Modeling and Optimization of Medium-Speed WEDM Process Parameters for Machining SKD11

Zhang, Guojun; Guo, Jianwen; Ming, Wuyi; Li, Mingzhen; Huang, Yu

doi:10.1080/10426914.2013.773024

Cited by 70 publications

(34 citation statements)

References 19 publications

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“…Then, two different methods, namely BPNN-GA and NSGA-II (coded by using Matlab 2014a), are proposed to optimize the process parameters of WEDM for obtaining the optimal surface integrity with minimizing SR,WLT, and SCD, which is the main objective of this research. Moreover, these two approaches have proven their effectiveness because they have been successfully implemented to find out the optimal parameters on material removal rate (MRR) and 3D surface quality of WEDM [11][12][13] or to optimize the process of laser brazing [14]. Finally, the confirmation experiment is conducted to verify the efficiency of these methods applied in optimizing surface integrity characteristics.…”

Section: Outline Of the Workmentioning

confidence: 99%

Optimization of process parameters on surface integrity in wire electrical discharge machining of tungsten tool YG15

Zhang

Ming

Huang

et al. 2015

Int J Adv Manuf Technol

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This study mainly investigates the effect and optimization of process parameters on surface integrity including white layer thickness and crack density in wire electrical discharge machining (WEDM) of tungsten tool YG15 which is one of the most important hardened stainless steel alloys used in the mold industries. In this paper, four input process parameters including pulse-on time, pulse current, water pressure, and feed rate were set during WEDM experiment, and three output characteristics including surface roughness (SR), white layer thickness (WLT), and surface crack density (SCD) were taken as the performance criteria of surface integrity. Then an experiment for central composite design (CCD) of processing the tungsten tool YG15 has been conducted according to response surface methodology (RSM). After analyzing the experimental results and optimizing the WEDM process using two different methods namely backpropagation neural network combined with genetic algorithm (BPNN-GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the optimal solution can be obtained. The analysis results manifest that the pulseon time and pulse current have a significant effect on the SR, WLT, and SCD. Moreover, several confirmation tests were carried out to verify the efficiency of the optimization methods, and then the more appropriate method was demonstrated by the comparison of optimization results. According to analysis and discussion of results, the most suitable process parameter combinations can be obtained to guide the actual machine, which contribute to increase the surface integrity and accuracy of WEDM and simultaneously reduce the ratio of disqualification for industrial application.

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Section: Outline Of the Workmentioning

confidence: 99%

Optimization of process parameters on surface integrity in wire electrical discharge machining of tungsten tool YG15

Zhang

Ming

Huang

et al. 2015

Int J Adv Manuf Technol

Self Cite

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“…SO optimization was applied by Scott et al [2]. Similar work is reported by Liao et al [3], Huang et al [4], Konda et al [5], Puri and Bhattacharyya [6], Manna and Bhattacharyya [7], and Zhang et al [8] to find the best solution which corresponds to minimum or maximum value of individual objectives. This type of optimization usually does not consider the interactions among different objectives.…”

mentioning

confidence: 85%

“…GA is a population-based stochastic search procedure which is closely modeled on the natural process of evolution with emphasis on breeding and the survival of the fittest [31]. In view of many process parameters and randomness in the WEDM process, Zhang et al [8] adopted back-propagation neural network combining with genetic algorithm to optimize MRR and SR individually. With number of output responses, simultaneous optimization becomes difficult when they are conflicting.…”

mentioning

confidence: 99%

Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353

Varun

Venkaiah

2014

Int J Adv Manuf Technol

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Wire electric discharge machining is one of the fastest growing machining processes. In view of the complexity of the process, controlling the machining parameters without compromising on the response parameters is a tedious process. In this paper, a new optimization strategy, by coupling grey relational analysis (GRA) with genetic algorithm (GA), is proposed to simultaneously optimize the response parameters. Experiments were conducted on EN 353 work material to study the effects of various process parameters on the response parameter such as material removal rate (MRR), surface roughness (SR), and cutting width (kerf). Process parameters such as pulse on time, pulse off time, peak current, and servo voltage are considered. ANOVA analysis was carried out to find the parameters affecting the responses with the help of 3D surface plots. A regression model is formed for each response and this model serves as the objective function for GA. In the proposed GRA coupled with GA method, GA is main technique and GRA entropy is used to generate weights systematically. Search is made for optimal solution in a global space. Hence, the obtained solution is not within the conducted experiments alone, it is a global optimal solution in the selected range of process parameter. Pareto surface and contour plots also plotted to help selection of responses based on individual priorities.

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“…Pon was found to be the most contributing factor for both MRR and Ra. Zhang [24] reported that Pon and Poff were the two most influential control factors for Ra, whereas for MRR, Pon and wire feed were found to be the major contributing factors during machining of SKD11 steel. Dhobe [5] studied the effects of different WEDM parameters on Ra while cutting Cryo-treated AISI D2 tool steel.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Effect of Wire Electric Dischage Machining Process Parameters for the Formation of High Speed Steel Form Tool

Ishfaq¹,

Mufti²,

Ahmad³

et al. 2018

Adv. Sci. Technol. Res. J.

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The use of form tools is growing in industry, owing to their inherent advantage of improving productivity. However, the accurate formation of form tool profile is a really tedious task. In this research work, wire electric discharge machining (WEDM) process has been used for the generation of a form tool. Pulse on-time, pulse off-time, servo voltage, wire tension, flushing pressure have been considered as input parameters, whereas tool geometry (clearance angle, included angle), surface roughness and material removal rate are the selected responses. Response surface methodology (RSM) (Box Bhenken experimental design) technique has been used for design of experiments. Analysis of Variance (ANOVA) has shown that pulse on-time and pulse off-time are the two influential control factors for material removal rate (MRR), surface roughness (Ra), clearance angle and included angle. Contour plot analysis has been performed to find out the optimal ranges of the most influential control factors for each response characteristics.

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Modeling and Optimization of Medium-Speed WEDM Process Parameters for Machining SKD11

Cited by 70 publications

References 19 publications

Optimization of process parameters on surface integrity in wire electrical discharge machining of tungsten tool YG15

Optimization of process parameters on surface integrity in wire electrical discharge machining of tungsten tool YG15

Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353

Analysis of the Effect of Wire Electric Dischage Machining Process Parameters for the Formation of High Speed Steel Form Tool

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