Electro-discharge machining of alumina: Investigation of material removal rate and surface roughness

M.Y. Ali; M.A. Moudood; M.A. Maleque; M. Hazza; E. Y. T. Adesta

doi:10.15282/jmes.11.4.2017.5.0271

Authors

M.Y. Ali Department of Manufacturing and Materials Engineering International Islamic University Malaysia, PO Box 10, 50728 Kuala Lumpur, Malaysia
M.A. Moudood Department of Manufacturing and Materials Engineering International Islamic University Malaysia, PO Box 10, 50728 Kuala Lumpur, Malaysia
M.A. Maleque Department of Manufacturing and Materials Engineering International Islamic University Malaysia, PO Box 10, 50728 Kuala Lumpur, Malaysia
M. Hazza Department of Manufacturing and Materials Engineering International Islamic University Malaysia, PO Box 10, 50728 Kuala Lumpur, Malaysia
E. Y. T. Adesta Department of Manufacturing and Materials Engineering International Islamic University Malaysia, PO Box 10, 50728 Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.15282/jmes.11.4.2017.5.0271

Keywords:

Electro-discharge machining; non-conductive ceramic; assisting electrode; response surface methodology; material removal rate; surface roughness.

Abstract

Alumina is a non-conductive ceramic material which can meet the high demand of industrial applications due to its excellent physical and chemical properties. However, machining of alumina is not possible by using the conventional machining methods due to its inherent brittleness. Recently, electro-discharge machining has been used for structuring alumina with assisting electrode to initiate the spark between the conductive tool electrode and the non-conductive work piece material. However, the effects of process parameters on material removal rate and surface roughness have not been investigated to formulate mathematical models. This study dealt with developing models for material removal rate and surface roughness correlating three process parameters which are peak current, pulse-on time and gap voltage using response surface methodology. The models were verified with 7% error between the results of empirical models and the experimental values.

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