Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints

Statistical tools such as design of experiments (DoE), analysis of variance (ANOVA) were used to develop the empirical relationship, to predict the ultimate tensile strength of the joint at the 95% percent confidence level. Response surface graph and contour plots were constructed using response sur...

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Detalles Bibliográficos
Autores principales: Rajendran, C., Srinivasan, K., Balasubramanian, V., Balaji, H., Selvaraj, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Materials Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661257/
https://www.ncbi.nlm.nih.gov/pubmed/31372402
http://dx.doi.org/10.1016/j.dib.2019.103735
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author Rajendran, C.
Srinivasan, K.
Balasubramanian, V.
Balaji, H.
Selvaraj, P.
author_facet Rajendran, C.
Srinivasan, K.
Balasubramanian, V.
Balaji, H.
Selvaraj, P.
author_sort Rajendran, C.
collection PubMed
description Statistical tools such as design of experiments (DoE), analysis of variance (ANOVA) were used to develop the empirical relationship, to predict the ultimate tensile strength of the joint at the 95% percent confidence level. Response surface graph and contour plots were constructed using response surface methodology (RSM) concept. From this investigation, it is found that the joint fabricated with a tool rotational speed of 1500 rpm, welding speed of 40 mm/min, tool tilt angle of 1.5° and tool shoulder diameter of 6 mm, exhibited maximum tensile strength of 380 MPa.
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spelling pubmed-66612572019-08-01 Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints Rajendran, C. Srinivasan, K. Balasubramanian, V. Balaji, H. Selvaraj, P. Data Brief Materials Science Statistical tools such as design of experiments (DoE), analysis of variance (ANOVA) were used to develop the empirical relationship, to predict the ultimate tensile strength of the joint at the 95% percent confidence level. Response surface graph and contour plots were constructed using response surface methodology (RSM) concept. From this investigation, it is found that the joint fabricated with a tool rotational speed of 1500 rpm, welding speed of 40 mm/min, tool tilt angle of 1.5° and tool shoulder diameter of 6 mm, exhibited maximum tensile strength of 380 MPa. Elsevier 2019-03-14 /pmc/articles/PMC6661257/ /pubmed/31372402 http://dx.doi.org/10.1016/j.dib.2019.103735 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Materials Science
Rajendran, C.
Srinivasan, K.
Balasubramanian, V.
Balaji, H.
Selvaraj, P.
Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title_full Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title_fullStr Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title_full_unstemmed Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title_short Data set on prediction of friction stir welding parameters to achieve maximum strength of AA2014-T6 aluminium alloy joints
title_sort data set on prediction of friction stir welding parameters to achieve maximum strength of aa2014-t6 aluminium alloy joints
topic Materials Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661257/
https://www.ncbi.nlm.nih.gov/pubmed/31372402
http://dx.doi.org/10.1016/j.dib.2019.103735
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