Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology

Mir, M.; Wani, M.

Growing Science » International Journal of Industrial Engineering Computations » Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print) Quarterly Publication Volume 9 Issue 1 pp. 63-74 , 2018

Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology Pages 63-74 Download PDF

Authors: M. Junaid Mir, M. F. Wani

DOI: 10.5267/j.ijiec.2017.4.004

Keywords: Cutting parameters, Tool wear, Surface roughness, RSM, ANOVA, Desirability function

Abstract: The present work deals with some machinability studies on tool wear and surface roughness, in finish hard turning of AISI D2 steel using PCBN, Mixed ceramic and coated carbide inserts. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters viz., cutting speed, cutting time and tool hardness on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA).The relationship(s) between input variables and the response parameters are determined using a quadratic regression model. The results show that the tool wear was influenced principally by the cutting time and in the second level by the cutting tool hardness. On the other hand, cutting time was the dominant factor affecting workpiece surface roughness followed by cutting speed. Finally, the multiple response optimizations of tool wear and surface roughness were carried out using the desirability function approach (DFA).

How to cite this paper

 Mir, M & Wani, M. (2018). Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology.International Journal of Industrial Engineering Computations , 9(1), 63-74.

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