ANOVA Analysis and L9 Taguchi Design for Examination of Flat Slide Burnishing of Unalloyed Structural Carbon Steel

Abstract

Diamond burnishing is a finishing precision machining that is often used to improve the quality characteristics of previously machined surfaces. With its help, the surface roughness can be reduced, the surface hardness can be increased, and the tensile stresses remaining in the surface after cutting can be transformed into compressive ones, and these changes can increase the service life of the components. Diamond burnishing was typically developed for processing cylindrical surfaces and is most often used for this type of surface. In this manuscript, we present a new method with the help of sliding burnishing, which can also be used on flat surfaces. By using the clamping head of a special tool into the main spindle of the vertical milling machine and moving it along a suitable path, the flat surface can be burnished. Machining experiments were carried out with the new type of tool on general-purpose, unalloyed, structural carbon steel samples on which the flat surfaces were previously generated by face milling. The examined parameters were the burnishing force F, the feed fb, and the number of passes (NoP). The L9 Taguchi experiment design was applied for executing flat slide burnishing, and the examination was conducted by ANOVA analysis. This research contributes to the field by providing insights into optimizing the burnishing process parameters for achieving desired surface quality in milling operations.

Optimization of the Surface Roughness and Chip Compression Ratio of Duplex Stainless Steel in a Wet Turning Process Using the Taguchi Method

“…The formula for the smaller-the-better signal-to-noise (S/N) ratio is given in Equation ( 2), which is a measure of the variation in the output quality characteristic (signal) relative to the variation due to other factors (noise). By minimizing the variation in the output quality characteristic, the S/N ratio is increased, leading to higher quality and lower costs [38]. The smaller-the-better S/N ratio (minimization) is calculated as follows:…”