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A PARAMETRIC EXPERIMENTAL DESIGN STUDY OF ABRASIVE
WATER JET MACHINING
M. BHENGRA, R. DAVIS, R. LAKRA, A. DUNGDUNG & A. BAKHLA
Department of Mechanical Engineering, S.S.E.T, S.H.I.A.T.S, Allahabad, India
ABSTRACT
In this research work, Grey Relational Analysis was selected to determine the optimal combination of various
input parameters of Abrasive Water Jet. A L9 orthogonal array was employed to study the performance characteristics of
cutting operation on Al-6061. With the help of Grey Relational Analysis we were able to obtain optimal combination of
process parameters for maximum Material Removal Rate (MRR) and minimum Surface Roughness (R
a
).
KEYWORDS: Abrasive Water Jet, Grey Relational Analysis, MRR, Orthogonal Array, Surface Roughness
INTRODUCTION
In Abrasive Water Jet, a narrow stream of water carrying abrasive particles, under controlled conditions, is
impinged on work piece. The material is removed from the work piece due to small fracture created by the abrasive
particles. Abrasive Jet Machining is used for drilling, deburring, etching, and cleaning of hard and brittle metals, alloys,
and non-metallic materials. To achieve optimal machining performance the machining parameters should be chosen
properly.
Grey Relational analysis is a part of Grey Theory established by Dr. Deng in 1989. Grey relational analyses
provide an efficient and valid conclusion to an experiment or model which has incomplete information by establishing a
relationship between two discrete sequences. This purpose of this paper is to use Grey relational analysis to obtain optimal
combination of machining parameter for maximum material removal rate (MRR) and minimum surface roughness (SR)
and to find the individual effect of each machining parameter on material removal rate and surface roughness.
EXPERIMENTAL DETAILS
Material
In the present study, Al 6061 was used as work piece material. Al 6061 possesses high toughness and hardness. Al
6061 founds its application in aerospace components, marine fittings etc.
Design of Experiment
Design of Experiment is a systematic approach to solve engineering problems that applies principles and
techniques of data collection stage so as to generate the best combinations of factors by establishing a relationship between
factors affecting a process and the output of the process. In this study, three control variable were used namely, pressure,
nozzle distance and disk flow rate. In machining parameter design, three level machining parameters were selected, shown
in table 2.1.
International Journal of Mechanical
Engineering (IJME)
ISSN(P): 2319-2240; ISSN(E): 2319-2259
Vol. 5, Issue 4, Jun - Jul 2016; 1-8
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