Machine learning for the prediction of edge cracking in sheet metal forming processes

This work aims to evaluate the performance of various machine learning algorithms in the prediction of metal forming defects, particularly the occurrence of edge cracking. To this end, seven different single classifiers and two types of ensemble models (majority voting and stacking) were used to mak...

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Bibliographic Details
Main Author: Marques, Armando E. (author)
Other Authors: Prates, Pedro A. (author), Fonseca, Ana R. (author), Oliveira, Marta C. (author), Soares, Martinho S. (author), Fernandes, José V. (author), Ribeiro, Bernardete M. (author)
Format: bookPart
Language:eng
Published: 2023
Subjects:
Sheet metal forming
Machine learning
Defect prediction
Edge cracking
Online Access:http://hdl.handle.net/10773/33001
Country:Portugal
Oai:oai:ria.ua.pt:10773/33001

Internet

http://hdl.handle.net/10773/33001

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