Skip to main content
Log in

Multi-criteria decision making in the selection of machining parameters for Inconel 718

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

Taguchi’s methods and design of experiments are invariably used and adopted as quality improvement techniques in several manufacturing industries as tools for offline quality control. These methods optimize single-response processes. However, Taguchi’s method is not appropriate for optimizing a multi-response problem. In other situations, multi-responses need to be optimized simultaneously. This paper presents multi-response optimization techniques. A set of non-dominated solutions are obtained using non-sorted genetic algorithm for multi-objective functions. Multi-criteria decision making (MCDM) is proposed in this work for selecting a single solution from nondominated solutions. This paper addresses a new method of MCDM concept based on technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS determines the shortest distance to the positive-ideal solution and the greatest distance from the negative-ideal solution. This work involves the high-speed machining of Inconel 718 using carbide cutting tool with six objective functions that are considered as attributes against the process variables of cutting speed, feed, and depth of cut. The higher-ranked solution is selected as the best solution for the machining of Inconel 718 in its respective environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. N. Narutaki and Y. Yamane, High-speed machining of Inconel 718 with ceramic tools, Ann. CIRP, 42(1) (1993) 103–106.

    Article  Google Scholar 

  2. A. Gatto and L. Iuliano, Advanced coated ceramic tools for machining super alloys, Int. J. Mach. Tools Manufacturing, 37(5) (1997) 591–605.

    Article  Google Scholar 

  3. I. A. Choudhury and M. A. El-Baradie, Machining nickel base super alloys: Inconel 718, Proc. Int Mech Engg (B): J. Eng. Manuf., 212 (1998) 195–206.

    Article  Google Scholar 

  4. E. O. Ezugwu, Z. M. Wang and C. I. Okeke, Tool life and surface integrity when machining Inconel 718 with PVD- and CVD-coated tools, Tribol. Trans., 42(2) (1999) 353–360.

    Article  Google Scholar 

  5. M. Benghersallah, L. Boulanouar, A. Devillez, S. Dominiak and D. Dudzinski, Morpholological investigations in the wear of carbide inserts in milling, International review of Mechanical Engineering, 2/1 (2008) 68–74.

    Google Scholar 

  6. Y. S. Liao and R. H. Shiue, Carbide tool wear mechanism in turning of Inconel 718 with ceramic tools, Wear, 193 (1996) 16–24.

    Article  Google Scholar 

  7. I. PuertasArbizu and C. J. LuisPerez, Surface roughness prediction by factorial design of experiments in turning processes, Journal Materials Processing Technology, 143–144 (2003) 390–396.

    Article  Google Scholar 

  8. A. Jawaid, S. Koksal and S. Sharif, Wear behavior of PVD and CVD coated carbide tools when face milling Inconel 718, Tribol. Trans., 43(2) (2000) 325–331.

    Article  Google Scholar 

  9. J. P. Davim, A note on the determination of optimal cutting conditions for surface finish obtained in turning using design of experiments, Journal Materials Processing Technology, 116 (2001) 305–308.

    Article  Google Scholar 

  10. I. A. Choudhury and M. A. El-Baradie, Machinability of nickel-base super alloys: a general view, Journal Materials Processing Technology, 77 (1998) 278–284.

    Article  Google Scholar 

  11. U. Natarajan, P. R. Periyannan and S. H. Yang, Multi response optimization for micro end milling process using response surface methodology, International journal of advanced manufacturing technology, 56 (2011) 177–185.

    Article  Google Scholar 

  12. M. Kurt, E. Bagei and Y. Kaynak, Application of Taguchi methods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes, International journal of advanced manufacturing technology, 40 (2009) 458–469.

    Article  Google Scholar 

  13. A. Molinari and M. Nouari, Modeling of tool wear by diffusion in metal cutting, Wear, 525 (2002) 135–149.

    Article  Google Scholar 

  14. W. H. Yang and Y. S. Tang, Design optimization of cutting parameters for turning operations based on Taguchi method, Journal of Materials Processing Technology, 84 (1998) 122–129.

    Article  Google Scholar 

  15. Z. Y. Wang et al., Hybrid machining of Inconel 718, International Journal of Machine Tools & Manufacture, 43 (2003) 1391–1396.

    Article  Google Scholar 

  16. M. S. Chua, H. T. Loh, Y. S. Wong and M. Rahman, Optimization of cutting conditions for multi-pass turning operations using sequential quadratic programming, Journal of Materials Processing Technology, 28(1–2) (1991) 253–262.

    Article  Google Scholar 

  17. W. T. Chien and C. S. Tsai, The investigation on the prediction of tool wear and the determination of optimum cutting conditions in machining 17-4PH stainless steel, Journal of Material Processing Technology, 140(1–3) (2003) 340–345.

    Article  Google Scholar 

  18. F. Cus and J. Balic, Optimization of cutting process by GA approach, Robotics and Computer Integrated Manufacturing, 19 (2003) 113–121.

    Article  Google Scholar 

  19. E. Amiolemhen and A. O. A. Ibhadode, Application of genetic algorithms determination of the optimal machining parameters in the conversion of a cylindrical bar stock into a continuous finished profile, International Journal of Machine Tools and Manufacture, 44(12–13) (2004) 1403–1412.

    Article  Google Scholar 

  20. R. Saravanan, P. Asokan and K. Vijayakumar, Machining parameters optimization for turning cylindrical stock into a continuous finished profile using genetic algorithm (GA) and simulated annealing (SA), Int. Journal of Advanced Manufacturing Technology, 119(21) (2003) 817–822.

    Google Scholar 

  21. R. Saravanan, Evolutionary bi-criteria optimum design of robots based on task specifications, Int J Adv Manuf Technol, 41 (2009) 386–406.

    Article  Google Scholar 

  22. M. Dagdeviren, A hybrid multi criteria decision making problem for personnel selection in manufacturing systems, Journal of Intelligent manufacturing, 21 (2010) 451–460.

    Article  Google Scholar 

  23. S. Sun, Assessing computer numerical control machines using data envelopment analysis. Int J Prod Res, 40(9) (2002) 2011–2039.

    Article  MATH  Google Scholar 

  24. I. Mahdavi, A. Heidarzade, B. Sadeghpour-Gildeh and N. Mahdavi-Amiri, A general fuzzy TOPSIS model in multiple criteria decision making, Int J Adv Manuf Technol, 45 (2009) 406–420.

    Article  Google Scholar 

  25. R. Quiza Sardinas, M. Rivas and E. Alfonso, Genetic algorithm-based multi objective optimization of cutting parameters in turning process, Int. J. Eng. Applica. Artificial. Intelligence, 19(2) (2006) 127–133.

    Article  Google Scholar 

  26. R. Venkata Rao, Machinability evaluation of work materials using a combined multiple attribute decision-making method, Int J Adv Manuf Technology, 28 (2006) 221–227.

    Article  Google Scholar 

  27. S. Gara, W. Bouzid, M. Hbaieb, M. Ben and Amar, Cutting speed optimization in high speed turning, International review of Mechanical Engineering, 1/3 (2007) 237–244.

    Google Scholar 

  28. J. L. Rosa, A. Robin, M. B. Silva, C. A. Baldan and M. P. Peres, Electro deposition of copper on titanium wires: Taguchi experimental design approach, J Mater Process Technol, 209 (2009) 1181–1188.

    Article  Google Scholar 

  29. J. Deng, L. Liu, J. Liu, J. Zhao and X. Yang, Failure mechanisms of TiB2 particle and SiC whisker reinforced Al2O3 ceramic cutting tools when machining nickel-based alloys, Int. J.Mach. Tools Manufact, 45(12–13) (2005) 1393–1401.

    Google Scholar 

  30. William Ho, Xiaoweixu and Prasanta K. Dey, MCDM approaches for supplier evaluation and selection: A Literature review, European journal of operational Research, 202(1) (2012) 16–24.

    Article  Google Scholar 

  31. Ounnar and Pujo, Pull control for job shop: Holonic manufacturing system approach using multi criteria decision making, Journal of Intellignet manufacturing, 23(1) (2012) 141–153.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. Thirumalai.

Additional information

Recommended by Associate Editor Jihong Hwang

R. Thirumalai received his ME degree in Manufacturing Technology from the National Institute of Technology, Trichy (NITT). He is currently pursuing PhD studies in Mechanical Engineering. Currently, he is an Associate Professor of the Mechanical Engineering Department, SNS College of Technology, Coimbatore. His areas of interests include machining, multicriteria decision making, design of experiments, and optimizations techniques.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thirumalai, R., Senthilkumaar, J.S. Multi-criteria decision making in the selection of machining parameters for Inconel 718. J Mech Sci Technol 27, 1109–1116 (2013). https://doi.org/10.1007/s12206-013-0215-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-013-0215-7

Keywords

Navigation