WEDM of Mg/CRT/BN composites: Effect of materials and machining parameters

Gopal, P.; Prakash, K. Soorya; Jayaraj, S.

doi:10.1080/10426914.2017.1279316

Cited by 57 publications

(23 citation statements)

References 20 publications

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“…29 It has been found that the recent studies are oriented toward the investigation of the machinability prospects of differently reinforced hybrid MMCs . [30][31][32][33] Despite the availability of the broad range of research activities in the themed research, the two existing research gaps are as follows:…”

Section: Introductionmentioning

confidence: 99%

Investigating the influence of WEDM process parameters in machining of hybrid aluminum composites

Kumar

Grover

Manna

et al. 2020

Advanced Composites Letters

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This article presents an experimental investigation to assess the influence of input process parameters of machinability of wire electrical discharge machining (WEDM) process for machining of triple-reinforced silicon carbide, graphite, and iron oxide hybrid aluminum (Al-6061) metal matrix composites. The composite work specimens, developed using stir casting process, have been processed through WEDM process by adopting a statistically controlled design of experimentation approach. Furthermore, analysis of variance and regression analysis have been performed to understand the influence of the input process parameters on material removal rate (MRR) and spark gap (SG) width. The statistical analysis highlighted the improvements in MRR and SG by 33.72% and −27.28%, respectively, upon adopting the suggested optimized range of input process parameters. Further, the morphology of the machined composite surfaces has also been studied using scanning electron microscopy and energy dispersive spectroscopy to report the phenomenon of formation of recast layer.

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Section: Introductionmentioning

confidence: 99%

Investigating the influence of WEDM process parameters in machining of hybrid aluminum composites

Kumar

Grover

Manna

et al. 2020

Advanced Composites Letters

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“…Furthermore, Taguchi technique is the most commonly used optimization/modelling technique while only 3% research works are reported for modelling with ANFIS [11][12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Wire-EDM of Ballistic Grade Aluminium Alloy

Singh¹,

Misra²,

Upadhyay³

et al. 2018

Int. J. Automot. Mech. Eng.

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Intricacy and complexity of ballistic missile and aerospace parts makes WEDM an essential machining process. The current study aims to formulate an ANFIS model for Wire-EDM of ballistic grade aluminium alloy. The experimentation has been conducted with four input variables namely pulse on time (T on), pulse off time (T off), peak current (I p), and servo voltage (V s). Material removal rate (MRR) is employed as process performance evaluator. The values predicted by the developed model are found closer to experimental outcome and thus ensures the model suitability for prediction purpose and intelligent manufacturing. Machined surfaces are also examined by the scanning electron microscope (SEM) to obtain better insight of the process.

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“…Taguchi-based orthogonal array manner is used to formulate the experimental diagram for WEDM considering reinforcement degree and size, spark on time (Ton), spark off time (Toff) and wire feed (Wf) as processing parameters. ANOVA results divulge that Ton and wt% of reinforcement has more impact on Ra and MRR [9]. Authors showed that the values calculated from the mathematical model of Ra and MRR values were comparable to that of experimental results.…”

Section: Introductionmentioning

confidence: 70%

“…The MLRM equation for samples 1 and 2 are given in Equations (8) and (9). The value of surface roughness obtained using MLRM equation both before and after implementation of AIS algorithm is compared with experimental value along with their absolute percentage error (APE) for samples 1 and 2 MMCs shown in Figures 6 and 7.…”

Section: Resultsmentioning

confidence: 99%

WEDM of Cu/WC/SiC composites: development and machining parameters using artificial immune system

Meenakshi¹,

Suresh²

2019

Journal of Experimental Nanoscience

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A systematic read on evaluating the machining characteristics of wire cut electrical discharge machining (WEDM) using analysis of variance (ANOVA) and multilinear regression model based multi objective optimization is provided during this analysis article. The current work explores, the surface roughness of copper metal matrix composite (MMCs) is minimized by optimizing the process parameters like spark on time, spark off time, peak current and wire feed. Taguchi's L9 orthogonal array has been used to conduct the experiments for two samples having a different composition to measure the surface roughness. The order of significance of parameters on surface roughness (Ra) for sample 1 and 2 MMCs were found using ANOVA and a multilinear regression model (MLRM) was developed to predict the Ra value. The new contribution in the present work is that, the coefficients of MLRM were optimized using artificial immune system algorithm with the objective of minimizing the mean absolute percentage error. Finally, the optimum process parameters were obtained to minimize the surface roughness and reported that the reduced value of Ra for 2.5% and 5% WC Copper MMCs were 0.9 lm and 1.1 lm, respectively later which were established by confirmation experiments.

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WEDM of Mg/CRT/BN composites: Effect of materials and machining parameters

Cited by 57 publications

References 20 publications

Investigating the influence of WEDM process parameters in machining of hybrid aluminum composites

Investigating the influence of WEDM process parameters in machining of hybrid aluminum composites

An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Wire-EDM of Ballistic Grade Aluminium Alloy

WEDM of Cu/WC/SiC composites: development and machining parameters using artificial immune system

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