| Title: | Prediction of surface roughness with genetic programming |
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| Authors: | ID Brezočnik, Miran (Author)
ID Kovačič, Miha (Author)
ID Ficko, Mirko (Author) |
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| Files: |  http://dx.doi.org/10.1016/j.jmatprotec.2004.09.004
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | In this paper we propose genetic programming to predict surface roughness in end-milling. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Spindle speed, feed rate,depth of cut, and vibrations are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by genetic programming. Accuracy of the best model was proved with the testing data. It was established that the surface roughness is most influenced by the feed rate, whereas the vibrations increase the prediction accuracy. |
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| Keywords: | end milling, surface roughness, prediction of surface roughness, genetic programming |
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| Year of publishing: | 2004 |
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| PID: | 20.500.12556/DKUM-27532  |
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| UDC: | 621.914:004.89 |
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| ISSN on article: | 0924-0136 |
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| COBISS.SI-ID: | 9026582 |
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| NUK URN: | URN:SI:UM:DK:CX2LMQOO |
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| Publication date in DKUM: | 01.06.2012 |
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| Views: | 2326 |
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| Downloads: | 138 |
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| Metadata: |    |
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| Categories: | Misc.
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