Effect of cutting parameters on surface roughness in turning of CPM 10V steel

Anđelko Aleksić, D. Rodić, M. Sekulić, Marin Gostimirović, B. Savković
{"title":"Effect of cutting parameters on surface roughness in turning of CPM 10V steel","authors":"Anđelko Aleksić, D. Rodić, M. Sekulić, Marin Gostimirović, B. Savković","doi":"10.1109/INFOTEH53737.2022.9751329","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to investigate the effect of cutting parameters on surface roughness during turning of CPM 10V steel with a coated cutting tool. Machining of CPM 10V steel and finding a suitable tool is very challenging due to its physical and mechanical properties, especially since the machining of this material has not been extensively researched. The experiments were carried out using an Index GU-600 CNC lathe and the surface roughness Ra was measured in process. A three-factorial three-level experimental design was used for the experiments. Statistical method analysis of variance (ANOVA) is applied to study the effects of cutting speed, feed rate, and depth of cut on surface roughness. The results of this study show that feed rate and the depth of cut have the most significant effect on surface roughness. The developed model can be used in the machining industry to predict and analyze cutting parameters for optimal surface roughness.","PeriodicalId":6839,"journal":{"name":"2022 21st International Symposium INFOTEH-JAHORINA (INFOTEH)","volume":"54 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 21st International Symposium INFOTEH-JAHORINA (INFOTEH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFOTEH53737.2022.9751329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The objective of this paper is to investigate the effect of cutting parameters on surface roughness during turning of CPM 10V steel with a coated cutting tool. Machining of CPM 10V steel and finding a suitable tool is very challenging due to its physical and mechanical properties, especially since the machining of this material has not been extensively researched. The experiments were carried out using an Index GU-600 CNC lathe and the surface roughness Ra was measured in process. A three-factorial three-level experimental design was used for the experiments. Statistical method analysis of variance (ANOVA) is applied to study the effects of cutting speed, feed rate, and depth of cut on surface roughness. The results of this study show that feed rate and the depth of cut have the most significant effect on surface roughness. The developed model can be used in the machining industry to predict and analyze cutting parameters for optimal surface roughness.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
切削参数对cpm10v钢车削表面粗糙度的影响
本文的目的是研究切削参数对CPM 10V钢涂层刀具车削过程中表面粗糙度的影响。由于CPM 10V钢的物理和机械性能,特别是由于这种材料的加工尚未得到广泛的研究,因此加工CPM 10V钢并找到合适的刀具是非常具有挑战性的。实验在u -600型数控车床上进行,并在加工过程中测量了表面粗糙度Ra。试验采用三因子三水平试验设计。采用方差分析的统计方法研究了切削速度、进给速度和切削深度对表面粗糙度的影响。研究结果表明,进给量和切削深度对表面粗糙度的影响最为显著。该模型可用于机械加工行业预测和分析最佳表面粗糙度的切削参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
PV system site selection using PVGIS and Fuzzy AHP Face Mask Detection Based on Machine Learning and Edge Computing Smart Production Systems: Methods and Application Analyzing the Effects of Abnormal Resonance Voltages using Artificial Neural Networks Real-Time Data Processing Techniques for a Scalable Spatial and Temporal Dimension Reduction
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1