Optimizing Micro-Turning Parameters during Step Turning Process on Titanium Alloy with RSM

An attempt was made to evaluate and improve the machining parameters of micro-turning titanium alloy with cermet insert on the titanium alloy’s surface roughness. The experiments were done using a strong statistical tool to construct a matrix by utilizing Response Surface Methodology (RSM) and Box-Behnken design for performing the micro turning. Quadratic model was generated to predict the response and also used to appraise the effect of outcomes. The results of the investigation suggest that the cutting feed as well as speed rate are the input elements that have the greatest impact on surface roughness. Numerical with graphical optimization methods are figured out to seek out the optimum method parameters. The subsequent machining conditions lead to minimum surface roughness on speed 2944 rpm, 7.23 μm/rev feed along with 15 μm depth of cut that helps to attain the great surface quality with minimum machining value and at the same time improves the productivity with 86% of optimum desirability rate.

[1]  R. Suresh,et al.  Parametric Optimization of Cutting Parameters for Micro-Machining of Titanium Grade-12 Alloy Using Statistical Techniques , 2021, International Journal of Lightweight Materials and Manufacture.

[2]  K. Ravi Kumar,et al.  Investigation and optimization of machining through hole by abrasive water jet machining in AA6063/Bagasseash/TiN hybrid composites , 2021, Materials and Manufacturing Processes.

[3]  Huawei Song,et al.  Multiresponse Optimization for Laser-Assisted Machining of Fused Silica Using Response Surface Methodology , 2019, Silicon.

[4]  S Arunkumar,et al.  Optimization of the Machining parameter of LM6 Alminium alloy in CNC Turning using Taguchi method , 2017 .

[5]  K. Ganesan,et al.  Analysis and optimisation of machining parameters in micro turning using RSM , 2015 .

[6]  Satyanarayana Kosaraju,et al.  Optimal machining conditions for turning Ti-6Al-4V using response surface methodology , 2013 .

[7]  N. Muthukrishnan,et al.  Influence of Coolant in Machinability of Titanium Alloy (Ti-6Al-4V) , 2011 .

[8]  R. Balasubramaniam,et al.  Some Preliminary Metallurgical Studies on Grain Size and Density of Work Material used in Micro Turning Operation , 2010 .

[9]  Mehdi Tajdari,et al.  Surface roughness modelling in hard turning operation of AISI 4140 using CBN cutting tool , 2010 .

[10]  H. Onozuka,et al.  Study on orthogonal turning of titanium alloys with different coolant supply strategies , 2009 .

[11]  B. Ramamoorthy,et al.  Machinability investigation of Inconel 718 in high-speed turning , 2009 .

[12]  Anirban Bhattacharya,et al.  Estimating the effect of cutting parameters on surface finish and power consumption during high speed machining of AISI 1045 steel using Taguchi design and ANOVA , 2009, Prod. Eng..

[13]  Viktor P. Astakhov,et al.  Effects of the cutting feed, depth of cut, and workpiece (bore) diameter on the tool wear rate , 2007 .

[14]  Tuğrul Özel,et al.  Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks , 2005 .

[15]  Jeong-ick Lee,et al.  A comparison in a back-bead prediction of gas metal arc welding using multiple regression analysis and artificial neural network , 2000 .

[16]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[17]  Ralf Schweizer,et al.  Metal Cutting Principles , 2016 .

[18]  Teuku Meurah Indra Mahlia,et al.  Effect of cutting parameters on the surface roughness of titanium alloys using end milling process , 2010 .

[19]  B. Sidda Reddy,et al.  Prediction of Surface Roughness in Turning Using Adaptive Neuro-Fuzzy Inference System , 2009 .

[20]  A. Kumar,et al.  FABRICATION OF MINIATURE COMPONENTS USING MICROTURNING , 2003 .

[21]  J. L. C. Salles,et al.  Effects of Machining Parameters on Surface Quality of the Ultra High Molecular Weight Polyethylene (UHMWPE) , 2003 .

[22]  Takahisa Masuzawa,et al.  State of the Art of Micromachining , 2000 .