As Consumer Behavior Changes, Manufacturing Patterns Tend to Be More Versatile with Smaller Quantities
Production lines must be frequently updated to keep up with changes in the market. This also brings challenges to product inspection in the process. For inspection equipment and workers, both their skills and equipment have to be updated to quickly switch between lines and accurately inspect a wide range of products.
We will explore how artificial intelligence can be applied in the computer and peripheral equipment industry, and how it can help people make the right decisions, allowing more flexibility and intelligence in the manufacturing process, enabling the customized small-volume, large-variety production.
During the manufacturing process, various types of defects such as dents, scratches, cracks, deformation and dirt are inevitably generated. Using rules-based machine vision technology, it is difficult to identify all the defects and is very likely to have high under-kill and over-kill issues.
By simply collect the image data of defective and qualified products, as well as training deep learning models, the errors can be effectively reduced and reliable results can be obtained.