An end mill is a cutting tool used for metal processing, such as cutting and drilling metal products. It comes in various shapes and sizes depending on the application. Chipping or wear of the cutting edge not only affects the machining accuracy, but also the safety of the operator due to injuries caused by broken cutting tools.
Until the introduction of this solution, all inspections of the cutting tools were done manually by humans, and even the ID and data management of the tools were all done manually.
After the inspection, the tools are divided into usable tools and unusable tools, and the unusable tools are asked to be re-sharpened by the tool manufacturer, which is called re-grinding.
The inspection of cutting tools was done visually, with the operator focusing the camera by hand. Scratches and chips on the cutting edge would appear differently depending on how the lighting was applied and the tilt of the cutting tool, and the judgment results were not stable. In addition, it was difficult to focus on the cutting edge of a blade tool with a diameter as small as 1mm when inspecting it visually.
This solution performs transport, inspection, and sorting automatically.
In order to reduce the burden on workers, robots were introduced to carry and sort the tools to the inspection equipment. In order to transport a variety of tools, hands and stock boxes were made according to the specifications.
The ID is automatically read before inspection to recall data on the condition of the cutting tool, and different cameras are used to take pictures according to the diameter of the cutting edge. Then, using a unique algorithm, the camera automatically focuses, takes a picture, and displays an enlarged image of the blade surface. The results are displayed, saved in a database, and then sorted to see if they can be used.
Our equipment achieved high inspection accuracy, and reduced the labor cost of inspecting cutting tools by 700,000 yen/month. In addition, since it determined whether the front or side of the tool is scratched or worn, it succeeded in visualizing the characteristics of the scratches. Furthermore, since the images are automatically created, they can be easily rechecked by the human eye. Therefore, it is even easy for amateurs to clearly see scratches and wear, which contributes to reducing the workload of the operator.