Artificial intelligence applications for friction stir welding: A review

B Eren, MA Guvenc, S Mistikoglu - Metals and Materials International, 2021 - Springer
Advances in artificial intelligence (AI) techniques that can be used for different purposes
have enabled it to be used in many different industrial applications. These are mainly used …

A survey of machine learning in friction stir welding, including unresolved issues and future research directions

U Chadha, SK Selvaraj, N Gunreddy… - Material Design & …, 2022 - Wiley Online Library
Friction stir welding is a method used to weld together materials considered challenging by
fusion welding. FSW is primarily a solid phase method that has been proven efficient due to …

Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters

RM Nejad, N Sina, DG Moghadam, R Branco… - International Journal of …, 2022 - Elsevier
In this paper, the fracture behavior and fatigue crack growth rate of the 2024-T351 aluminum
alloy has been investigated. At first, the 2024-T351 aluminum alloys have been welded …

Finite element modelling, predictive modelling and optimization of metal inert gas, tungsten inert gas and friction stir welding processes: a comprehensive review

K Kalita, D Burande, RK Ghadai… - Archives of Computational …, 2023 - Springer
Welding is an essential fabrication process in any of the construction or manufacturing
industries. Over the years, numerous welding techniques have been developed to fulfil the …

Prediction of the ultimate tensile strength (UTS) of asymmetric friction stir welding using ensemble machine learning methods

S Matitopanum, R Pitakaso, K Sethanan, T Srichok… - Processes, 2023 - mdpi.com
This research aims to develop ensemble machine-learning methods for forecasting the
ultimate tensile strength (UTS) of friction stir welding (FSW). The substance utilized in the …

[HTML][HTML] Numerical and experimental study of underwater friction stir welding of 1Cr11Ni2W2MoV heat-resistant stainless steel

M Ragab, H Liu, HA Abdel-Aleem… - Journal of Materials …, 2024 - Elsevier
Due to the benefits of solid-state joining, friction stir welding (FSW) has seen an increase in
applications in the aircraft and automotive industries. However, short tool life and heat …

Investigation on material flow and microstructural evolution mechanism in non-thinning and penetrating friction stir welded Al–Cu aluminum alloy

D Li, H Liu, S Du, X Li, Y Gao, Y Zuo - Materials Science and Engineering: A, 2023 - Elsevier
Non-thinning and penetrating friction stir welding (NTPFSW) was proposed through an
innovative welding system. The traditional backing plate was replaced by a small-size …

Ultrasonic spot welding of aluminum-copper dissimilar metals: a study on joint strength by experimentation and machine learning techniques

MP Satpathy, SB Mishra, SK Sahoo - Journal of Manufacturing Processes, 2018 - Elsevier
Ultrasonic metal welding (USMW) is one of the solid state joining techniques which provides
an alternative approach of joining soft and highly conductive materials like aluminum and …

[HTML][HTML] Finite element prediction of residual stress and deformation induced by double-pass TIG welding of Al 2219 plate

AS Ahmad, Y Wu, H Gong, L Nie - Materials, 2019 - mdpi.com
Finite element (FE) analysis of welding residual stress and deformation is one of the
essential stages in the manufacturing process of mechanical structures and parts. It aids in …

[HTML][HTML] Improving prediction of springback in sheet metal forming using multilayer perceptron-based genetic algorithm

T Trzepieciński, HG Lemu - Materials, 2020 - mdpi.com
This paper presents the results of predictions of springback of cold-rolled anisotropic steel
sheets using an approach based on a multilayer perceptron-based artificial neural network …