Development and application of a machine vision system for measurement of tool wear

Abstract

Tool wear measurement is of great concern in machining industry, as it affects the surface qualities, dimensional accuracy and production costs of the machined components. The orthodox methods of measuring tool wear are time consuming and limited in accuracy and application. In this study, machine vision system based on digital image processing was developed for measurement of tool wear. The basic components of the system are: a charge coupled device (CCD) camera, PC, Microsoft Windows Video Maker, frame grabber, Video to USB cable, digital image processing software (Photoshop and digital image processing toolbox for MATLAB), multi-directional insert fixture, and light source. Tool wear images were captured and ten different wear features: length, width, area, equivalent diameter, centroid, major axis length, minor axis length, solidity, eccentricity and orientation were extracted from the images. The pixels dimension of the system was found to be Px = 0.03306 and Py = 0.03333. The accuracy of the system compared to SANDVIK Coromant hand-held microscopic lens was found to have an absolute error less than 3.13%. The system has been applied in the analysis of tool wear of uncoated cemented carbide inserts used for turning of NST 37.2 steel. A tool wear index (TWI) was proposed as a potential indicator for tool wear monitoring. A graphical user interface (GUI) was designed for easy application of system