RT Journal Article
T1 A comparison of different discriminant analysis techniques in a steel industry welding process
A1 Prats-Montalbán, José M.
A1 Ferrer, Alberto
A1 Malo, J. L.
A1 Gorbeña, J.
AB The present work compares several statistical discriminant analysis techniques applied to a steel industry welding process. Data from 85 variables collected from 18,605 links, classified as Good (18,381), Defective (195) or Bad (29) from laboratory analysis, are available. Process engineers want to find out which variables explain the main differences between the three defined types, so they can implement effective action to reduce the percentage of Defective and Bad links. The approaches used are SIMCA, Global PCA, PLS-DA and Fisher's Linear Discriminant Analysis (LDA). The dataset comprises two kinds of variables, one for the chemical properties of the links, and the other related to the welding process. All the above approaches basically lead to the same results and match the ones derived from the more traditional Fisher s Linear Discriminant Analysis (LDA) technique. The pros and cons of the approaches used are discussed.
SN 0169-7439
YR 2006
FD 2006-01-20
LK https://hdl.handle.net/11556/3562
UL https://hdl.handle.net/11556/3562
LA eng
NO Prats-Montalbán , J M , Ferrer , A , Malo , J L & Gorbeña , J 2006 , ' A comparison of different discriminant analysis techniques in a steel industry welding process ' , Chemometrics and Intelligent Laboratory Systems , vol. 80 , no. 1 , pp. 109-119 . https://doi.org/10.1016/j.chemolab.2005.08.005
NO The authors would like to thank to the referees for their helpful comments and suggestions that have improved the consistency of this work. This research was supported by the Spanish Government (Science and Technology Ministry) and the European Union (RDE funds) under the project DPI 2001-2749-C02. The authors want to thank Vicinay Cadenas S.A. for its support, providing the data and sharing its process knowledge.
DS TECNALIA Publications
RD 31 jul 2024