Abstract

The machining model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radiuses (0.4, 0.8 and 1.2 mm) under different cutting conditions such as feed rate (0.08, 0.12, 0.14, 0.16, and 0.20 mm/rev), cutting speed (250, 355, and 500 RPM) and depth of cut (0.5, 1.0, and 1.5 mm). The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels; as a result minimum surface roughness achieved by the machining model was 2.5 micrometer. The established equation and graphs show that the feed rate (0.18 mm/rev) and cutting speed (90 m/min) were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut (1.5 mm), but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant as a result linear function was used for local model. The rsme (root square mean error) for local model in interaction terms and square terms was 0.22. Finally, experimentation was carried out to identify the effectiveness of the proposed method. However, it could be seen that the first-order effect of feed rate was significant while cutting speed and depth of cut was insignificant. The predicted and optimized surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

Highlights

  • Metal cutting is one of the important and widely used manufacturing processes in engineering industries

  • The main objective of this work was to develop and optimize a model for surface roughness based on cutting speed, depth of cut, nose radius and feed rate

  • The one factor at time analysis results are shown that the repeatability of accessories are acceptable, the model of OFAT is shown the suitability of polynomial model which is used for estimating the surface roughness

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Summary

Introduction

Metal cutting is one of the important and widely used manufacturing processes in engineering industries. The study of metal cutting focuses, among others, on the features of tools, input work materials, and the machine parameter settings influencing process efficiency and output quality characteristics (or responses) [1]. Surface quality is of great importance for the functional behavior of mechanical parts [3]. Surface roughness besides tolerances impose one of the most critical constrains for cutting parameter selection in manufacturing process planning [4]. It is significantly affected by turning parameters. By choosing effectively parameters and finding optimal points it can be improved productivity for the finish turning

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