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An Integrated Fuzzy-MOORA Method for the Selection of Optimal Parametric Combination in Turing of Commercially Pure Titanium

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Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

This chapter explores the application of a hybrid approach namely multi-objective optimization based on ratio analysis (MOORA) in fuzzy context to obtain the best parametric combination during machining of commercially pure titanium (CP-Ti) Grade 2 with uncoated carbide inserts in dry cutting environment. A series of experiment was performed by adopting Taguchi based L27 orthogonal array. Cutting speed, feed rate, and depth of cut were selected as three process variables whereas cutting force, surface roughness and flank wear were selected as three major quality attributes to be minimized. The minimization was exploited using fuzzy embedded MOORA method and hence an optimal parametric combination was attained. The results of the investigation clearly revealed that, the fuzzy coupled with MOORA method, was capable enough in acquiring the best parametric setting during turning operation under specified cutting conditions.

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References

  1. Budinski KG (1991) Tribological properties of titanium alloys. Wear 151(2):203–217

    Article  Google Scholar 

  2. Palraj S, Venkatachari G (2008) Effect of biofouling on corrosion behaviour of grade 2 titanium in Mandapam seawaters. Desalination 230(1):92–99

    Article  Google Scholar 

  3. Zitter H, Plenk H (1987) The electrochemical behavior of metallic implant materials as an indicator of their biocompatibility. J Biomed Mater Res 21(7):881–896

    Article  Google Scholar 

  4. Lautenschlager EP, Monaghan P (1993) Titanium and titanium alloys as dental materials. Int Dent J 43(3):245–253

    Google Scholar 

  5. Aziz-Kerrzo M, Conroy KG, Fenelon AM, Farrell ST, Breslin CB (2001) Electrochemical studies on the stability and corrosion resistance of titanium-based implant materials. Biomaterials 22(12):1531–1539

    Article  Google Scholar 

  6. Ezugwu EO, Wang ZM (1998) Titanium alloys and their machinability—a review. J Mater Process Technol 68:262–274

    Article  Google Scholar 

  7. Ezugwu EO, Bonney J, Yamane Y (2000) An overview of the machinability of aero-engine alloys. J Mater Process Technol 134:233–253

    Article  Google Scholar 

  8. Narutaki N, Murakhoshi A (1983) Study on machining of titanium alloys. CIRP Ann Manuf Technol 32(1):65–69

    Article  Google Scholar 

  9. Jawaid A, Che-Haron C, Abdullah A (1999) Tool wear characteristics in turning of titanium alloy Ti-6246. J Mater Process Technol 92:329–334

    Article  Google Scholar 

  10. Leyens C, Peters M (2003) Titanium and titanium alloys. Wiley Online Library

    Google Scholar 

  11. Settineri L et al (2014) An evaluative approach to correlate machinability, microstructures, and material properties of gamma titanium aluminides. CIRP Ann Manuf Technol 63(1):57–60

    Article  Google Scholar 

  12. Lalwani D, Mehta N, Jain P (2008) Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel. J Mater Process Technol 206(1):167–179

    Article  Google Scholar 

  13. Aouici H et al (2012) Analysis of surface roughness and cutting force components in hard turning with CBN tool: prediction model and cutting conditions optimization. Measurement 45(3):344–353

    Article  Google Scholar 

  14. Asiltürk I, Neşeli S (2012) Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis. Measurement 45(4):785–794

    Article  Google Scholar 

  15. Hashmi KH et al (2016) Optimization of process parameters for high speed machining of Ti-6Al-4 V using response surface methodology. Int J Adv Manuf Technol 85(5–8):1847–1856

    Article  Google Scholar 

  16. Tebassi H et al (2017) On the modeling of surface roughness and cutting force when turning of Inconel 718 using artificial neural network and response surface methodology: accuracy and benefit. Period Polytech Mech Eng 61(1):1

    Article  Google Scholar 

  17. Chandrasekaran M, Muralidhar M, Krishna CM, Dixit U (2010) Application of soft computing techniques in machining performance prediction and optimization: a literature review. Int J Adv Manuf Technol 46(5–8):445–464

    Article  Google Scholar 

  18. Abburi N, Dixit U (2006) A knowledge-based system for the prediction of surface roughness in turning process. Robot Comput Integr Manuf 22(4):363–372

    Article  Google Scholar 

  19. Basheer AC, Dabade UA, Joshi SS, Bhanuprasad V, Gadre V (2008) Modeling of surface roughness in precision machining of metal matrix composites using ANN. J Mater Process Technol 197(1):439–444

    Article  Google Scholar 

  20. Mathonsi T, Laubscher RF, Gupta K (2018) Investigation on high speed machining of titanium grade 2 under MQL conditions. In: Proceedings of 16th international conference on manufacturing research 2018, Skovde (Sweden), Advances in manufacturing technology XXXII, pp 69–74. IOS Press

    Google Scholar 

  21. Miller T, Gupta K, Laubscher RF (2018) An experimental study on MQL assisted high speed machining of NiTi shape memory alloy. In: Proceedings of 16th international conference on manufacturing research 2018, Skovde (Sweden), Advances in manufacturing technology XXXII, pp 80–85. IOS Press

    Google Scholar 

  22. Mathonsi T, Laubscher RF, Gupta K (2018) On machinability of titanium grade 4 under minimum quantity lubrication assisted high speed machining. In: Conference of the South African Advanced Materials Initiative (CoSAAMI-2018). IOP conference series: materials science and engineering, vol 430, p 012013

    Article  Google Scholar 

  23. Gupta K, Laubscher RF (2016) MQL assisted machining of grade-4 titanium. In: Proceedings of international conference on competitive manufacturing (COMA), Stellenbosch (South Africa), pp 211–217, 27–29 Jan 2016

    Google Scholar 

  24. Singaravel B, Selvaraj T (2015) Optimization of machining parameters in turning operation using combined TOPSIS and AHP method. Tehnicki Vjesnik 22(6):1475–1480

    Google Scholar 

  25. Sofuoglu MA, Orak S (2017) A novel hybrid multi criteria decision making model: application to turning operations. Int J Intell Syst Appl Eng 5(3):124–131

    Article  Google Scholar 

  26. Khan A, Maity K. Selection of optimal machining parameters in turning of CP-Ti grade 2 using a hybrid optimization technique

    Google Scholar 

  27. Khan A, Maity K (2016) Parametric optimization of some non-conventional machining processes using MOORA method. Int J Eng Res Afr 20:19–40. Trans Tech Publications

    Article  Google Scholar 

  28. Khan A, Maity K (2017) Application of MCDM-based TOPSIS method for the selection of optimal process parameter in turning of pure titanium. Benchmark Int J 24(7):2009–2021

    Article  Google Scholar 

  29. Khan A, Maity K (2018) Application potential of combined fuzzy-TOPSIS approach in minimization of surface roughness, cutting force and tool wear during machining of CP-Ti grade II. Soft Comput, 1–12

    Google Scholar 

  30. Zadeh L (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kurnool, 518002, Andhra Pradesh, India

    Akhtar Khan

  2. Department of Mechanical Engineering, National Institute of Technology Rourkela, Rourkela, 769008, Odisha, India

    Kalipada Maity

  3. Department of Mechanical Engineering, G. H. Raisoni College of Engineering Nagpur, Nagpur, 440016, Maharashtra, India

    Durwesh Jhodkar

Authors
  1. Akhtar Khan
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  2. Kalipada Maity
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  3. Durwesh Jhodkar
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Correspondence to Akhtar Khan .

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Editors and Affiliations

  1. Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Doornfontein, Johannesburg, South Africa

    Kapil Gupta

  2. Assistant Professor, University Center for Research and Development, Chandigarh University, Gharuan, Mohali, India

    Munish Kumar Gupta

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Khan, A., Maity, K., Jhodkar, D. (2020). An Integrated Fuzzy-MOORA Method for the Selection of Optimal Parametric Combination in Turing of Commercially Pure Titanium. In: Gupta, K., Gupta, M. (eds) Optimization of Manufacturing Processes. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-030-19638-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-19638-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19637-0

  • Online ISBN: 978-3-030-19638-7

  • eBook Packages: EngineeringEngineering (R0)

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