Experimental modelling and multi-response optimization of travelling wire electrochemical spark machining of Pyrex glass

The present study focuses on experimental modelling of travelling wire electrochemical spark machining process using coupled methodology comprising Taguchi methodology and response surface methodology. Experiments were conducted on Pyrex glass workpiece using L27 orthogonal array considering applied voltage, pulse on-time, pulse off-time, electrolyte concentration and wire feed velocity as input parameters and material removal rate, surface roughness (Ra) and kerf width (Kw) as output parameters. The multi-response optimization is also pe rformed using a coupled analysis comprising grey relational analysis and principal component analysis. The optimal process parameter setting demonstrates the enhancement of material removal rate by 154% and reduction of surface roughness and kerf width by 21% and 11%, respectively, against the initial parameter setting.

[1]  J. A. McGeough,et al.  Evaluation of an Apparatus for Electrochemical Arc Wire-Machining , 1988 .

[2]  C. Chu,et al.  Hybrid micromachining of glass using ECDM and micro grinding , 2013 .

[3]  Abbas Al-Refaie.  Grey-data envelopment analysis approach for solving the multi-response problem in the Taguchi method , 2010 .

[4]  Xiaojun Liu,et al.  Optimal tolerance design for products with correlated characteristics by considering the present worth of quality loss , 2008 .

[5]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[6]  H R Kim,et al.  Using the orthogonal array with grey relational analysis to optimize the laser hybrid welding of a 6061-T6 Al alloy sheet , 2008 .

[7]  N. C. Hwang,et al.  Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling , 2009 .

[9]  W. Peng,et al.  Study of electrochemical discharge machining technology for slicing non-conductive brittle materials , 2004 .

[10]  Amitabha Ghosh,et al.  Mechanism of spark generation during electrochemical discharge machining: a theoretical model and experimental verification , 1996 .

[11]  C-J Tzeng,et al.  Optimization of wire electrical discharge machining of pure tungsten using neural network and response surface methodology , 2011 .

[12]  V. Fascio,et al.  Machining of non-conducting materials using electrochemical discharge phenomenon – An overview , 2005 .

[13]  Kamlakar P Rajurkar,et al.  Experimental Investigations into Traveling Wire Electrochemical Spark Machining (TW-ECSM) of Composites , 1991 .

[14]  H. Tsuchiya,et al.  Wire electro-chemical discharge machining of glasses and ceramics , 1985 .

[15]  Cheng-Kuang Yang,et al.  Improving machining performance of wire electrochemical discharge machining by adding SiC abrasive to electrolyte , 2006 .

[16]  Amit Sharma,et al.  Modelling and optimization of cut quality during pulsed Nd:YAG laser cutting of thin Al-alloy sheet for straight profile , 2012 .

[17]  V. Jain,et al.  Machining piezoelectric (PZT) ceramics using an electrochemical spark machining (ECSM) process , 1996 .

[18]  Raghuvir Kumar,et al.  Modelling and optimisation of electro-discharge diamond face grinding of cemented carbide-cobalt composite , 2012 .

[19]  Vinod Yadava,et al.  Finite element prediction of material removal rate due to traveling wire electrochemical spark machining , 2009 .

[20]  Alakesh Manna,et al.  A study on micro machining of e-glass–fibre–epoxy composite by ECSM process , 2012 .

[21]  B. Bhattacharyya,et al.  Experimental investigations into electrochemical discharge machining (ECDM) of non-conductive ceramic materials , 1999 .

[22]  L. Slătineanu,et al.  Drilling of Difficult-to-Cut Steel by Electrochemical Discharge Machining , 2011 .

[23]  Phillip J. Ross,et al.  Taguchi Techniques For Quality Engineering: Loss Function, Orthogonal Experiments, Parameter And Tolerance Design , 1988 .

[24]  J Chen,et al.  An approach to partner selection in virtual enterprises based on grey relational analysis , 2011 .

[25]  V. Yadava,et al.  Modeling and optimization of laser beam percussion drilling of thin aluminum sheet , 2013 .

[26]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[27]  Bibhuti Bhusan Biswal,et al.  Determination of optimum parameters with multi-performance characteristics in laser drilling—A grey relational analysis approach , 2011 .