Processing Parameter Influence for Dimple Fabrication on WC Tool Inserts Using Laser Surface Texturing (LST)
M. Kore, U. Sarma, S. N. Joshi and B. Kuriachen
WC is an excellent cutting tool material, capable of shaping and cutting metallic (ferrous or non-ferrous) materials with notable surface finish, quality and precision. The performance of these tools is affected by its wear and friction in the cutting zone during the machining process. For improving the machining properties and the performance of the tools, surface modification or texturing is necessary on the tool surface. Surface modification is usually carried out by non-contact and high accuracy methods like electric discharge machining (EDM), focused ion beam (FIB), photolithography, laser surface texturing (LST), etc. In the present study, dimples were generated on the tip of WC inserts using a conventional millisecond Nd:YAG laser. The impact of laser process parameters viz. pulse duration, frequency and current on the output parameters like dimple diameter, dimple depth, heat affected zone (HAZ), aspect ratio and textured area ratio were investigated using Taguchi’s L9 orthogonal array. Regression models were employed to develop mathematical relations among the input process parameters, and the responses. The level of significance of the laser parameters on the output parameters was obtained by the analysis of variance (ANOVA). A direct dependency of the aspect ratio on the dimple depth was found, showing the same effects for the variation of laser parameters. Texture area ratio, on the other hand being directly proportional to the dimple diameter, an increase in the laser process parameters causes an increase in both the texture area ratio and the dimple depth diameter. An aspect ratio of 0.1 and a maximum textured area ratio of 56.5% were found to give the best results. The HAZ, pores and micro-cracks were also observed on the samples.
Keywords: Nd:YAG laser, tungsten carbide, WC, laser surface texturing (LST), dimple, heat affected zone (HAZ), Taguchi method, analysis of variance (ANOVA), regression model