Experimental investigation and optimization of cobalt bonded tungsten carbide composite by hybrid AHP-TOPSIS approach

The present study is intended to investigate the influence of process parameters like pulse on time, pulse off time, pulse current and voltage on the performance aspects like material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) of cobalt bonded tungsten carbide work-piece in...

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Bibliographic Details
Main Authors: Rahul Nadda, Raj Kumar, Tej Singh, Ranchan Chauhan, Amar Patnaik, Brijesh Gangil
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:Alexandria Engineering Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016818301364
Description
Summary:The present study is intended to investigate the influence of process parameters like pulse on time, pulse off time, pulse current and voltage on the performance aspects like material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) of cobalt bonded tungsten carbide work-piece in an electrical discharge machining (EDM) with graphite and copper electrodes. Experimental investigation reveals that higher MRR (4.0125 mm3/min) and lower TWR (0.00012 gm/min) and SR (2.28 µm) is achieved with graphite electrode as compared with copper electrode where highest MRR and lowest TWR and SR achieved as 0.0615 mm3/min, 0.00026 gm/min and 2.58 µm respectively. The optimum setting of process parameters so as to improve the machining performance was determined using hybrid analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) based multi criteria decision making (MCDM) approach. From this approach, an optimum set of process parameters is: pulse on time = 90 µs, pulse off time = 63 µs, pulse current = 12A and voltage = 50 V for graphite electrode. The proposed hybrid AHP-TOPSIS methodology is also compared with other MCDM methods reported in the literature so as to proof the viability of the present method. Keywords: EDM, Material removal rate, Tool wear rate, Surface roughness, Optimization
ISSN:1110-0168