Effect of electrode materials and process parameters on deposition characteristics during GMAW-AM

Pattanayak, Suvranshu; Sahoo, Susanta Kumar; Sahoo, Ananda Kumar

doi:10.1080/10426914.2023.2217895

Cited by 4 publications

(1 citation statement)

References 47 publications

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“…In the ever-evolving landscape of materials science and manufacturing, AISI 904L stainless steel stands out as a super austenitic alloy with exceptional properties [2], encompassing high strength, weld ability, and corrosion resistance [3]. The weld bead geometry, encompassing crucial parameters like DP, BW, and TS [4], assumes a pivotal role in dictating the structural integrity and performance of welded joints. In this context, the development of an accurate predictive model for weld bead geometry in laser-welded joints made from AISI 904L super austenitic stainless steel under Argon shielding gases emerges as essential [5].…”

Section: Introductionmentioning

confidence: 99%

LSTM Modeling for Improved Laser Welding of AISI 904 L Stainless Steel for optimal Parameter Selection

2024

IRJMETS

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The welded joints of AISI 904 L super austenitic stainless steel are extensively utilized in automotive, ship, and aerospace industries, with joint quality assessed based on weld seam geometry, microstructures, and mechanical properties. However, selecting optimal weld input parameters to achieve desired specifications is traditionally time-consuming and relies heavily on the expertise of welding engineers or operators. To address this challenge and improve weld seam geometry and joint quality, this research proposes employing Long Short Term Memory (LSTM) modelling for laser welding of AISI 904 L stainless steel. The study systematically develops and evaluates LSTM models to predict weld bead geometry, including depth of penetration (DP), bead width (BW), and tensile strength (TS), with Argon shielding gases. By enhancing operator's expertise in parameter selection, this research significantly reduces time consumption, serving as a valuable tool for optimizing the welding process and enabling informed decision-making.

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