Application of Data Mining Techniques to eliminate duplication of points in Geometric Datasets used for the production of Additive Manufacturing components or 3D Printed models.

Published in: Innovation in Engineering, Technology and Education for Competitiveness and Prosperity: Proceedings of the 12th Latin American and Caribbean Conference for Engineering and Technology
Date of Conference: July 21-24,2014
Location of Conference: Guayaquil,Ecuador
Authors: Rafael Obregon
Refereed Paper: #144

Abstract:

Additive Manufacturing and 3D Printing processes begin with the creation of computer generated models of the parts to be produced. Once shapes are developed they are saved or exported into a format suitable for reproduction, most commonly to a polygonal or tessellated pattern. Geometric datasets tend to be large and include a considerable number of duplicated parameters. Data Mining can be applied to determine which elements of the dataset are most relevant and sufficient to replicate the shape. Algorithms and references are used to regroup the data into new patterns, eliminating duplications, and reducing the size of the dataset.

Resumen:

La Fabricación Aditiva o Impresión 3D inicia con la creación de modelos computarizados de las partes a producir. Una vez desarrollados los modelos se exportan a un formato adecuado para su reproducción, comúnmente a un patrón poligonal o teselado. El conjunto geométrico de puntos tiende a ser muy extenso e incluye un considerable número de datos repetidos. La Minería de Datos puede aplicarse para determinar cuáles de los elementos en este conjunto de datos es relevante y suficiente para reproducir el modelo. Algoritmos y referencias son usados para reagrupar los datos en nuevos patrones, eliminando duplicidades y reduciendo el tamaño de la base de datos.