Supervised Machine Learning Models for Predicting SS304H Welding Properties Using TIG, Autogenous TIG, and A-TIG

Supervised Machine Learning Models for Predicting SS304H Welding Properties Using TIG, Autogenous TIG, and A-TIG

This investigation explores the application of supervised machine learning regression approaches to predict various responses, including penetration, bead width, bead height, hardness, ultimate tensile strength, and percentage elongation in autogenous TIG-, A-TIG-, and TIG-welded joints of SS304H, w...

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Bibliographic Details
Main Authors: Subhodwip Saha, Barun Haldar, Hillol Joardar, Santanu Das, Subrata Mondal, Srinivas Tadepalli
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Crystals
Subjects:
A-TIG
autogenous TIG
supervised machine learning
process parameter optimization
Online Access:https://www.mdpi.com/2073-4352/15/6/529
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