LINEAR REGRESSION MODELING IN MACHINING OF TI 6AL 4V ALLOY USING TO PREDICT SURFACE ROUGHNESS
The objective of this work is to present a methodology to predict the roughness during the machining process of the Ti 6Al 4V, with a linear regression model, considering the parameters of speed rate, feed and depth as an input. The data used in this job was taken from work conduce in FIME, using mi...
| Autor: | |
|---|---|
| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2009 |
| País: | México |
| Recursos: | Corporación Mexicana de Investigación en Materiales |
| Repositório: | Repositorio COMIMSA |
| Idioma: | inglês |
| OAI Identifier: | oai:comimsa.repositorioinstitucional.mx:1022/398 |
| Acesso em linha: | http://comimsa.repositorioinstitucional.mx/jspui/handle/1022/398 |
| Access Level: | Acceso aberto |
| Palavra-chave: | info:eu-repo/classification/ARTÍCULO/LINEAR REGRESSION info:eu-repo/classification/cti/7 info:eu-repo/classification/cti/33 |
| Resumo: | The objective of this work is to present a methodology to predict the roughness during the machining process of the Ti 6Al 4V, with a linear regression model, considering the parameters of speed rate, feed and depth as an input. The data used in this job was taken from work conduce in FIME, using milling process in a rectangular pieces of titanium (Ti 6Al-4V), the tool was an endmill coated with Aluminum Titanium Nitride (AlTiN) with 4 cutting edge and 3/8" on a diameter of the tool. The milling was carried out over a length of 47 mm, using a design of experiment with 3 factors and 3 levels, giving a total of 27 experiments with 3 different tests. The roughness was measure with a ZEISS Perfilometers Surfcom 1500 SD2 with an automatic control. The model is useful to build a surface of the response of the machining process. This model can be used to predict the effect in roughness when the parameters are changed without risks and high costs; however, the model must be validated in order to be used as a predictor. The results indicate the ways to get a good model. |
|---|