Measurement and uncertainty analysis of surface roughness and material removal rate in micro turning operation and process parameters optimization

被引:41
|
作者
Kumar, S. P. Leo [1 ]
机构
[1] PSG Coll Technol, Coimbatore 641004, Tamil Nadu, India
关键词
Genetic algorithm; Material removal rate; Micro turning; Optimization; Surface roughness; Uncertainty analysis; TOOL WEAR; CUTTING PARAMETERS; TAGUCHI; RSM;
D O I
10.1016/j.measurement.2019.04.029
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The research work dealt with measurement and analysis of the effects of cutting conditions include Spindle speed (n), Feed rate (f) and Depth of Cut (a(p)) on Arithmetic Average Surface Roughness (Ra) and Material Removal Rate (MRR) in micro turning operation. C360 Copper alloy and Tungsten Carbide insert are chosen as the work and tool material respectively. Taguchi L-27 Orthogonal Array based Experiments were incorporated and micro pin of size 800 mu m are fabricated in micromachining tool. Quality of the measured results validated with Type-'A' uncertainty analysis and observed a standard deviation of +/- 0.007 mu m. It is observed that, combination of lower range of process variables (within the given range) yields fine surface finish and higher range of variables yields maximum MRR but poor surface finish. Analysis of variance was performed and inferred that, "a(p)" has significant influence on Ra and MRR. Also observed that, higher `F affects surface finish by marking phenomenon. Parameters optimization was carried out using Genetic Algorithm (GA). Optimum values of Ra and MRR were found as 0.031 mu m and 0.0768 mm(3)/s respectively and their process parameters are n = 1686 rev/min, f = 10.6242 mu m/rev and a(p) = 99.45 mu m. Finally accuracy of GA results validated with confirmation experiments. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:538 / 547
页数:10
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