Empirical modelling of machining parameters for turning operations using multi-objective Taguchi method

Authors

  • A. Saha

DOI:

https://doi.org/10.15282/ijame.14.3.2017.5.0352

Keywords:

ANOVA; Taguchi method; optimisation; regression analysis; Turning.

Abstract

This paper presents an effective approach for the optimisation of process parameters in the turning operation for machining ASTM A36 Mild Steel bar with multi-performance characteristics using multi-objective Taguchi method. Based on Taguchi orthogonal array, 27 experimental runs were performed to identify the optimal level of process parameters. The multiple performance characteristics including power consumption, surface roughness and frequency of tool vibration were the quality variables considered for the optimisation. An input-output inprocess parameter relationship model was developed using regression analysis for the power consumption, surface roughness and frequency of tool vibration. The optimum combination of machining parameters and their levels for the optimum multi-performance characteristics of the turning process was A1B1C1 (i.e. speed: 160 r.p.m, feed rate: 0.08 mm/rev and depth-of-cut: 0.1 mm). This study will be very useful to shop floor engineers in deciding the levels of the turning parameters for optimal performance characteristics.

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Published

2022-12-09

How to Cite

[1]
A. Saha, “Empirical modelling of machining parameters for turning operations using multi-objective Taguchi method”, Int. J. Automot. Mech. Eng., vol. 14, no. 3, pp. 4448–4461, Dec. 2022.

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Articles