Temperature and tool wear effects on the milling process of Ti6Al4V titanium alloy

钛合金 冶金 材料科学 合金 过程(计算) 计算机科学 操作系统
作者
Eshagh Saharkhiz,Kambiz Ghaemi Osgouie,Mohsen Davazdah Emami,Ali Tarokh
标识
DOI:10.1177/09544062251323061
摘要

Titanium and its alloys are difficult to cut due to the high cutting temperatures and stresses near the cutting-edge during machining. The high cutting temperatures are the result of heat generation during machining and the metal’s poor heat conductivity. The high stresses are due to the small contact area and titanium’s strength retention even at elevated temperatures. Predicting and controlling parameters influencing machining temperature is crucial for managing tool wear, reducing production costs, achieving superior surface quality with fewer operations, selecting appropriate fluids, and optimizing material removal rates. This study focuses on simulating milling processes using a finite element analysis with numerical and experimental validation. The results demonstrate a strong correlation between numerical simulations and experimental tests. An investigation of four key process inputs – cutting depth, spindle speed, feed rate, and cutting width– reveals that cutting depth has the most significant impact on machining temperature, while spindle speed has the least. Additionally, predictions of temperatures through polynomial regressions with good R-factors are achieved in designed experiments. The study also examines cooling methods’ impacts on the tool wear in dry, semi-dry (MQL), and compressed air machining techniques experimentally. The results indicate a 70.5% reduction in tool wear using MQL compared to dry methods, with the compressed air achieving a 50.5% decrease relative to dry methods. Ultimately, this research offers valuable insights for minimizing tool wear and heat generation and selecting optimal and effective parameters in the machining of titanium alloys. SEM micrographs reveal that the efficient lubrication provided by the MQL system effectively reduces workpiece material adhesion to the tool’s edge.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
建议保存本图,每天支付宝扫一扫(相册选取)领红包
实时播报
量子星尘发布了新的文献求助10
刚刚
liu关闭了liu文献求助
1秒前
2秒前
可乐鸡翅发布了新的文献求助10
2秒前
一颗蘑古力完成签到 ,获得积分10
2秒前
小马甲应助芋泥采纳,获得10
2秒前
领导范儿应助llyq66698采纳,获得30
3秒前
Z.zz完成签到,获得积分10
4秒前
笨笨的荧荧完成签到 ,获得积分10
4秒前
舒心代柔发布了新的文献求助10
4秒前
can完成签到,获得积分10
5秒前
LLLZX发布了新的文献求助10
6秒前
6秒前
想人陪的飞薇完成签到 ,获得积分10
7秒前
清爽的以晴完成签到 ,获得积分10
8秒前
8秒前
自然的青筠完成签到,获得积分10
9秒前
9秒前
香蕉觅云应助孙天睿采纳,获得10
10秒前
啵啵完成签到,获得积分10
10秒前
闫诺完成签到 ,获得积分10
10秒前
山谷发布了新的文献求助10
10秒前
10秒前
11秒前
陶军辉发布了新的文献求助10
11秒前
13秒前
哆面体完成签到,获得积分10
14秒前
Orange应助咸蛋超人采纳,获得10
15秒前
深情安青应助笑口常开采纳,获得10
17秒前
啵啵发布了新的文献求助30
17秒前
yyds应助kento采纳,获得50
17秒前
dd发布了新的文献求助10
17秒前
19秒前
小米发布了新的文献求助10
20秒前
20秒前
量子星尘发布了新的文献求助10
20秒前
23秒前
zchth123完成签到,获得积分10
23秒前
23秒前
不知终日梦为鱼完成签到,获得积分10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1041
Mentoring for Wellbeing in Schools 1000
Binary Alloy Phase Diagrams, 2nd Edition 600
Atlas of Liver Pathology: A Pattern-Based Approach 500
A Technologist’s Guide to Performing Sleep Studies 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5492938
求助须知:如何正确求助?哪些是违规求助? 4590837
关于积分的说明 14432833
捐赠科研通 4523546
什么是DOI,文献DOI怎么找? 2478402
邀请新用户注册赠送积分活动 1463425
关于科研通互助平台的介绍 1436097