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Optimization of Machining Parameters During Dry Cutting of Ti6Al4V Using Taguchi’s Orthogonal Array

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Emerging Trends in Mechanical Engineering

Abstract

The present study assessed the effect of control parameter, i.e. approach angle (A), cutting speed (B), depth of cut (C) and feed (D) on the response characteristics, i.e. material removal rate (MRR) and surface roughness (SR) during machining of titanium alloy using Taguchi technique. Experimental trials were performed on the lathe machine using the L9 orthogonal array. Statistical analysis carried out to know the contribution and effect of cutting parameters on response characteristics. From the analysis, it was found that the feed (D) was the most influential factor followed by approach angle (A) which affects the surface roughness (SR) while cutting speed (B) had a most significant effect on the material removal rate (MRR). Subsequently, an optimal control parameter was obtained and modelled for response characteristics.

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References

  1. Avuncan G (1998) Machining economy and cutting tools. Makine Takim Endustrisi Ltd. Publication, Istanbul, pp 375–403

    Google Scholar 

  2. Groover MP (2010) Fundamentals of modern manufacturing: materials, processes, and systems. Wiley, Danvers, MA

    Google Scholar 

  3. Kumar P, Misra JP (2019) Modelling of tool wear for Ti64 turning operation. Mater Sci Forum 969:750–755. https://doi.org/10.4028/www.scientific.net/MSF.969.750

    Article  Google Scholar 

  4. Abhang LB, Hameedullah M (2012) Determination of optimum parameters for multi-performance characteristics in turning by using grey relational analysis. The Int J Adv Manuf Technol 63(1–4):13–24. https://doi.org/10.1007/s00170-011-3857-6

    Article  Google Scholar 

  5. Pawan K, Misra JP (2018) A surface roughness predictive model for DSS longitudinal turning operation. DAAAM International Scientific Book, Chapter 25, pp 285–296

    Google Scholar 

  6. Xie J, Luo MJ, Wu KK, Yang LF, Li DH (2013) Experimental study on cutting temperature and cutting force in dry turning of titanium alloy using a non-coated micro-grooved tool. Int J Mach Tools Manuf 73:25–36. https://doi.org/10.1016/j.ijmachtools.2013.05.006

    Article  Google Scholar 

  7. Boujelbene M (2018) Investigation and modeling of the tangential cutting force of the Titanium alloy Ti–6Al–4V in the orthogonal turning process. Procedia Manufacturing, Maharashtra, India, pp 571–577

    Article  Google Scholar 

  8. Bai J, Bai Q, Tong Z (2018) Experimental and multiscale numerical investigation of wear mechanism and cutting performance of polycrystalline diamond tools in micro-end milling of titanium alloy Ti–6Al–4V. Int J Refract Metals Hard Mater 74:40–51. https://doi.org/10.1016/j.ijrmhm.2018.03.007

    Article  Google Scholar 

  9. Khan A, K Maity (2018) Influence of cutting speed and cooling method on the machinability of commercially pure titanium (CP-Ti) grade II. J Manuf Process 31:650–661. https://doi.org/10.1016/j.jmapro.2017.12.021

    Article  Google Scholar 

  10. Montgomery DC, Runger GC (2010) Applied statistics and probability for engineers. Wiley

    Google Scholar 

  11. Montgomery DC (2017) Design and analysis of experiments. Wiley

    Google Scholar 

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Correspondence to P. Kumar .

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Kumar, P., Misra, J.P. (2020). Optimization of Machining Parameters During Dry Cutting of Ti6Al4V Using Taguchi’s Orthogonal Array. In: Vijayaraghavan, L., Reddy, K., Jameel Basha, S. (eds) Emerging Trends in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-32-9931-3_23

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  • DOI: https://doi.org/10.1007/978-981-32-9931-3_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9930-6

  • Online ISBN: 978-981-32-9931-3

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