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 …

AI for tribology: Present and future

N Yin, P Yang, S Liu, S Pan, Z Zhang - Friction, 2024 - Springer
With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI)
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …

Machine learning approach with various regression models for predicting the ultimate tensile strength of the friction stir welded AA 2050-T8 joints by the K-Fold cross …

B Anandan, M Manikandan - Materials Today Communications, 2023 - Elsevier
This research work aims to develop the friction stir welding (FSW) technique to resolve the
solidification issues when joining the AA2050-T8. The identification of the right process …

Machine learning approach for predicting the peak temperature of dissimilar AA7050-AA2014A friction stir welding butt joint using various regression models

B Anandan, M Manikandan - Materials Letters, 2022 - Elsevier
Friction stir welding (FSW) is a solid-state joining process that produces joints without
melting and recasting. This process gains attention in the aerospace sectors for joining …

Influence of cooling conditions on tensile lap shear strength and microstructure of friction stir welded aluminum alloy 5052-H32 and polycarbonate light weight hybrid …

BM Nagarajan, M Manoharan - Journal of Manufacturing Processes, 2022 - Elsevier
The joining of dissimilar materials, notably polymer and metal, is incredibly demanding due
to the differences in the materials' mechanical, chemical, and thermal characteristics. In this …

Determination of the Ultimate Tensile Strength (UTS) of friction stir welded similar AA6061 joints by using supervised machine learning based algorithms

A Mishra, R Morisetty - Manufacturing Letters, 2022 - Elsevier
Abstract The Ultimate Tensile Strength (MPa) of identical FSWed AA 6061 joints is
determined using five Supervised Machine Learning regression-based and classification …

Application of machine learning approaches to predict joint strength of friction stir welded aluminium alloy 7475 and PPS polymer hybrid joint

R Sandeep, A Natarajan - Proceedings of the Institution of …, 2022 - journals.sagepub.com
Vehicle weight has been a critical concern in the aerospace and automobile industries for
decades. Integrating dissimilar aluminium and polymer hybrid structures is beneficial for …

Effect of polynomial, radial basis, and Pearson VII function kernels in support vector machine algorithm for classification of crayfish

FH Garabaghi, R Benzer, S Benzer, AÇ Günal - Ecological Informatics, 2022 - Elsevier
Freshwater crayfish are one of the most important aquatic organisms that play a pivotal role
in the aquatic food chain as well as serving as bioindicators for the aquatic ecosystem health …

Recent developments in tensile properties of friction welding of carbon fiber-reinforced composite: A review

M Asmael, B Safaei, O Kalaf, Q Zeeshan… - Nanotechnology …, 2022 - degruyter.com
In this review article, the joining of carbon fiber-reinforced polymer composite with metallic
materials by using friction welding techniques was discussed and the effects of process …

Strategies to improve joint strength of friction lap welded AA7475/PPS hybrid joint with surface pre-treatment on AA7475

R Sandeep, BM Nagarajan, SK Kumar, SJ Adarsh… - Materials Letters, 2023 - Elsevier
Friction lap welding (FLW) technology has recently emerged as a promising joining
technology to join aluminium alloys and polymers. The strength of the metal-polymer hybrid …