same factory operating manual inspection would have around 15 manual inspection stations, manned at least 16 or 17 hours a day. The effective throughput speed for manual inspection varies between 5 to 12 metres per minute, according to Shelton, whereas a vision system operating at the end of a final process like heat setting might run at 50 to 60 metres per minute.”

cut from a different cloth

“Shelton Vision might use five or six different illumination setups for inspecting apparel textiles: top light or diffuse lighting; transmitted light; light that is shining at a low angle across the fabric and light at a low angle shining down the length of the fabric; and reflective illumination.”

“Shelton Vision’s software also includes an automatic training functionality to deal with new styles of fabric, as well as being able to classify and grade defects to distinguish between a subtle defect and a normal variation in the fabric. It also has a way of validating the system by running a video of the defect map, as if the system were inspecting the fabric again in order to tune the algorithm sensitivity.”

“One of the big returns on investment for a vision system, according to Shelton, is in optimising the process of portioning the fabric into smaller rolls, or pieces, that are then packaged and sold. Shelton Vision’s inspection system will generate an electronic defect map, an interactive map for the full width and length of the web with positions and types of defects marked.”

“The easiest two calculations are labour saved and the yield improvement through optimisation.”

Read the full article here

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