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Optimization and Property Evaluation of 0.5 mm SS304 Thick Sheets Welded by Microplasma Arc Welding with and without Post Heat Treatment


Affiliations
1 Production and IndustrialEngineering Department, National Institute of Technology Jamshedpur, Jharkhand 831014, India

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 are taken into consideration. Property evaluation and comparison of weld are 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) is applied for optimization of the weld quality at chosen process parameters and compared to that of the experimental results by considering tensile strength as an output. The ANN will be useful for estimating the welding current to yield an optimum tensile strength, thus providing better process control.

Keywords

Micro plasma arc welding (MPAW), Distortion, Artificial neural network (ANN), Residual stress, Post weld heat treatment (PWHT)
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  • Optimization and Property Evaluation of 0.5 mm SS304 Thick Sheets Welded by Microplasma Arc Welding with and without Post Heat Treatment

Abstract Views: 38  | 

Authors

Kasif Ansari
Production and IndustrialEngineering Department, National Institute of Technology Jamshedpur, Jharkhand 831014, India
Mayuri Baruah
Production and IndustrialEngineering Department, National Institute of Technology Jamshedpur, Jharkhand 831014, India

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 are taken into consideration. Property evaluation and comparison of weld are 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) is applied for optimization of the weld quality at chosen process parameters and compared to that of the experimental results by considering tensile strength as an output. The ANN will be useful for estimating the welding current to yield an optimum tensile strength, thus providing better process control.

Keywords


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