Abstract

Surface integrity is a critical aspect in ensuring the quality of components or products, particularly in industries such as automotive, aerospace, and machinery where superior surface finish and prolonged functionality of cylindrical parts are essential. Burnishing, a chip-less cold working finishing process, enhances the surface finish of machined workpieces through plastic deformation. This review paper delves into various aspects of the burnishing process and its impact on surface properties, drawing insights from multiple research projects. It explores topics including residual stresses, surface roughness, microhardness, cooling strategies, and modeling techniques. Key findings underscore the influence of burnishing parameters such as speed, feed rate, penetration depth, and number of passes on surface roughness and microhardness. Moreover, the process induces compressive residual strains on the workpiece surface, with their magnitude varying based on operational parameters. The choice of cooling methods, including kerosene, minimum quantity lubrication (MQL), cryogenic cooling, and hybrid cooling, significantly affects surface integrity. Various modeling approaches, such as Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Response Surface Methodology (RSM), aid in predicting and optimizing surface characteristics. Despite the extensive discussion on surface roughness, microhardness, residual stresses, cooling methods, and modeling, out-of-roundness in the burnishing process remains understudied and warrants further investigation. This review contributes valuable insights for enhancing surface qualities in manufacturing applications and deepening our understanding of the burnishing process.

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