Modelo predictivo para acabado superficial en el proceso de texturizado por EDT

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work aims at introducing Bayesian network-based classifiers to predict parameters defining surface roughness (Ra), when texture is produced by Electro Discharge Texturing (EDT) because the non-linearity, instabilities and also somewhat expensive experimentation of the process, robust and reliable algorithms to deal with all the factors that are difficult to characterize are necessary to provide appropriate prediction techniques. A series of experiments were conducted using a modified EDM machine ALIC-1 with traverse motions, providing the means to produce plane surface textures. With data collected were constructed models using Bayesian networks, the validation tests showed acceptable behavior within the operating range. Consistent results were obtained with the physical phenomena governing the process and shows that it is possible to find a surface roughness with particular specifications. Key words: Surface roughness, Bayesian networks, EDT, EDM.
Original languageSpanish
Title of host publicationMétodos Numéricos y sus Aplicaciones en Diferentes Areas
Pages484-491
Number of pages8
Publication statusPublished - 1 Jan 2013
EventIX Congreso Colombiano de Métodos Numéricos: Simulación en Ciencias y Aplicaciones Industriales, IX CCMN 2013 -
Duration: 1 Jan 2013 → …

Conference

ConferenceIX Congreso Colombiano de Métodos Numéricos: Simulación en Ciencias y Aplicaciones Industriales, IX CCMN 2013
Period1/01/13 → …

Cite this

Machado, C. M. M. (2013). Modelo predictivo para acabado superficial en el proceso de texturizado por EDT. In Métodos Numéricos y sus Aplicaciones en Diferentes Areas (pp. 484-491)