Uncertainty of Cutting Edge Roughness Estimation Depending on Waviness Filtration

The quality of surface finishing of manufactured parts is influenced by material and texture of the cutting edge as well as cutting parameters. To characterize the surface texture of a cutting tool standardized statistical roughness parameters are used as provided by inspection tools, i.e. profilers and microscopes. A topography scan undergoes several data analysis steps to detrend roughness from waviness and form before the standardized procedures (ISO 4287 and ISO 13565-2) are applied to estimate the statistical parameters of the roughness profile.A new series of ISO-standards (16610-xx) has been developed during the past decade that provide besides the Gaussian filtration method alternative filter algorithms. Each filter has a different kernel characteristics delivering slightly different curvatures of the waviness profile. This article shows the influence of the shape of filter kernels on roughness parameters and investigates possible estimation of the uncertainty of roughness amplitude density distributions accordingly.The filtration dependence of roughness parameters will be illustrated for a typical cutting tool, as example one of uncoated carbide.