Fuzzy Decision Tree applied to defects classification of glass manufacturing using data from a glass furnace model

Author

Costa, Herbert R do N ; Neve, Alessandro La

Author_Institution

Dept. of Comput. Sci., Centro Univ. da FEI - Brazil, São Bernardo do Campo, Brazil

fYear

2012

fDate

6-8 Aug. 2012

Firstpage

1

Lastpage

6

Abstract

Fuzzy Decision Tree (FID 3.4) and other algorithms were used for the classification of the defects that occur in the production process of glass for packing. In this study we used the Project “Newglass” installed in Portugal. This project used a model of Manufactures to study the process of manufacturing glass packaging. The database Project "Newglass” consists of the operating variables of the furnace and the percentage of defects found in end products of the factory model. The classification obtained through the Fuzzy Decision Tree was compared with the results obtained in the manufacture of glass for packing. The classifications obtained in the manufacture and in the FID 3.4 software were also compared with the classification obtained with CART (Classification and Regression Tree) and Artificial Neural Network (ANN) algorithms.

Keywords

decision trees; fuzzy set theory; glass manufacture; production engineering computing; ANN algorithm; CART; FID 3.4 software; Project Newglass; artificial neural network; classification-and-regression tree; defect classification; factory model; fuzzy decision tree; glass furnace model; glass manufacturing; glass packaging; Classification algorithms; Databases; Decision trees; Furnaces; Glass; Raw materials; Standards;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American

Conference_Location

Berkeley, CA

ISSN

pending

Print_ISBN

978-1-4673-2336-9

Electronic_ISBN

pending

Type

conf

DOI

10.1109/NAFIPS.2012.6291000

Filename

6291000