Applications of machine learning in friction stir welding: Prediction of joint properties, real-time control and tool failure diagnosis

AH Elsheikh - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Abstract Machine learning (ML) methods have received immense attention as potential
models for modeling different manufacturing systems. This paper presents a comprehensive …

[HTML][HTML] Joining of automotive sheet materials by friction-based welding methods: A review

M Haghshenas, AP Gerlich - Engineering science and technology, an …, 2018 - Elsevier
The demands for higher fuel efficiency in the automotive sector have motivated the
increased use of multi-material combinations for lightweight designs in recent years. This …

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 …

Experimental investigation, intelligent modeling and multi-characteristics optimization of dry WEDM process of Al–SiC metal matrix composite

RK Fard, RA Afza, R Teimouri - Journal of Manufacturing Processes, 2013 - Elsevier
Dry wire electrical discharge machining (WEDM) is an environmentally friendly modification
of the oil WEDM process in which liquid dielectric is replaced by a gaseous medium. In the …

The Effect of Friction Stir Welding Parameters on the Weldability of Aluminum Alloys with Similar and Dissimilar Metals

WH Khalafe, EL Sheng, MR Bin Isa, AB Omran… - Metals, 2022 - mdpi.com
The solid-state welding method known as friction stir welding (FSW) bonds two metallic work
parts, whether the same or different, by plastically deforming the base metal. The frictional …

Machined quality prediction and optimization for micro-EDM drilling of semi-conductive SiC wafer

HT Cao, JR Ho, PC Tung, YT Lin, CK Lin - Materials Science in …, 2024 - Elsevier
Abstract Semi-conductive SiC (semi-SiC) wafer is the third generation of semiconductor
materials. However, its high hardness and brittleness make it extremely difficult to machine 3 …

A comparative study of common nature-inspired algorithms for continuous function optimization

Z Wang, C Qin, B Wan, WW Song - Entropy, 2021 - mdpi.com
Over previous decades, many nature-inspired optimization algorithms (NIOAs) have been
proposed and applied due to their importance and significance. Some survey studies have …

[HTML][HTML] Friction stir welding parameter optimization using novel multi objective dragonfly algorithm

P Pitchipoo, A Muthiah, K Jeyakumar… - International Journal of …, 2021 - Elsevier
Friction stir welding (FSW) is a type of welding in which the joint is made in the solid phase
using the heat generated through friction. FSW is used to produce welds with superior …

Development of a fuzzy logic based model to elucidate the effect of FSW parameters on the ultimate tensile strength and elongation of pure copper joints

A Heidarzadeh, ÖM Testik, G Güleryüz… - Journal of Manufacturing …, 2020 - Elsevier
In this study, for the first time, a fuzzy logic model was used to elucidate and optimize the
friction stir welding of pure copper. For microstructural characterization, light microscopy …

Physics-embedded machine learning: Case study with electrochemical micro-machining

Y Lu, M Rajora, P Zou, SY Liang - Machines, 2017 - mdpi.com
Although intelligent machine learning techniques have been used for input-output modeling
of many different manufacturing processes, these techniques map directly from the input …