Hossain Shazzad, Abedin Mohammad Zoynal, Saha Rotan Kumar, Touhiduzzaman Md, Hossen Md Jakir
Department of Industrial and Production Engineering, Dhaka University of Engineering & Technology, Gazipur, Bangladesh.
Department of Mechanical Engineering, Dhaka University of Engineering & Technology, Gazipur, Bangladesh.
Heliyon. 2024 Dec 12;11(1):e41051. doi: 10.1016/j.heliyon.2024.e41051. eCollection 2025 Jan 15.
This study investigates the optimization of cutting conditions for machining titanium alloy (Ti-6Al-4V) using Response Surface Methodology (RSM), with the goal of minimizing tool-chip interface temperature and surface roughness. The research focuses on key cutting parameters to investigate the most effective combinations for enhancing surface finish and reducing thermal impact during machining. The present study deals with the dry turning of Ti-6Al-4V alloy with carbide alloy inserts in a way to utilize the Analysis of Variance (ANOVA) to develop predictive models for minimum surface roughness and optimum temperature. The findings reveal that both cutting speed and depth of cut are critical in determining machining outcomes. Specifically, a low cutting speed of 88 m/min coupled with a high depth of cut of 0.20 mm was found to elevate the cutting temperature to approximately 835 °C, resulting a surface roughness of 0.59 μm. Conversely, increasing the cutting speed to 120 m/min while reducing the depth of cut to 0.10 mm significantly lowered the temperature to around 607 °C, resulting a surface roughness of 0.19 μm; thus, thereby improving surface finish and reducing thermal stress on the tool. Additionally, a 27 % reduction in cutting temperature and a minimum surface roughness of 0.19 μm were achieved with optimal settings of 120 m/min cutting speed, 0.08 mm/rev feed rate, and 0.10 mm depth of cut. The study demonstrates the effectiveness of RSM in optimizing machining parameters for optimum temperature and better surface finish in the titanium alloy machining.
本研究采用响应面法(RSM)研究钛合金(Ti-6Al-4V)加工切削条件的优化,目标是使刀具-切屑界面温度和表面粗糙度最小化。该研究聚焦于关键切削参数,以探究在加工过程中提高表面光洁度和降低热影响的最有效组合。本研究采用硬质合金刀片对Ti-6Al-4V合金进行干式车削,利用方差分析(ANOVA)建立最小表面粗糙度和最佳温度的预测模型。研究结果表明,切削速度和切削深度对加工结果都至关重要。具体而言,发现88米/分钟的低切削速度与0.20毫米的高切削深度相结合会使切削温度升高至约835℃,表面粗糙度为0.59微米。相反,将切削速度提高到120米/分钟,同时将切削深度降低到0.10毫米,可将温度显著降低至约607℃,表面粗糙度为0.19微米;从而改善了表面光洁度并降低了刀具上的热应力。此外,在切削速度为120米/分钟、进给速度为0.08毫米/转、切削深度为0.10毫米的最佳设置下,切削温度降低了27%,表面粗糙度最小为0.19微米。该研究证明了响应面法在优化钛合金加工参数以实现最佳温度和更好表面光洁度方面的有效性。