Multiresponse optimization of micro-wire electrical discharge machining process

Kuriachen, Basil; Somashekhar, K. P.; Mathew, Jose

doi:10.1007/s00170-014-6005-2

Cited by 58 publications

(27 citation statements)

References 36 publications

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“…Further, for an increase in current from 2 to 3 A, there is a small increase in kerf width which indicates that the amount of spark energy used in sparking with debris was observed to be high. Analysis of variance (ANOVA) is an objective decisionmaking tool based on a statistical method for noticing any differences in the average performance of groups of items tested [24,25]. Here, the ANOVA is utilized to examine which machining parameter significantly affects the performance characteristic of wire-cut EDM of duplex stainless steel.…”

Section: S/n Ratio Calculation For Kerfmentioning

confidence: 99%

“…Optimization techniques such as design of experiments [9], response surface methodology [10][11][12], fuzzy control system [13][14][15][16][17], genetic algorithm [18] and grey relational analysis [19] are the inevitable tool in achieving optimum process parameters of the wire EDM process. A similar kind of evaluation has also been performed by many researchers on various materials like Inconel [20,21], AISI D2 [22,23], titanium and titanium super alloys [24][25][26][27], etc. Based on the evaluation of those research papers on wire EDM, it has been seen that different attempts are made on the investigations of predicting the effect of process parameters on various conductive materials for achieving maximum material removal rate (MRR), minimum surface roughness (Ra) and wire wear ratio (WWR) on wire EDM and they were found useful.…”

Section: Introductionmentioning

confidence: 99%

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Experimental investigation and prediction of optimum process parameters of micro-wire-cut EDM of 2205 DSS

Rajmohan¹,

Kumar²

2016

Int J Adv Manuf Technol

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Micro-wire-cut electrode discharge machining (EDM) is an emerging manufacturing process in the field of micro-manufacturing to fabricate the complex profiles of micro-components. It is a complex process involving various process parameters such as pulse on time, pulse off time, wire speed, wire tension and current. In addition to micro-fabrication, this process can also be extended in the field of tool design and developments such as dies, moulds, precision manufacturing, contour cutting, etc., where complex shapes need to be generated with high-grade dimensional accuracy and surface finish. In this research work, an attempt is made to investigate the effect of process parameters on the output variables such as material removal rate (MRR), surface finish and the cutting width (kerf) of wire-cut EDM for duplex stainless steel (DSS). Scanning electron microscopy (SEM) has been used to capture the images of the kerf width, and the measurements are taken with the help of the welding expert system and software. An optimization technique (Taguchi method) has been employed to identify the optimum parameters of the micro-wire-cut EDM process for cutting 2205 grade duplex stainless steel. The effect of each control parameter on the performance measure is studied individually using the plots of signal to noise ratio.

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Section: S/n Ratio Calculation For Kerfmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental investigation and prediction of optimum process parameters of micro-wire-cut EDM of 2205 DSS

Rajmohan¹,

Kumar²

2016

Int J Adv Manuf Technol

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“…Besides, legitimate flushing may not be conceivable if the working crevice turns out to be too little, which thusly diminishes the MRR. As the release current builds, the interim between the beats likewise expands which lessens the power force after an ideal level [18]. The plot which is checks the presumption of ordinariness.…”

Section: Analysis Of Mrrmentioning

confidence: 61%

Experimental Investigation and Multi Response Optimization of WEDM Process of AA7075 Metal Matrix Composites Using Particle Swarm Optimization

Ramanan¹,

John²

2017

IJIES

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Abstract:Wire electric discharge machining (WEDM) has turned out to be one of the well-known machining procedures utilized in bringing up elaborate aspects on electrically conductive substances. To improve the performance of WEDM process an attempt was made to improve the material removal rate (MRR) and minimize surface roughness (SR) on AA7075-activated carbon composites. The machined surface integrity associated with MRR and SR have been analysed as a function of processing parameters, such as discharge current, pulse on time, pulse off time and servo speed rate. Analysis of variance (ANOVA) is carried out in the idea of identifying tremendous causes of parameters. Experimental outcome authorize the feasibility of proposed prediction strategy and the developed particle swarm optimization (PSO) algorithm. Experiment result indicates that the MRR and SR are more sensitive to a change in size than a change in volume fraction of reinforcement. AA7075-activated carbon composites have extensive applications in aerospace and marine sectors.

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“…Several attempts had been made to study and optimize the process parameters of micro-WEDM process using techniques such as GA, SA, artificial neural networks, and fuzzy logic (Yusup et al 2012;Rao and Kalyankar 2014;Yan and Fang 2008;Vijayaraj and Gowri 2010;Somashekhar et al 2012a, b;Sivaprakasam et al 2013;Kuriachen et al 2015;Kovacevic et al 2014). Now, the multiobjective optimization problem for micro-WEDM is solved using NSTLBO algorithm.…”

Section: Optimization Of Process Parameters Of Micro-wire-electric DImentioning

confidence: 99%

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

Rao

2015

Teaching Learning Based Optimization Algorithm

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Multiobjective optimization aspects of a traditional machining process namely surface grinding and five modern machining processes namely, wire-electro discharge machining process, micro-wire-electric discharge machining process, laser cutting process, electrochemical machining process, and electrochemical discharge machining process are presented in this chapter. A posteriori multiobjective optimization algorithm named as nondominated sorting teaching-learning-based optimization (NSTLBO) algorithm is proposed to solve the multiobjective optimization problems of the machining processes. A Pareto optimal set of solutions along with a Pareto front is presented for each of the considered machining processes.

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Multiresponse optimization of micro-wire electrical discharge machining process

Cited by 58 publications

References 36 publications

Experimental investigation and prediction of optimum process parameters of micro-wire-cut EDM of 2205 DSS

Experimental investigation and prediction of optimum process parameters of micro-wire-cut EDM of 2205 DSS

Experimental Investigation and Multi Response Optimization of WEDM Process of AA7075 Metal Matrix Composites Using Particle Swarm Optimization

Multiobjective Optimization of Machining Processes Using NSTLBO Algorithm

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