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Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)

This study aimed to optimize machining parameters to obtain better surface roughness and remnant depth ratio values under dry turning of NiTi-shape memory alloy (SMA). During the turning experiments, various machining parameters were used, including three different cutting speeds v(c) (105, 144, and...

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Detalles Bibliográficos
Autores principales: Zhao, Yanzhe, Cui, Li, Sivalingam, Vinothkumar, Sun, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10488984/
https://www.ncbi.nlm.nih.gov/pubmed/37687476
http://dx.doi.org/10.3390/ma16175786
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author Zhao, Yanzhe
Cui, Li
Sivalingam, Vinothkumar
Sun, Jie
author_facet Zhao, Yanzhe
Cui, Li
Sivalingam, Vinothkumar
Sun, Jie
author_sort Zhao, Yanzhe
collection PubMed
description This study aimed to optimize machining parameters to obtain better surface roughness and remnant depth ratio values under dry turning of NiTi-shape memory alloy (SMA). During the turning experiments, various machining parameters were used, including three different cutting speeds v(c) (105, 144, and 200 m/min), three different feed rates f (0.05, 0.1, and 0.15 mm/rev), and three different depths of cut a(p) (0.1, 0.15, and 0.2 mm). The effects of machining parameters in turning experiments were investigated on the response surface methodology (RSM) with Box–Behnken design (BBD) using the Design Expert 11; how the cutting parameters affect the surface quality is discussed in detail. In this context, the cutting parameters were successfully optimized using a genetic algorithm (GA). The optimized processing parameters are v(c) = 126 m/min, f = 0.11 mm/rev, a(p) = 0.14 mm, resulting in surface roughness and remnant depth ratio values of 0.489 μm and 64.13%, respectively.
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spelling pubmed-104889842023-09-09 Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA) Zhao, Yanzhe Cui, Li Sivalingam, Vinothkumar Sun, Jie Materials (Basel) Article This study aimed to optimize machining parameters to obtain better surface roughness and remnant depth ratio values under dry turning of NiTi-shape memory alloy (SMA). During the turning experiments, various machining parameters were used, including three different cutting speeds v(c) (105, 144, and 200 m/min), three different feed rates f (0.05, 0.1, and 0.15 mm/rev), and three different depths of cut a(p) (0.1, 0.15, and 0.2 mm). The effects of machining parameters in turning experiments were investigated on the response surface methodology (RSM) with Box–Behnken design (BBD) using the Design Expert 11; how the cutting parameters affect the surface quality is discussed in detail. In this context, the cutting parameters were successfully optimized using a genetic algorithm (GA). The optimized processing parameters are v(c) = 126 m/min, f = 0.11 mm/rev, a(p) = 0.14 mm, resulting in surface roughness and remnant depth ratio values of 0.489 μm and 64.13%, respectively. MDPI 2023-08-24 /pmc/articles/PMC10488984/ /pubmed/37687476 http://dx.doi.org/10.3390/ma16175786 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Yanzhe
Cui, Li
Sivalingam, Vinothkumar
Sun, Jie
Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title_full Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title_fullStr Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title_full_unstemmed Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title_short Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)
title_sort understanding machining process parameters and optimization of high-speed turning of niti sma using response surface method (rsm) and genetic algorithm (ga)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10488984/
https://www.ncbi.nlm.nih.gov/pubmed/37687476
http://dx.doi.org/10.3390/ma16175786
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