Selection of Optimum Drilling Parameters on Burr Height Using Response Surface Methodology and Genetic Algorithm in Drilling of AISI 304 Stainless Steel

被引:31
作者
Kilickap, Erol [1 ]
Huseyinoglu, Mesut [1 ]
机构
[1] Dicle Univ, Dept Mech Engn, TR-21280 Diyarbakir, Turkey
关键词
Box-Behnken Design; Burr Height; Drilling; Genetic Algorithm; Response surface methodology; 316L STAINLESS-STEEL; NEURAL-NETWORKS; OPTIMIZATION; SIZE; TAGUCHI; PERFORMANCE; ALLOY; TOOLS; MODEL;
D O I
10.1080/10426911003720854
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article illustrates an application of response surface methodology (RSM) and genetic algorithm (GA) for selecting the optimum combination values of drilling parameters affecting the burr height in drilling of AISI 304 stainless steel. The purpose of this article is to investigate the influence of the cutting parameters, such as cutting speed and feed rate, and point angle on burr height produced when drilling AISI 304 stainless steel. The experiments were conducted based on the Box-Behnken design. The measured results were collected and analyzed with the aid of a commercial software package Design Expert 6 and Matlab. A mathematical prediction model was developed using RSM) for the burr height. The effects of drilling parameters on the burr height were evaluated using RSM and optimum drilling conditions for minimizing the burr height were determined using GA. The GA optimization results have revealed that the minimum burr height was obtained at lower cutting speed and feed rates while at higher point angle.
引用
收藏
页码:1068 / 1076
页数:9
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