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Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm

As a new, high-strength and clean cast iron material, nitrogen-containing gray cast iron has excellent properties and a wide range of application prospects. However, the excellent material properties of the material not only make the machinability challenging, but also the high efficiency and qualit...

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Detalles Bibliográficos
Autores principales: Lin, Yongchuan, Ma, Jiyang, Lai, Debin, Zhang, Jingru, Li, Weizhu, Li, Shengzhu, He, Shengjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691928/
https://www.ncbi.nlm.nih.gov/pubmed/36439750
http://dx.doi.org/10.1016/j.heliyon.2022.e11629
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author Lin, Yongchuan
Ma, Jiyang
Lai, Debin
Zhang, Jingru
Li, Weizhu
Li, Shengzhu
He, Shengjian
author_facet Lin, Yongchuan
Ma, Jiyang
Lai, Debin
Zhang, Jingru
Li, Weizhu
Li, Shengzhu
He, Shengjian
author_sort Lin, Yongchuan
collection PubMed
description As a new, high-strength and clean cast iron material, nitrogen-containing gray cast iron has excellent properties and a wide range of application prospects. However, the excellent material properties of the material not only make the machinability challenging, but also the high efficiency and quality of the machining process is a pressing issue. Therefore, it is necessary to study the machining characteristics of nitrogen-containing gray cast iron to obtain the optimal machining parameters to enrich the research work on nitrogen-containing gray cast iron. In this paper, the machining characteristics of nitrogen-containing gray cast iron are systematically studied, and the effects of cutting parameters on milling force, milling temperature, and surface roughness are analyzed. And, based on the machinability assessment, the objective function weights under different production requirements are determined by using hierarchical analysis trade-offs, and an integrated optimization model based on non-dominated ranking genetic algorithm and hierarchical analysis (AHP) is proposed. The model outputs the optimal combination of milling parameters by inputting the cutting speed (vc), feed rate per tooth (fz) and cutting depth (ap), surface roughness and cutting efficiency as the objective functions. The experimental results show that cutting depth has the greatest effect on the cutting force and cutting speed has the greatest effect on the cutting temperature and the surface roughness. The passivation effect of nitrogen on the graphite tip resulted in an increase in both cutting force and cutting temperature. The parameter optimization results indicated that the optimized roughing parameters significantly improve the surface quality while machining efficiently; the optimized finishing parameters improve Ra by 23.53% while ensuring higher MRR, which can achieve efficient and high-quality machining under different production requirements and provide an experimental basis for practical engineering applications of nitrogen-containing gray cast iron.
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spelling pubmed-96919282022-11-26 Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm Lin, Yongchuan Ma, Jiyang Lai, Debin Zhang, Jingru Li, Weizhu Li, Shengzhu He, Shengjian Heliyon Research Article As a new, high-strength and clean cast iron material, nitrogen-containing gray cast iron has excellent properties and a wide range of application prospects. However, the excellent material properties of the material not only make the machinability challenging, but also the high efficiency and quality of the machining process is a pressing issue. Therefore, it is necessary to study the machining characteristics of nitrogen-containing gray cast iron to obtain the optimal machining parameters to enrich the research work on nitrogen-containing gray cast iron. In this paper, the machining characteristics of nitrogen-containing gray cast iron are systematically studied, and the effects of cutting parameters on milling force, milling temperature, and surface roughness are analyzed. And, based on the machinability assessment, the objective function weights under different production requirements are determined by using hierarchical analysis trade-offs, and an integrated optimization model based on non-dominated ranking genetic algorithm and hierarchical analysis (AHP) is proposed. The model outputs the optimal combination of milling parameters by inputting the cutting speed (vc), feed rate per tooth (fz) and cutting depth (ap), surface roughness and cutting efficiency as the objective functions. The experimental results show that cutting depth has the greatest effect on the cutting force and cutting speed has the greatest effect on the cutting temperature and the surface roughness. The passivation effect of nitrogen on the graphite tip resulted in an increase in both cutting force and cutting temperature. The parameter optimization results indicated that the optimized roughing parameters significantly improve the surface quality while machining efficiently; the optimized finishing parameters improve Ra by 23.53% while ensuring higher MRR, which can achieve efficient and high-quality machining under different production requirements and provide an experimental basis for practical engineering applications of nitrogen-containing gray cast iron. Elsevier 2022-11-17 /pmc/articles/PMC9691928/ /pubmed/36439750 http://dx.doi.org/10.1016/j.heliyon.2022.e11629 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Lin, Yongchuan
Ma, Jiyang
Lai, Debin
Zhang, Jingru
Li, Weizhu
Li, Shengzhu
He, Shengjian
Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title_full Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title_fullStr Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title_full_unstemmed Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title_short Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
title_sort multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691928/
https://www.ncbi.nlm.nih.gov/pubmed/36439750
http://dx.doi.org/10.1016/j.heliyon.2022.e11629
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