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228168

ARTIFICIAL NEURAL NETWORK MODELLING OF THE SURFACE ROUGHNESS OF FRICTION STIR WELDED AA7020-T6 ALUMINUM ALLOY

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Last updated: 29 Dec 2024

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Abstract

In the present investigation, lap joints of the AA7020-T6 aluminum sheets were joined using friction stir welding (FSW). The AA7020-T6 sheets has 3 mm thickness. The FSW was carried out at three different tool rotational speeds of 1200 rpm, 1400 rpm and 1600 rpm; and three different welding speeds of 20 mm/min, 40 mm/min, and 60 mm/min. During FSW, the tool tilt angle and plunging depth were kept constant at 3o and 0.5 mm, respectively. The FSW was performed using a tool with a tapered pin profile and a flat shoulder. The surface quality of the FSW specimens was evaluated by the arithmetic average roughness value (Ra). The results revealed that increasing of the tool rotational speed and/or the welding speed increases the surface roughness of AA7020-T6 lap joints. The developed artificial neural network (ANN) model showed a good agreement between the predicted and experimental results. The ANN model exhibited mean relative error (MRE) of 3.8%.

DOI

10.21608/erjsh.2020.228168

Keywords

Friction Stir Welding, artificial neural network, Surface roughness, Design of experiments

Authors

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Last Name

Abdullah

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Affiliation

Mechanical Engineering Department, Shoubra Faculty of Engineering, Benha University, Cairo, Egypt

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First Name

S.

Last Name

S. Mohammed

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Affiliation

Mechanical Engineering Department, Shoubra Faculty of Engineering, Benha University, Cairo, Egypt.

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First Name

S.

Last Name

A. Abdallah

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Affiliation

Mechanical Engineering Department, Shoubra Faculty of Engineering, Benha University, Cairo, Egypt.

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Volume

46

Article Issue

1

Related Issue

32693

Issue Date

2020-10-01

Receive Date

2022-03-30

Publish Date

2020-10-01

Page Start

1

Page End

5

Print ISSN

3009-6049

Online ISSN

3009-6022

Link

https://erjsh.journals.ekb.eg/article_228168.html

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https://erjsh.journals.ekb.eg/service?article_code=228168

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228,168

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Research articles

Type Code

2,276

Publication Type

Journal

Publication Title

Engineering Research Journal (Shoubra)

Publication Link

https://erjsh.journals.ekb.eg/

MainTitle

ARTIFICIAL NEURAL NETWORK MODELLING OF THE SURFACE ROUGHNESS OF FRICTION STIR WELDED AA7020-T6 ALUMINUM ALLOY

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Article

Created At

23 Jan 2023