Optimizing machining parameters to combine high productivity with high surface integrity in grinding silicon carbide ceramics

Abstract

Advanced ceramics such as silicon carbide offer many desirable characteristics for industrial and commercial use in terms of their high temperature tolerance, wear and abrasive resistance, and corrosion resistance. However, the machining of ceramics into practical forms presents a challenge because of the difficulty and cost involved in the material removal process due to their high hardness and high brittleness. In this work, experiments were conducted to study the effect of various parameters such as depth of cut, table feed, size and density of grit on the metal removal rate, surface roughness, surface and subsurface damages. Mathematical models were developed using the data obtained experimentally considering the significant parameters only. Finally, a genetic algorithm (GA) code has been developed to optimize the ceramic grinding process with multiple objectives. The manufacturer׳s constraints on the basis of functional requirements of the component were also considered in the GA code. The study demonstrates that the grinding process parameters can be varied to achieve better metal removal rate, good surface finish and lower surface and subsurface damages simultaneously.