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Empirical modeling and multi-response optimization of duplex turning for Ni-718 alloy

Author

Listed:
  • Sunil Kumar

    (Babu Banarasi Das University)

  • Ravindra Nath Yadav

    (BBD National Institute of Technology and Management)

  • Raghuvir Kumar

    (BN College of Engineering and Technology)

Abstract

In duplex turning, two-cutting tools as primary-tool is mounted on main tool post and secondary-tool is mounted on indigenous tool post on lathe machine. The objective of present work is to optimize the duplex turning parameters for primary cutting force, secondary cutting force and surface roughness for aerospace material especially Nickel alloy (Ni-718). For this, Taguchi methodology (TM) with response surface methodology (RSM) is utilized for modeling as well as multi-objective optimization of parameters. Firstly, the TM approach has been applied to determine the central value using experimental data, which is used as central value for RSM modeling. The results show that significant improvement in the all responses at optimal data with acceptable limit of errors. It also shows the percentage decrease in primary cutting force = 9.06%, secondary cutting force = 30.91% with improvement in average surface roughness = 1.78% positively.

Suggested Citation

  • Sunil Kumar & Ravindra Nath Yadav & Raghuvir Kumar, 2020. "Empirical modeling and multi-response optimization of duplex turning for Ni-718 alloy," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 126-139, February.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:1:d:10.1007_s13198-019-00931-5
    DOI: 10.1007/s13198-019-00931-5
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    References listed on IDEAS

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    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Mandeep Chahal & Vikram Singh & Rohit Garg, 2017. "Optimum surface roughness evaluation of dies steel H-11 with CNC milling using RSM with desirability function," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 432-444, June.
    3. Shofique U. Ahmed & Rajesh Arora, 2019. "Quality characteristics optimization in CNC end milling of A36 K02600 using Taguchi’s approach coupled with artificial neural network and genetic algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 676-695, August.
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