考虑刀具使用时间标准的圆刀片冷却参数的优化建模

Juan Manuel Bello Bermejo , Berk Saatçi , Daniel Johansson , Sören Hägglund , Jan-Eric Ståhl , Christina Windmark
{"title":"考虑刀具使用时间标准的圆刀片冷却参数的优化建模","authors":"Juan Manuel Bello Bermejo ,&nbsp;Berk Saatçi ,&nbsp;Daniel Johansson ,&nbsp;Sören Hägglund ,&nbsp;Jan-Eric Ståhl ,&nbsp;Christina Windmark","doi":"10.1016/j.procir.2025.02.050","DOIUrl":null,"url":null,"abstract":"<div><div>Optimization of machining processes, such as milling, is essential for industrial efficiency and product quality. To achieve greater efficiency, it is necessary to understand how tools wear down in different conditions in order to anticipate possible undesirable events like sudden breakage or unpredictable degradation. This study focuses on understanding tool wear in dry milling of compacted graphite iron (CGI) EN-GJV-450 using PVD-coated cemented carbide and cBN tools to predict tool life effectively. The research builds on the Colding model, an empirical framework for tool life estimation, by incorporating and comparing two chip thickness concepts in order to optimize the Colding model’s performance, maximum chip thickness (h<sub>max</sub>) and equivalent chip thickness (h<sub>e</sub>). Through systematic experimentation and modelling, this work has identified optimal conditions for tool life prediction, with h<sub>max</sub> offering a potentially resource-efficient cross-validation alternative aligned with sustainability goals. The results demonstrate that the optimized Colding model effectively predicts tool life for both coated cemented carbide and cBN cutting tools with round geometry in dry milling of CGI. The insights gained further enhance our understanding of the milling process and provide a solid foundation for selecting appropriate machining parameters to extend tool life and improve process efficiency.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"133 ","pages":"Pages 286-291"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal modelling of Colding parameters for round inserts with respect to tool use-time criteria\",\"authors\":\"Juan Manuel Bello Bermejo ,&nbsp;Berk Saatçi ,&nbsp;Daniel Johansson ,&nbsp;Sören Hägglund ,&nbsp;Jan-Eric Ståhl ,&nbsp;Christina Windmark\",\"doi\":\"10.1016/j.procir.2025.02.050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Optimization of machining processes, such as milling, is essential for industrial efficiency and product quality. To achieve greater efficiency, it is necessary to understand how tools wear down in different conditions in order to anticipate possible undesirable events like sudden breakage or unpredictable degradation. This study focuses on understanding tool wear in dry milling of compacted graphite iron (CGI) EN-GJV-450 using PVD-coated cemented carbide and cBN tools to predict tool life effectively. The research builds on the Colding model, an empirical framework for tool life estimation, by incorporating and comparing two chip thickness concepts in order to optimize the Colding model’s performance, maximum chip thickness (h<sub>max</sub>) and equivalent chip thickness (h<sub>e</sub>). Through systematic experimentation and modelling, this work has identified optimal conditions for tool life prediction, with h<sub>max</sub> offering a potentially resource-efficient cross-validation alternative aligned with sustainability goals. The results demonstrate that the optimized Colding model effectively predicts tool life for both coated cemented carbide and cBN cutting tools with round geometry in dry milling of CGI. The insights gained further enhance our understanding of the milling process and provide a solid foundation for selecting appropriate machining parameters to extend tool life and improve process efficiency.</div></div>\",\"PeriodicalId\":20535,\"journal\":{\"name\":\"Procedia CIRP\",\"volume\":\"133 \",\"pages\":\"Pages 286-291\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Procedia CIRP\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212827125001507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia CIRP","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212827125001507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

加工工艺的优化,如铣削,对工业效率和产品质量至关重要。为了获得更高的效率,有必要了解工具在不同条件下是如何磨损的,以便预测可能出现的不良事件,如突然断裂或不可预测的退化。本研究的重点是了解使用pvd涂层硬质合金和cBN刀具干磨致密石墨铁(CGI) EN-GJV-450的刀具磨损情况,以有效预测刀具寿命。本研究以刀具寿命估算的经验框架Colding模型为基础,结合并比较了最大切屑厚度(hmax)和等效切屑厚度(he)这两个切屑厚度概念,以优化Colding模型的性能。通过系统的实验和建模,这项工作已经确定了刀具寿命预测的最佳条件,hmax提供了一种符合可持续发展目标的潜在资源高效交叉验证替代方案。结果表明,优化后的冷却模型可以有效地预测CGI干铣削中涂层硬质合金和cBN刀具的刀具寿命。所获得的见解进一步增强了我们对铣削过程的理解,并为选择适当的加工参数以延长刀具寿命和提高加工效率提供了坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal modelling of Colding parameters for round inserts with respect to tool use-time criteria
Optimization of machining processes, such as milling, is essential for industrial efficiency and product quality. To achieve greater efficiency, it is necessary to understand how tools wear down in different conditions in order to anticipate possible undesirable events like sudden breakage or unpredictable degradation. This study focuses on understanding tool wear in dry milling of compacted graphite iron (CGI) EN-GJV-450 using PVD-coated cemented carbide and cBN tools to predict tool life effectively. The research builds on the Colding model, an empirical framework for tool life estimation, by incorporating and comparing two chip thickness concepts in order to optimize the Colding model’s performance, maximum chip thickness (hmax) and equivalent chip thickness (he). Through systematic experimentation and modelling, this work has identified optimal conditions for tool life prediction, with hmax offering a potentially resource-efficient cross-validation alternative aligned with sustainability goals. The results demonstrate that the optimized Colding model effectively predicts tool life for both coated cemented carbide and cBN cutting tools with round geometry in dry milling of CGI. The insights gained further enhance our understanding of the milling process and provide a solid foundation for selecting appropriate machining parameters to extend tool life and improve process efficiency.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.80
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信