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

Abstract 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.

[1]  Shailesh Dewangan,et al.  Study of surface integrity and dimensional accuracy in EDM using Fuzzy TOPSIS and sensitivity analysis , 2015 .

[2]  Mahdi Bitarafan,et al.  Evaluating the connecting members of cold-formed steel structures in reconstruction of earthquake-prone areas in Iran using the AHP methods , 2013 .

[3]  Tej Singh,et al.  Hybrid entropy – TOPSIS approach for energy performance prioritization in a rectangular channel employing impinging air jets , 2017 .

[4]  Stephen T. Newman,et al.  State of the art electrical discharge machining (EDM) , 2003 .

[5]  Edmundas Kazimieras Zavadskas,et al.  Evaluating construction projects of hotels based on environmental sustainability with MCDM framework , 2017 .

[6]  Fu-Chen Chen,et al.  Multi-objective optimisation of high-speed electrical discharge machining process using a Taguchi fuzzy-based approach , 2007 .

[7]  R. Purohit,et al.  Mathematical modeling of electric discharge machining of cast Al-4Cu-6Si alloy-10wt.% SiCp composites , 2007 .

[8]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[9]  B. Yan,et al.  The effect in EDM of a dielectric of a urea solution in water on modifying the surface of titanium , 2005 .

[10]  Peter,et al.  Analytical hierarchy processes (AHP) for the selection of solvents in early stages of pharmaceutical process development , 2011 .

[11]  B. C. Routara,et al.  Multi-objective parametric optimization of nano powder mixed electrical discharge machining of AlSiCp using response surface methodology and particle swarm optimization , 2017, Alexandria Engineering Journal.

[12]  Asha B. Chelani,et al.  Optimal selection of full scale tannery effluent treatment alternative using integrated AHP and GRA approach , 2011, Expert Syst. Appl..

[13]  S. Mahapatra,et al.  A hybrid approach for multi-response optimization of non-conventional machining on AlSiCp MMC , 2013 .

[14]  Tej Singh,et al.  Optimization of tribo-performance of brake friction materials: Effect of nano filler , 2015 .

[15]  Akbar Esfahanipour,et al.  Decision making in stock trading: An application of PROMETHEE , 2007, Eur. J. Oper. Res..

[16]  D. K. Tripathy,et al.  Multi-attribute optimization of machining process parameters in powder mixed electro-discharge machining using TOPSIS and grey relational analysis , 2016 .

[17]  I. Puertas,et al.  EDM machinability and surface roughness analysis of TiB2 using copper electrodes , 2017 .

[18]  Andrzej Piegat,et al.  Comparative analysis of MCDM methods for the assessment of mortality in patients with acute coronary syndrome , 2016, Artificial Intelligence Review.

[19]  H. Hocheng,et al.  Preliminary study of material removal in electrical-discharge machining of SiC/Al , 1997 .

[20]  Prasanta Sahoo,et al.  Optimization of Surface Roughness and MRR in EDM Using WPCA , 2013 .

[21]  C. Sathiya Narayanan,et al.  Optimization of EDM process parameters in machining Si3N4–TiN conductive ceramic composites to improve form and orientation tolerances , 2016 .

[22]  T. Muthuramalingam,et al.  A review on influence of electrical process parameters in EDM process , 2015 .

[23]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[24]  Ming Zhou,et al.  High-speed EDM milling with moving electric arcs , 2009 .

[25]  Tej Singh,et al.  Selection of brake friction materials using hybrid analytical hierarchy process and vise Kriterijumska Optimizacija Kompromisno Resenje approach , 2018 .

[26]  R. Karthikeyan,et al.  Mathematical modelling for electric discharge machining of aluminium–silicon carbide particulate composites , 1999 .

[27]  Johan Springael,et al.  PROMETHEE and AHP: The design of operational synergies in multicriteria analysis.: Strengthening PROMETHEE with ideas of AHP , 2004, Eur. J. Oper. Res..

[28]  Bijan Sarkar,et al.  Eclectic decision for the selection of tree borne oil (TBO) as alternative fuel for internal combustion engine. , 2015 .

[29]  M. Uthayakumar,et al.  Electrical Discharge Machining of Al(6351)–SiC–B4C Hybrid Composite , 2014 .

[30]  Mohan Kumar Pradhan,et al.  Estimating the effect of process parameters on surface integrity of EDMed AISI D2 tool steel by response surface methodology coupled with grey relational analysis , 2013 .

[31]  S. P. Sivapirakasam,et al.  Multi-attribute decision making for green electrical discharge machining , 2011, Expert Syst. Appl..