%0 Journal Article %1 Brezocnik:2004:JMPT %A Brezocnik, M. %A Kovacic, M. %A Ficko, M. %D 2004 %J Journal of Materials Processing Technology %K Evolutionary Manufacturing Milling, Surface algorithms algorithms, genetic programming, roughness; systems, %P 28--36 %R doi:10.1016/j.jmatprotec.2004.09.004 %T Prediction of surface roughness with genetic programming %V 157-158 %X 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.

@article{Brezocnik:2004:JMPT, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Brezocnik, M. and Kovacic, M. and Ficko, M.}, biburl = {https://www.bibsonomy.org/bibtex/206a953bbad2147d8c802275ce04fa3c1/brazovayeye}, doi = {doi:10.1016/j.jmatprotec.2004.09.004}, interhash = {1999c6a0b3b7d1c6d76a790a750618d1}, intrahash = {06a953bbad2147d8c802275ce04fa3c1}, issn = {0924-0136}, journal = {Journal of Materials Processing Technology}, keywords = {Evolutionary Manufacturing Milling, Surface algorithms algorithms, genetic programming, roughness; systems,}, month = {20 December 2004}, notes = {Originally in AMME 2000-2002 conference \cite{Brezocnik:2002:AMME}. Achievements in Mechanical and Materials Engineering Conference. Selected for publication as full paper in the Special Issue of the Journal of Materials Processing Technology (Elsevier, the Netherlands)}, pages = {28--36}, timestamp = {2008-06-19T17:37:01.000+0200}, title = {Prediction of surface roughness with genetic programming}, volume = {157-158}, year = 2004 }