کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1704952 | 1012420 | 2012 | 16 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Regression and ANN models for estimating minimum value of machining performance Regression and ANN models for estimating minimum value of machining performance](/preview/png/1704952.png)
Surface roughness is one of the most common performance measurements in machining process and an effective parameter in representing the quality of machined surface. The minimization of the machining performance measurement such as surface roughness (Ra) must be formulated in the standard mathematical model. To predict the minimum Ra value, the process of modeling is taken in this study. The developed model deals with real experimental data of the Ra in the end milling machining process. Two modeling approaches, regression and Artificial Neural Network (ANN), are applied to predict the minimum Ra value. The results show that regression and ANN models have reduced the minimum Ra value of real experimental data by about 1.57% and 1.05%, respectively.
Journal: Applied Mathematical Modelling - Volume 36, Issue 4, April 2012, Pages 1477–1492