Optimization and property evaluation of 0.5 mm SS304 thick sheets welded by microplasma arc welding with and without post heat treatment

Authors

DOI:

https://doi.org/10.56042/ijems.v31i3.6628

Keywords:

Micro plasma arc welding (MPAW), Distortion, Artificial neural network (ANN), Residual stress, Post weld heat treatment (PWHT)

Abstract

The present work investigates the micro plasma arc welding (MPAW) of SS304L of 0.5 mm steel sheets. It primarily highlights the weld quality of SS304 of 0.5 mm thickness with and without post weld heat treatment (PWHT). Thin sheets are more prone to distortion at time of solidification because of residual stress induced. After PWHT of the welded sample, the distortion is reduced. The effect of input parameters such as pulse current, gas flow rate and welding speed were taken into consideration. Property evaluation and comparison of weld were carried out before and after the PWHT by hardness, tensile test, microstructure, X-Ray Diffraction (XRD) and scanning electron microscope (SEM). Furthermore, artificial neural network (ANN) was applied for optimization of the weld quality at chosen process parameters and compared to that of the experimental results by considering tensile strength as am output. The ANN will be useful for estimating the welding current to yield an optimum tensile strength, thus providing better process control.

Author Biographies

Kasif Ansari, Department of Production and Industrial Engineering, National Institute of Technology Jamshepur

Research Scholar

Department of Prodcution and Industrial Engineering

National Institute of Technology Jamshedpur

831014, Jharkhand, India

Mayuri Baruah, Department of Production and Industrial Engineering, National Institute of Technology Jamshepur

Assistant Professor
Department of Production and Industrial Engineering
National Institute of Technology Jamshedpur
831014, Jharkhand, India

Downloads

Published

2024-10-23