Additive friction stir deposition: a review on processes, parameters, characteristics, and applications

Li, Xia; Li, Xiaoliang; Hu, Shenheng; Liu, Yubing; Ma, Diao

doi:10.1007/s00170-024-13890-4

Int J Adv Manuf Technol

2024

DOI: 10.1007/s00170-024-13890-4

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Additive friction stir deposition: a review on processes, parameters, characteristics, and applications

Xia Li,

Xiaoliang Li,

Shenheng Hu

et al.

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Cited by 3 publications

References 110 publications

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An overview of strategies for identifying manufacturing process window through design of experiments and machine learning techniques while considering the uncertainty associated with

Cabrera,

Zouhri,

Zimmer-Chevret

et al. 2024

Int J Adv Manuf Technol

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An overview of strategies for identifying manufacturing process window through design of experiments and machine learning techniques while considering the uncertainty associated with

Cabrera,

Zouhri,

Zimmer-Chevret

et al. 2024

Int J Adv Manuf Technol

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Friction Stir-Based Techniques: An Overview

El-Zathry,

Akinlabi,

Woo

et al. 2024

Weld World

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Friction stir-based techniques (FSTs), originating from friction stir welding (FSW), represent a solid-state processing method catering to the demands of various industrial sectors for lightweight components with exceptional properties. These techniques have gained much more attraction by providing an opportunity to tailor the microstructure and enhance the performance and quality of produced welds and surfaces. While significant attention has historically been directed towards the FSW process, this review delves into the working principles of FSTs, exploring their influence on mechanical properties and microstructural characteristics of various materials. Additionally, emphasis is placed on elucidating the advancement of hybrid FSW processes for both similar and dissimilar metal components, aimed at enhancing welding quality through meticulous control of grain textures, structures, precipitation, and phase transformations. Finally, the review identifies current knowledge gaps and suggests future research directions. This review paper synthesises academic literature sourced from the Web of Science (WoS) and Scopus databases, supplemented by additional sources such as books from the last 15 years.

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Machine learning classification applied to the effect of AFSD process parameters on tensile properties

Zhu,

Wang,

Wang

et al. 2024

Materials Letters

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Additive friction stir deposition: a review on processes, parameters, characteristics, and applications

Cited by 3 publications

References 110 publications

An overview of strategies for identifying manufacturing process window through design of experiments and machine learning techniques while considering the uncertainty associated with

An overview of strategies for identifying manufacturing process window through design of experiments and machine learning techniques while considering the uncertainty associated with

Friction Stir-Based Techniques: An Overview

Machine learning classification applied to the effect of AFSD process parameters on tensile properties

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