The surface layer properties of super-hard materials may be modified by a laser beam treatment and the regular texturization is one of possible approaches. The designed experiment was conducted based on two main controlled factors: the average diameter of cavities and the level of the blackening. The obtained dataset was processed with a response surface model for the coefficient of friction as the outcome. Typical statistical analysis of data with quantitative control factors bases on many theoretical assumptions, with the most important and the most influential one: the normality of random noises distributions. Such assumption is often used but rarely it is analyzed for its weakness and large uncertainty in results. The paper describes a non-parametric approach to the statistical analysis of the uncertainty. It releases us from the direct assumption of particular probability distributions. The bootstrap is formally the method based on random resampling with replacement from the source dataset. It allows to identify the whole distribution shape of raw data and related confidence intervals without additional assumptions about particular distribution. The paper presents the analysis processed for the practical case: original, commercially available rings for front sealing sintered from SiC with a texture modified by a laser beam and tested on tribological tester for changed properties. The paper contains notes on encountered difficulties and possible guidelines for similar analysis.Keywords: Bootstrap, uncertainty, non-parametric approach, tribology, laser beam texturization
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