Investigating the electrical discharge machining (EDM) parameter effects on Al-Mg2Si metal matrix composite (MMC) for high material removal rate (MRR) and less EWR–RSM approach

Hourmand, Mehdi; Farahany, Saeed; Sarhan, Ahmed A.D.; Noordin, M.Y.

doi:10.1007/s00170-014-6491-2

Cited by 103 publications

(41 citation statements)

References 23 publications

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“…Step 5: Under the food distribution principle of wolf pack, the position of lead wolf is updated. Then, the renewing positions of the p worst wolves in wolf pack are calculated according to equation (7) x id = x min + rand 3 x max À x min ð7Þ…”

Section: Gpr For Predictionmentioning

confidence: 99%

Integrated optimization model in wire electric discharge machining using Gaussian process regression and wolf pack algorithm approach while machining SiCp/Al composite

Ming

et al. 2018

Advances in Mechanical Engineering

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To further improve prediction accuracy and optimization quality of wire electrical discharge machining of SiCp/Al composite, trim cuts were performed using Taguchi experiment method to investigate the influence of cutting parameters, such as pulse duration (T on), pulse interval (T off), water pressure (W p), and wire tension (W t)), on material removal rate and three-dimensional surface characteristics (S q and S a). An optimization model to predict material removal rate and surface quality was developed using a novel hybrid Gaussian process regression and wolf pack algorithm approach based on experiment results. Compared with linear regression model and back propagation neural network, the availability of Gaussian process regression is confirmed by experimental data. Results show that the worst average predictive error of five independent tests for material removal rate, S q , and S a are not more than 10.66%, 19.85%, and 22.4%, respectively. The proposed method in this article is an effective method to optimize the process parameters for guiding the actual wire electrical discharge machining process.

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Section: Gpr For Predictionmentioning

confidence: 99%

Integrated optimization model in wire electric discharge machining using Gaussian process regression and wolf pack algorithm approach while machining SiCp/Al composite

Ming

et al. 2018

Advances in Mechanical Engineering

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“…Therefore, many kinds of the stranger aluminum alloys phases were invented to overcome these weaknesses. Some investigations on the machining of metal matrix composites have been reported [2][3][4][5][6][7][8][9][10]. Interpenetrating double metal phase composite is a kind of metal matrix composite which is enhanced by network structure reinforced.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on Turning of Double Metal Composite with Network Interpenetrating Structure

Qiao

Ning

et al. 2015

Materials and Manufacturing Processes

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The interpenetrating double metal phase composite is anisotropic. According to the structural and mechanical properties, the cutting process becomes more complicated. In this work, experimental investigation was systematically studied by means of turning experiments, and focused on cutting force and surface roughness; extra attention has been paid to the cutting phenomena in the zone of reinforcing phase and bimetal interface. Cutting force performance is similar to the ordinary materials, but there are several impact forces in cutting process. In addition, it is easy to produce cracks and exfoliations at metal/metal interface. These phenomena will lead to the decline of the machined surface quality.

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“…They illustrated the effect of input variables on MRR, EWR and microstructure changes. Conclusion was made that current and pulse on time is the most significant factors on MRR [3]. S. Gopalakannan et.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Electrical Discharge Machining Process Parameters using SCM420 low alloy steel by Response Surface Methodology

Morankar¹,

Shelke²

2017

IOSR JMCE

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Investigating the electrical discharge machining (EDM) parameter effects on Al-Mg2Si metal matrix composite (MMC) for high material removal rate (MRR) and less EWR–RSM approach

Cited by 103 publications

References 23 publications

Integrated optimization model in wire electric discharge machining using Gaussian process regression and wolf pack algorithm approach while machining SiCp/Al composite

Integrated optimization model in wire electric discharge machining using Gaussian process regression and wolf pack algorithm approach while machining SiCp/Al composite

Experimental Investigation on Turning of Double Metal Composite with Network Interpenetrating Structure

Optimization of Electrical Discharge Machining Process Parameters using SCM420 low alloy steel by Response Surface Methodology

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