Enhancing Machining performance in Stainless Steel Machining using MXene Coolant: A Detailed Examination

IF 1 Q4 ENGINEERING, MECHANICAL
M. Eaki, K. Kadirgama, D. Ramasamy, W. S. Wan harun, Khaled Abou El Hossein, L. Samylingam, C.K. Kok
{"title":"Enhancing Machining performance in Stainless Steel Machining using MXene Coolant: A Detailed Examination","authors":"M. Eaki, K. Kadirgama, D. Ramasamy, W. S. Wan harun, Khaled Abou El Hossein, L. Samylingam, C.K. Kok","doi":"10.15282/ijame.21.1.2024.04.0850","DOIUrl":null,"url":null,"abstract":"Metal cutting, a complex process in manufacturing, involves various factors that significantly affect the quality of the final product. Notably, the turning process is crucial, with outcomes that heavily depend on multiple machining parameters. These parameters encompass speed, depth of cut, feed rate, the type of coolant used (specifically, high heat transfer MXene coolant), and insert types, among others. The material of the workpiece is also a critical factor in the metal-cutting operation. This study focuses on achieving optimal surface quality and minimizing cutting forces in the turning process. It recognizes the substantial impact of numerous process parameters, directly or indirectly affecting the product's surface roughness and cutting forces. Understanding these optimal parameters can lower machining costs and improve product quality. Our research concentrates on turning a stainless-steel alloy workpiece using a carbide insert tool. We employ the Response Surface Method (RSM) to optimize cutting parameters within a set range of cutting speed (100, 125, 150 m/min), feed rate (0.1, 0.2, 0.3 mm/rev), and depth of cut (0.4, 0.8, 1.2 mm). Additionally, we use various tool geometries and the RSM design of experiments to enhance and analyze the multi-response parameters of surface roughness and tool life. Optimal machining parameters for MXene-NFC involve a cutting speed of 140 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 0.5 mm. These settings ensure minimal surface roughness, maximum tool life, and the greatest total length of cut, achieving a composite desirability of 0.695.","PeriodicalId":13935,"journal":{"name":"International Journal of Automotive and Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Automotive and Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15282/ijame.21.1.2024.04.0850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Metal cutting, a complex process in manufacturing, involves various factors that significantly affect the quality of the final product. Notably, the turning process is crucial, with outcomes that heavily depend on multiple machining parameters. These parameters encompass speed, depth of cut, feed rate, the type of coolant used (specifically, high heat transfer MXene coolant), and insert types, among others. The material of the workpiece is also a critical factor in the metal-cutting operation. This study focuses on achieving optimal surface quality and minimizing cutting forces in the turning process. It recognizes the substantial impact of numerous process parameters, directly or indirectly affecting the product's surface roughness and cutting forces. Understanding these optimal parameters can lower machining costs and improve product quality. Our research concentrates on turning a stainless-steel alloy workpiece using a carbide insert tool. We employ the Response Surface Method (RSM) to optimize cutting parameters within a set range of cutting speed (100, 125, 150 m/min), feed rate (0.1, 0.2, 0.3 mm/rev), and depth of cut (0.4, 0.8, 1.2 mm). Additionally, we use various tool geometries and the RSM design of experiments to enhance and analyze the multi-response parameters of surface roughness and tool life. Optimal machining parameters for MXene-NFC involve a cutting speed of 140 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 0.5 mm. These settings ensure minimal surface roughness, maximum tool life, and the greatest total length of cut, achieving a composite desirability of 0.695.
使用 MXene 冷却液提高不锈钢加工性能:详细研究
金属切削是一种复杂的制造工艺,涉及各种因素,对最终产品的质量有重大影响。其中,车削工艺至关重要,其结果在很大程度上取决于多个加工参数。这些参数包括速度、切削深度、进给速度、使用的冷却液类型(特别是高传热 MXene 冷却液)和刀片类型等。工件材料也是金属切削操作中的一个关键因素。本研究的重点是在车削过程中实现最佳表面质量和最小切削力。它认识到众多工艺参数的重大影响,这些参数直接或间接地影响产品的表面粗糙度和切削力。了解这些最佳参数可以降低加工成本,提高产品质量。我们的研究集中于使用硬质合金刀片车削不锈钢合金工件。我们采用响应面法(RSM)在设定的切削速度(100、125、150 米/分钟)、进给量(0.1、0.2、0.3 毫米/转)和切削深度(0.4、0.8、1.2 毫米)范围内优化切削参数。此外,我们还使用各种刀具几何形状和 RSM 实验设计来增强和分析表面粗糙度和刀具寿命的多响应参数。MXene-NFC 的最佳加工参数包括 140 m/min 的切削速度、0.05 mm/rev 的进给量和 0.5 mm 的切削深度。这些设置可确保最小的表面粗糙度、最长的刀具寿命和最长的总切削长度,实现 0.695 的复合理想度。
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 求助全文
来源期刊
CiteScore
2.40
自引率
10.00%
发文量
43
审稿时长
20 weeks
期刊介绍: The IJAME provides the forum for high-quality research communications and addresses all aspects of original experimental information based on theory and their applications. This journal welcomes all contributions from those who wish to report on new developments in automotive and mechanical engineering fields within the following scopes. -Engine/Emission Technology Automobile Body and Safety- Vehicle Dynamics- Automotive Electronics- Alternative Energy- Energy Conversion- Fuels and Lubricants - Combustion and Reacting Flows- New and Renewable Energy Technologies- Automotive Electrical Systems- Automotive Materials- Automotive Transmission- Automotive Pollution and Control- Vehicle Maintenance- Intelligent Vehicle/Transportation Systems- Fuel Cell, Hybrid, Electrical Vehicle and Other Fields of Automotive Engineering- Engineering Management /TQM- Heat and Mass Transfer- Fluid and Thermal Engineering- CAE/FEA/CAD/CFD- Engineering Mechanics- Modeling and Simulation- Metallurgy/ Materials Engineering- Applied Mechanics- Thermodynamics- Agricultural Machinery and Equipment- Mechatronics- Automatic Control- Multidisciplinary design and optimization - Fluid Mechanics and Dynamics- Thermal-Fluids Machinery- Experimental and Computational Mechanics - Measurement and Instrumentation- HVAC- Manufacturing Systems- Materials Processing- Noise and Vibration- Composite and Polymer Materials- Biomechanical Engineering- Fatigue and Fracture Mechanics- Machine Components design- Gas Turbine- Power Plant Engineering- Artificial Intelligent/Neural Network- Robotic Systems- Solar Energy- Powder Metallurgy and Metal Ceramics- Discrete Systems- Non-linear Analysis- Structural Analysis- Tribology- Engineering Materials- Mechanical Systems and Technology- Pneumatic and Hydraulic Systems - Failure Analysis- Any other related topics.
×
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