An experimental analysis and optimization of machining rate and surface characteristics in WEDM of Monel-400 using RSM and desirability approach

Kumar, Vinod; Kumar, Vikas; Jangra, Kamal Kumar

doi:10.1007/s40092-015-0103-0

Cited by 45 publications

(22 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Scanning electron microscopy revealed that the multi-channel electrodes produce better surfaces than single-channel electrodes for both aerospace alloys. Kumar et al (2015) and Sharma et al (2015) also worked on optimization of process parameters using response surface methodology and desirability function. Some of the previous works used the Taguchi method and response surface methodology as tools for the design of experiment in various areas including machining operations (Sharma et al 2013a, b;Khanna and Singh 2013;Gupta et al 2012;Garg et al 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

et al. 2015

View full text Add to dashboard Cite

Electric discharge drill machine (EDDM) is a spark erosion process to produce micro-holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the electric discharge drilling machine, it is very necessary to study the process parameters of machine tool. In this research paper, a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as tool wear rate (TWR). The best parameters such as pulse on-time, pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better TWR in drilling of Al-7075. A plan of experiments, based on L 27 Taguchi design method, was selected for drilling of material. Analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on TWR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off-time gives maximum MRR.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

et al. 2015

View full text Add to dashboard Cite

show abstract

“…The outcomes revealed that the WEDM responses were influenced by the POT, POFT, and CA, respectively. Additionally, the R a , one of the most important indicators of the surface integrity was optimized in conjunction with other factors, including the cutting speed (CS) [8], wire wear ratio (WWR) [9], kerf width (KW) [10][11][12], and material removal rate (MRR) [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the effects of the varied conditions on machining responses for different WEDM operations have been performed. Different optimization techniques, such as the RSM [1,2,4,[6][7][8][9]13], Taguchi [3,14], grey relation analysis (GRA) [15], and hybrid approach [9,10,12] were utilized to resolve the optimizing issues. However, the published works regarding optimization in the WEDM performances have still the limitations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experiments and optimization for the WEDM process: A trade-off analysis between surface quality and production rate

et al. 2020

View full text Add to dashboard Cite

This work addressed a parameter optimization to simultaneously decrease the root mean square roughness (Rq) as well as the thickness of the white layer (TW) and improve the material removal rate (MRR) for the wire electro-discharge machining (WEDM) of a stainless steel 304 (SS304). The factors considered are the discharge current (C), the gap voltage (VO), the pulse on time (POT), and the wire drum speed (SP). The interpolative radius basic function (RBF) is applied to show the correlation between the varied factors and WEDM performances measured. The optimal selection is chosen using the multi-objective particle swarm optimization (MOPSO). Moreover, a traditional one using the response surface method (RSM) and desirability approach (DA) is adopted to compare the working efficiency of two optimization techniques. The results showed that the optimal findings of the C, POT, VO, and SP are 5.0 A, 1.0 µs, 61.0 V, and 8.0 m/min, respectively. The values of the Rq and TW are decreased by approximately 33.33% and 23.53%, respectively, while the MRR enhances 47.42% at the optimal selection, as compared to the common values used. The BRF-MOPSO can provide better performance than the RSM-DA.

show abstract

“…J Ind Eng Int. https ://doi.org/10.1007/s4009 2-018-0264-8), desirability function (Kumar et al 2015), for finding out the optimal process parameter values. Researchers are now focusing on employment of artificial intelligence (AI) techniques, viz.…”

Section: Introductionmentioning

confidence: 99%

Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach

2018

View full text Add to dashboard Cite

Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the modeling and optimization study on dimensional deviations of square-shaped microgroove in laser micromachining of aluminum oxide (Al 2 O 3) ceramic material with pulsed Nd:YAG laser by considering the air pressure, lamp current, pulse frequency, pulse width and cutting speed as process parameters. Thirty-two sets of laser microgrooving trials based on central composite design (CCD) design of experiments (DOEs) are performed, and response surface method (RSM), artificial neural network (ANN) and genetic algorithm (GA) are subsequently applied for mathematical modeling and multi-response optimization. The performance of the predictive ANN model based on 5-8-8-3 architecture gave the minimum error (MSE = 0.000099) and presented highly promising to confidence with percentage error less than 3% in comparison with experimental result data set. The ANN model combined with GA leads to minimum deviation of upper width, lower width and depth value of − 0.0278 mm, 0.0102 mm and − 0.0308 mm, respectively, corresponding to optimum laser microgrooving process parameters such as 1.2 kgf/cm 2 of air pressure, 19.5 Amp of lamp current, 4 kHz of pulse frequency, 6% of pulse width and 24 mm/s of cutting speed. Finally, the results have been verified by performing a confirmatory test.

show abstract

An experimental analysis and optimization of machining rate and surface characteristics in WEDM of Monel-400 using RSM and desirability approach

Cited by 45 publications

References 26 publications

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

Experiments and optimization for the WEDM process: A trade-off analysis between surface quality and production rate

Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach

Contact Info

Product

Resources

About