Analyzing Different Techniques For Surface Characterization

Abstract

This research examines various methodologies for surface characterization with particular emphasis on statistical and fractal approaches. The study analyzes existing literature to identify the most effective techniques for quantifying surface roughness at micro and nano scales. Through systematic comparison of mathematical models, including those developed by Borodich, Longuet-Higgins, and others, this paper establishes a comprehensive framework for selecting appropriate characterization methods based on specific surface properties and application requirements. Experimental validation demonstrates that fractal-based approaches offer superior precision for irregular surfaces, while statistical methods remain optimal for surfaces with regular patterns. The findings contribute to enhanced understanding of tribological interactions and provide practical guidelines for researchers and engineers in fields ranging from materials science to precision manufacturing