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

Author:

Eaki M.,Kadirgama K.,Ramasamy Devarajan,Wan harun Wan Sharuzi,El Hossein Khaled Abou,Samylingam L.,Kok C.K.

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.

Publisher

Universiti Malaysia Pahang Publishing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3