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Machinability model and multi-response optimisation of process parameters through regression and utility concept

Author

Listed:
  • Ashok Kumar Sahoo
  • Amlana Panda
  • Bijaya Bijeta Nayak
  • Ramanuj Kumar
  • Rabin Kumar Das
  • Ramesh Kumar Nayak

Abstract

Over the years, it is essential to produce appropriate dimensions with quality parts for the use in various automotive components. This paper presents modelling and multi-optimisation exploration on the hard part turning of EN 24 grade steel at 48 HRC with coated carbide multilayer inserts for three roughness factors (Ra, Rz, and Rt). Taguchi L16 orthogonal design with three input parameters and three quality characteristics output was applied to suitably model the process requirements. The second model provides a high coefficient of determination (R2 = 0.98 for Ra, 0.97 for Rz and 0.95 for Rt respectively) compared with the linear model that demonstrates high significance. The ideal parametric setting for different multiple quality features was found to be the depth of cut (0.4 mm), feed rate (0.04 mm/rev) and cutting speed (200 m/min) respectively. The multi-responses optimisation has been simultaneously performed using Taguchi method and the utility concept.

Suggested Citation

  • Ashok Kumar Sahoo & Amlana Panda & Bijaya Bijeta Nayak & Ramanuj Kumar & Rabin Kumar Das & Ramesh Kumar Nayak, 2021. "Machinability model and multi-response optimisation of process parameters through regression and utility concept," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 11(3), pages 390-414.
    • Handle: RePEc:ids:ijpmbe:v:11:y:2021:i:3:p:390-414
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