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Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis
In this study, a multi-objective optimization of directed energy deposition (DED) process was conducted with Taguchi-Grey relational analysis. The used part was designed as a flat rectangle which would be deposited by a single-layer and multi-track DED process. Firstly, after finishing Taguchi exper...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9053841/ https://www.ncbi.nlm.nih.gov/pubmed/35530372 http://dx.doi.org/10.1007/s00170-022-09210-3 |
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author | Chang, Yu-Yang Qiu, Jun-Ru Hwang, Sheng-Jye |
author_facet | Chang, Yu-Yang Qiu, Jun-Ru Hwang, Sheng-Jye |
author_sort | Chang, Yu-Yang |
collection | PubMed |
description | In this study, a multi-objective optimization of directed energy deposition (DED) process was conducted with Taguchi-Grey relational analysis. The used part was designed as a flat rectangle which would be deposited by a single-layer and multi-track DED process. Firstly, after finishing Taguchi experiments, the effects of five control factors (laser power, overlap ratio, powder feed rate, scanning speed and laser defocus distance) on three DED product qualities (cladding efficiency, surface roughness and porosity) were, respectively, analyzed. Then, through Grey relational analysis (GRA), an optimal factor setting which can take all qualities into account was found and had better deposition results compared with previous setting. Furthermore, ANOVAs were conducted to find out significant factors of each qualities. By using the significant factors as variations, three second-order polynomial regression predictive models for qualities were created. Based on the GRA and ANOVAs results, additional one-factor-at-a-time (OFAT) experiments which used the optimal setting as the center point were performed. The qualities variation resulting from adjusting overlap ratio and laser defocus distance of optimal setting were investigated, and the results were also used as additional data to verified the accuracies of three regression models. |
format | Online Article Text |
id | pubmed-9053841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-90538412022-05-02 Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis Chang, Yu-Yang Qiu, Jun-Ru Hwang, Sheng-Jye Int J Adv Manuf Technol Original Article In this study, a multi-objective optimization of directed energy deposition (DED) process was conducted with Taguchi-Grey relational analysis. The used part was designed as a flat rectangle which would be deposited by a single-layer and multi-track DED process. Firstly, after finishing Taguchi experiments, the effects of five control factors (laser power, overlap ratio, powder feed rate, scanning speed and laser defocus distance) on three DED product qualities (cladding efficiency, surface roughness and porosity) were, respectively, analyzed. Then, through Grey relational analysis (GRA), an optimal factor setting which can take all qualities into account was found and had better deposition results compared with previous setting. Furthermore, ANOVAs were conducted to find out significant factors of each qualities. By using the significant factors as variations, three second-order polynomial regression predictive models for qualities were created. Based on the GRA and ANOVAs results, additional one-factor-at-a-time (OFAT) experiments which used the optimal setting as the center point were performed. The qualities variation resulting from adjusting overlap ratio and laser defocus distance of optimal setting were investigated, and the results were also used as additional data to verified the accuracies of three regression models. Springer London 2022-04-29 2022 /pmc/articles/PMC9053841/ /pubmed/35530372 http://dx.doi.org/10.1007/s00170-022-09210-3 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Chang, Yu-Yang Qiu, Jun-Ru Hwang, Sheng-Jye Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title | Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title_full | Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title_fullStr | Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title_full_unstemmed | Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title_short | Multi-objective optimization of directed energy deposition process by using Taguchi-Grey relational analysis |
title_sort | multi-objective optimization of directed energy deposition process by using taguchi-grey relational analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9053841/ https://www.ncbi.nlm.nih.gov/pubmed/35530372 http://dx.doi.org/10.1007/s00170-022-09210-3 |
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