Prediction of surface roughness in end milling using swarm intelligence

被引:17
作者
El-Mounayri, H [1 ]
Dugla, Z [1 ]
Deng, HY [1 ]
机构
[1] Purdue Sch Engn & Technol, Dept Mech Engn, Indianapolis, IN USA
来源
PROCEEDINGS OF THE 2003 IEEE SWARM INTELLIGENCE SYMPOSIUM (SIS 03) | 2003年
关键词
D O I
10.1109/SIS.2003.1202272
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new technique from EC (Evolutionary Is Computation), PSO (Particle Swarm Optimization), : implemented to model the end milling process and predict the resulting surface roughness. Data collected from CNC cutting experiments using DOE approach. Data used for model calibration and validation. The inputs to the model consist of Feed, Speed and Depth of cut while the output from the model is surface roughness. The model is validated through a comparison of the experimental values with their predicted counterparts. A good agreement is found. The proved technique opens the door for a new, simple and efficient approach that could be applied to the calibration of other empirical models of machining.
引用
收藏
页码:220 / 227
页数:8
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