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Analysis of Poor Quality Cost in Auto Industry: A Case Study Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Investigation of Quality of Clean-Cut Surface for Sheet Metal Blanking Using Decision Tree

Authors : Pradip Patil, Vijaya Patil

Published in: Proceedings of International Conference on Intelligent Manufacturing and Automation

Publisher: Springer Nature Singapore

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Abstract

In case of sheet metal blanking, inadequate trimmed condition of such a blanked material may produce fit concerns in the assembly. Cracks may form due to uneven surfaces, leading to a loss of exterior smoothing and improved efficacy. Four underlying parameters are selected after punching: shear angle, punch penetration, burr height, fracture angle as decision-making input parameters to measure quality of clean-cut surface. The fracture depth is determined by gradually increasing the punch penetration. Experiments are conducted with uni-punch tool on the power press, and sheet metal material is IS277GI. This research aims to assess the cut surface quality using surface roughness value, which is categorized into three groups. To measure the efficiency of the cut surface, a classification model is developed adopting the machine learning decision tree classifier technique. The model's reliability is 93% of the Gini and Entropy index.

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Metadata
Title
Investigation of Quality of Clean-Cut Surface for Sheet Metal Blanking Using Decision Tree
Authors
Pradip Patil
Vijaya Patil
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of International Conference on Intelligent Manufacturing and Automation

Print ISBN: 978-981-19-7970-5

Electronic ISBN: 978-981-19-7971-2

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-7971-2_10

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