An automated flank wear measurement of microdrills using machine vision

The objective of this study is to develop an automated flank wear measurement scheme using vision system for a microdrill. The images of worn-out microdrills were captured after the hole-drilling tests on a 10-layered printed circuit board (PCB). The models were evaluated and validated based on the acquired image with a computer-based acquisition system. Edge detection was employed to extract the boundary with a pair of edge points, including both raising and falling edges, to compute the height of the cutting plane. The flank wear area, average flank wear height, and maximum wear height are computed by using this approach to evaluate the tool life. Experimental results show that the proposed scheme is reliable and effective for the automated frank wear measurement of microdrill in PCB production.