Utilizing Multi-Criteria Decision-Making for Selecting the Optimal Cutting Fluid in the Turning Process under Various Operating Conditions
Keywords:
Turning, Cutting Fluid, Cutting Force Measurement, Surface Roughness, Instrumentation and Experimentation, Cutting ParameterAbstract
With the rapid advancement of computer-aided engineering tools, design methodologies have undergone significant transformation, particularly in the areas of computational design and optimization. This study focuses on selecting the most suitable cutting fluid for turning operations based on key machining parameters such as feed force, cutting force, radial force, and surface roughness. Multi-criteria decision-making techniques, specifically TOPSIS and VIKOR, are used to analyze and rank different cutting fluids. Parametric modeling is carried out using MS Excel, allowing for efficient evaluation by adjusting input variables without manual calculations. The experimental work involves machining mild steel using a single-point High-Speed Steel (HSS) cutting tool under varying cutting speeds, feed rates, and eco-friendly cutting fluids. The results are presented through graphical analysis to identify the most effective cutting fluid under specific conditions. Additionally, the study investigates the influence of coolant flow, spindle speed, feed, depth of cut, and cutting force on surface finish. Recognizing the critical role of cutting fluid in machining performance, this research proposes an optimization model to manufacturers in selecting the most appropriate cutting fluid for improved turning process outcomes
Downloads
References
M.K. Vijaya Prabhu, P. Ponnusamy, and J. Senthil Kumar, Performance of various cutting fluids by estimating surface roughness of mild steel in turning, International Journal of Engineering Research and Technology (IJERT), no. 2, 2013, pp. 2278–0181.
W. Bouzid, Cutting parameter optimization to minimize production time in high speed turning, Journal of Materials Processing Technology, vol. 161, no. 3, pp. 388–395.
E. Kuram, B. Ozcelik, E. Demirbas, and E. Sik, Effects of the cutting fluid types and cutting parameters on surface roughness and thrust force, Proceedings of the World Congress on Engineering, vol. 2, 2010, pp. 978–988.
M. Nalbant, G. Gokkaya, and S. Gure, Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning, Materials & Design, vol. 28, no. 4, pp. 1379–1385.
T.S. Lan and M.Y. Wang, Competitive parameter optimization of multi-quality CNC turning, The International Journal of Advanced Manufacturing Technology, vol. 41, no. 7, 2009, pp. 820–826.
M.I. Khan and A. Haque Serajul, A Text of Manufacturing Science, Eastern Economy Edition: PHI Learning Private Limited, 2011, pp. 225–319.
D.K. Dwivedi, Study the effect of cutting parameters and heat treatment on machining behavior of spheroidized steel En-31, Journal of the Institution of Engineers (India), Part MC, Mechanical Engineering Division, vol. 82, no. 4, 2002, pp. 157–159.
P.V. Rao and D. Singh, A surface roughness prediction model for hard turning processes, International Journal of Advanced Manufacturing Technology, vol. 29, 2006, pp. 62–68.
G.K. Lal, Introduction to Machining Science, 2nd ed., New Age International (P) Limited, 2005, pp. 40–44.
B.L. Juneja, G.S. Sekhon, and Nitin Seth, Fundamentals of Metal Cutting and Machine Tools, New Age International (P) Limited, 2005, pp. 81–85.
T. Ozel, T.K. Hsu, and E. Zeren, Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel, The International Journal of Advanced Manufacturing Technology, vol. 25, no. 3, 2005, pp. 262–269.
R.F. Avila and A.M. Abrao, The effect of cutting fluids on the machining of hardened AISI 4340 steel, Journal of Materials Processing Technology, vol. 119, no. 1, 2001, pp. 21–26.
A. Rohit, B. Naga Raju, and M. Raja Roy, Optimization of tool temperature and surface roughness in wet and dry conditions during turning of mild steel using response surface method, 2015.
A. Bhattacharya, S. Das, P. Majumder, and A. Batish, 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, Production Engineering, vol. 3, no. 1, 2009, pp. 31–40.
M.A. Xavior and M. Adithan, Determining the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 austenitic stainless steel, Journal of Materials Processing Technology, vol. 209, no. 2, 2009, pp. 900–909.
S. Srikrishan, A.S. Reddy, and S. Vani, A new car selection in the market using TOPSIS technique, International Journal of Engineering Research and General Science, no. 2, 2014.
J.K. Chen and I.S. Chen, VIKOR method for selecting universities for future development based on innovation, Journal of Global Business Issues, vol. 2, no. 1, 2008, pp. 53.
N. Bhushan and K. Rai, Strategic Decision Making: Applying the Analytic Hierarchy Process, Springer Science & Business Media, 2007.
.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
