Surface Characterisation-Based Tool Wear Monitoring in Peripheral Milling

In the last decade, the progress of surface metrology has led to improved 3D characterisation of surfaces, offering the possibility of monitoring manufacturing operations and providing highly detailed information regarding the machine tool condition. This paper presents a case study where areal surface characterisation is used to monitor tool wear in peripheral milling. Due to the fact that tool wear has a direct effect on the machined workpiece surface, the machined surface topography contains much information concerning the machining conditions, including the tool wear state. By analysing the often subtle changes in the surface topography, one can highlight the tool wear state. This paper utilises areal surface characterization, areal auto-correlation function (AACF) and pattern analysis to illustrate the effect of tool wear on the workpiece surface. The result shows the following: (1) tool wear, previously difficult to detect, will influence almost all of the areal surface parameters; (2) the pattern features of AACF spectrum can reflect the subtle surface texture variation with increasing tool wear. The authors consider that, combined analysis of the surface roughness and its AACF spectrum are a good choice for monitoring the tool wear state especially with the latest developments in on-machine surface metrology.