A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel

Sahoo, A.; Mishra, P.

Growing Science » International Journal of Industrial Engineering Computations » A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print) Quarterly Publication Volume 5 Issue 3 pp. 407-416 , 2014

A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel Pages 407-416 Download PDF

Authors: Ashok Kumar Sahoo, Purna Chandra Mishra

DOI: 10.5267/j.ijiec.2014.4.002

Keywords: Coated carbide, Cutting temperature, Desirability approach, Hard turning, Response surface methodology

Abstract: This paper presents an experimental investigation on cutting temperature during hard turning of EN 24 steel (50 HRC) using TiN coated carbide insert under dry environment. The prediction model is developed using response surface methodology and optimization of process parameter is performed by desirability approach. A stiff rise in cutting temperature is noticed when feed and cutting speed are elevated. The effect of depth of cut on cutting temperature is not that much significant compared with cutting speed and feed as observed from main effects plot. The response surface second order model presented high correlation coefficient (R2 = 0.992) explaining 99.2 % of the variability in the cutting temperature which indicates the goodness of fit for the model to the actual data and high statistical significance of the model. The experimental and predicted values are very close to each other. The calculated error for cutting temperature lies between 1.88-3.19 % during confirmation trial. Therefore, the developed second order model correlates the relationship of the cutting temperature with the process parameters with good degree of approximation. The optimal combination for process parameter is depth of cut at 0.2mm, feed of 0.1597 mm/rev and cutting speed of 70m/min. Based on these combination, the value of cutting temperature is 302.950C whose desirability is one.

How to cite this paper

 Sahoo, A & Mishra, P. (2014). A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel.International Journal of Industrial Engineering Computations , 5(3), 407-416.

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