Improved model to predict machined surface roughness based on the cutting vibrations signal during hard turning

Abstract

Purpose: The objective was to study the influence of cutting vibrations in hard turning of AISI 1045 steel. Design/methodology/approach: A design of experiments using a complete factorial was used in the experiments. The specimens were tempered and quenched with 53 HRC. A piezoelectric dynamometer for turning with an acquisition data system was used in the measurements. Findings: The results showed excellent correlation between the model and results and showed that the frequency amplitudes increase the model reliability by 5%. Research limitations/implications: The instrumentation of machine and its correlation with the amplitudes of frequencies from data system acquisition could personalize the models for each experiment on the machines. Originality/value: The paper uses a commercial piece and provides important information for the improvements in the roughness of hardened steel, which is an important factor for the components surface integrity. © International OCSCO World Press. All rights reserved. 2010.