Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm

被引:92
|
作者
Kilickap, Erol [1 ]
Huseyinoglu, Mesut [1 ]
Yardimeden, Ahmet [1 ]
机构
[1] Dicle Univ, Dept Mech Engn, TR-21280 Diyarbakir, Turkey
关键词
Response surface methodology; Genetic algorithm; Box-Behnken design of experiments; Minimum quantity lubricant; Drilling; Surface roughness; ALUMINUM-SILICON ALLOYS; MINIMUM QUANTITY; TURNING PROCESS; PREDICTION; LUBRICANT; TAGUCHI; PERFORMANCE; DESIGN; STEEL; TOOL;
D O I
10.1007/s00170-010-2710-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Modeling and optimization of cutting parameters are one of the most important elements in machining processes. The present study focused on the influence machining parameters on the surface roughness obtained in drilling of AISI 1045. The matrices of test conditions consisted of cutting speed, feed rate, and cutting environment. A mathematical prediction model of the surface roughness was developed using response surface methodology (RSM). The effects of drilling parameters on the surface roughness were evaluated and optimum machining conditions for minimizing the surface roughness were determined using RSM and genetic algorithm. As a result, the predicted and measured values were quite close, which indicates that the developed model can be effectively used to predict the surface roughness. The given model could be utilized to select the level of drilling parameters. A noticeable saving in machining time and product cost can be obtained by using this model.
引用
收藏
页码:79 / 88
页数:10
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