Abstract It is of crucial importance to minimize the surface scratches that occur during abrasive processes in order to maintain the mechanical properties of products, improve surface quality and reduce subsurface cracks. However, current research lacks an evaluation index system for assessing and controlling surface scratches on stainless steel substrates. Addressing this issue, an evaluation index for scratches based on the surface topography characteristics of the workpiece is proposed, which is utilized to assess the state of scratches on the workpiece surface. First, using image processing techniques to screen 3D scratch data on the workpiece surface addresses the challenge of extracting 3D scratch features. Second, a feature evaluation metric for assessing lapping scratches was designed based on the extracted combined features. Finally, the influences of the abrasive grain size and lapping parameters on the characterization of lapping scratch features were explored and analyzed. The results of the Analysis of Variance indicate that the effect of lapping time on the number of scratches does not achieve statistical significance. Regression analysis reveals that reducing abrasive particle size and lapping pressure significantly affect the number of scratches and the average scratch depth. Furthermore, a negative correlation is observed between the rotational speed of lapping pad and the number of scratches and the average scratch depth. Among these factors, abrasive particle size has the most prominent effect on the number of scratches and the average scratch depth. Specifically, when abrasive grains with a particle size of w10 were used for processing, the minimum number of scratches observed was 28, with an average scratch depth of 315.62 nm and the density distribution coefficient value is 0.31. Compared to the abrasive particle size w50, there was a decrease of 57.58%, 52.38% and 35.48%.
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