Effect of powder composition, PTAW parameters on dilution, microstructure and hardness of Ni–Cr–Si–B alloy deposition: Experimental investigation and prediction using machine learning technique

The implementation of hard-facing alloy on the existing materials caters the need for high-performance surfaces in terms of wear and high temperatures. The present research explore the effect of Plasma Transferred Arc Welding (PTAW) parameters and powder composition on dilution, microstructure and hardness of the commonly used hard-facing alloy Ni-Cr-Si-B powder. The hard-facing alloy was deposited with three weight proportions of boron (2.5 %, 3 % and 3.5 %). The statistical-based Grey Relational Analysis (GRA) followed by a Machine Learning Algorithm (MLA) was implemented to identify the ideal parameters and degree of significance of each parameter and for the prediction of the responses. The dilution percentage, microstructure analysis, and phase detection were estimated through elemental analysis, Scanning electron Microscopy (SEM) and X-ray Diffraction Analysis (XRD) respectively. The experimental and modelling results revealed that 400 mm/min of scanning speed, 8 gm/min of powder delivery, 14 mm of stand-off distance, and 120 A of current were the optimal parameters along with 3.5 wt% of boron powder composition to yield a better dilution, microstructure and hardness.

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Publication Details

Journal
Heliyon
Published
2024-08-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e36087
Citations
12
Primary Topic
Advanced materials and composites
Type
article
Field-Weighted Citation Impact
2.55
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article

Effect of powder composition, PTAW parameters on dilution, microstructure and hardness of Ni–Cr–Si–B alloy deposition: Experimental investigation and prediction using machine learning technique

Kiran Shahapurkar, L. Rajeshkumar, N. Sivakumar, Venkatesh Chenrayan et al.
12 citations
Heliyon
Advanced materials and composites
2.55
article

Effect of powder composition, PTAW parameters on dilution, microstructure and hardness of Ni–Cr–Si–B alloy deposition: Experimental investigation and prediction using machine learning technique

Kiran Shahapurkar, L. Rajeshkumar, N. Sivakumar, Venkatesh Chenrayan, R. Venkatesan, Chandru Manivannan, Ritam Sharma
article en
12 citations

Abstract

The implementation of hard-facing alloy on the existing materials caters the need for high-performance surfaces in terms of wear and high temperatures. The present research explore the effect of Plasma Transferred Arc Welding (PTAW) parameters and powder composition on dilution, microstructure and hardness of the commonly used hard-facing alloy Ni-Cr-Si-B powder. The hard-facing alloy was deposited with three weight proportions of boron (2.5 %, 3 % and 3.5 %). The statistical-based Grey Relational Analysis (GRA) followed by a Machine Learning Algorithm (MLA) was implemented to identify the ideal parameters and degree of significance of each parameter and for the prediction of the responses. The dilution percentage, microstructure analysis, and phase detection were estimated through elemental analysis, Scanning electron Microscopy (SEM) and X-ray Diffraction Analysis (XRD) respectively. The experimental and modelling results revealed that 400 mm/min of scanning speed, 8 gm/min of powder delivery, 14 mm of stand-off distance, and 120 A of current were the optimal parameters along with 3.5 wt% of boron powder composition to yield a better dilution, microstructure and hardness.

HeliyonVol. 10(16)
National Institute of Technology Tiruchirappalli (IN), Alliance University (IN), Indira Gandhi Institute of Technology (IN), University of Malaya (MY), Trichy SRM Medical College Hospital and Research Centre (IN), Saveetha University (IN)
Openalex Percentile: Top 11%
Advanced materials and composites
2.55
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