| dc.creator | Pedro Pérez Villanueva | |
| dc.date | 2008 | |
| dc.date.accessioned | 2023-07-20T18:56:57Z | |
| dc.date.available | 2023-07-20T18:56:57Z | |
| dc.identifier | http://comimsa.repositorioinstitucional.mx/jspui/handle/1022/389 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7721155 | |
| dc.description | The aim of this research is to present a new methodology for predicting and optimizing the surface roughness during machining of 1018 and 4140 Steel. There is particular interest in finding the best machining value parameters that should be used to achieve good surface roughness. These parameter values can be found by this neural intelligent approach. This methodology analyzes and identifies the parameters involved in the machining process; with this information the model is able to predict the surface roughness value in different conditions and then optimize the results with different intelligent heuristics. The experimental results show that we may conclude that this intelligent system is a suitable methodology for predicting and optimizing surface roughness during the machining of 1018 and 4140 Steel. | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.relation | citation:Development and Application of an Intelligent System to Predict and Optimize the Surface Roughness of 1018 and 4140 Steel. I. Escamilla-Salazar, Pedro Perez, L. Torres-Treviño , Patricia C. Zambrano Robledo. November 2008 DOI: 10.1109/CERMA.2008.68 SourceIEEE Xplore Conference: Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08 | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by-nc-nd/4.0 | |
| dc.subject | info:eu-repo/classification/ARTÍCULO/NEURAL NETWORK | |
| dc.subject | info:eu-repo/classification/cti/7 | |
| dc.subject | info:eu-repo/classification/cti/7 | |
| dc.title | Development and Application of an Intelligent System to Predict and Optimize the Surface Roughness of 1018 and 4140 Steel | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.audience | students | |
| dc.audience | researchers | |
