The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II

Zhang, Guojun; Zhang, Zhen; Ming, Wuyi; Guo, Jianwen; Huang, Yu; Shao, Xinyu

doi:10.1007/s00170-013-5427-6

Cited by 59 publications

(17 citation statements)

References 23 publications

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“…RSM technique is a useful method to handle this problem, and more details about RSM can be learned from references [11,15].…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

“…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%

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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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“…RSM technique is a useful method to handle this problem, and more details about RSM can be learned from references [11,15].…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

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

View full text Add to dashboard Cite

show abstract

“…To map the whole Pareto optimal frontier, the optimization procedure often should be repeated many times, which is a time-consuming process [18]. Evolutionary algorithms have been recognized to be well suited to multiobjective optimization, for example, one of the most efficient and commonly used versions of multi-objective GA (NSGA-II) can handle large and complex constraints by natural-inspired operators, and the NSGA-II algorithm has low computational complexity and good convergence by applying effective elite strategy than the previous evolutionary algorithms [15]; it has been successfully applied in solving many complex engineering optimization problems and achieved remarkable results [19][20][21][22][23][24][25][26]. First of all, NSGA-II is selected to solve the multi-objective optimization model for oil-gas production process, and then, in order to further improve the diversity and convergence of Pareto optimal solutions obtained by NSGA-II algorithm when solving the complicated and constrained optimization problems, an improved NSGA-II algorithm (I-NSGA-II) is proposed in this paper.…”

Section: Multi-objective Optimization For Oil-gas Production Process mentioning

confidence: 99%

Multi-objective optimization method using an improved NSGA-II algorithm for oil–gas production process

Tan

Gao

Wang

2015

Journal of the Taiwan Institute of Chemical Engineers

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“…It can obtain the true Pareto-optimal solutions by the elitepreserving compared to NSGA. And it is widely used to obtain the set of Pareto-optimal solutions to handle constrained multi-objective optimization problems [19]. So, this work adopts the NSGA-II algorithm to solve the multi-objective optimization problem.…”

Section: Definitionmentioning

confidence: 99%

Multi-objective optimization method of precision forging process parameters to control the forming quality

Zhu

Wang

Lv³

2015

Int J Adv Manuf Technol

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To control the precision forging product forming quality, a multi-objective optimization method for process parameters design was proposed by applying Latin hypercube design method and response surface model approach. Meanwhile, the deformation homogeneity and material damage of forging product was first presented for evaluating the forming quality. Then, as a case of study, the radial precision forging for a hollow shaft with variable cross section and wall thickness was carried out. The 3D rigid-plastic finite element (FE) model of the radial precision forging was established. The parameters on the forming quality evaluation function study were discussed to investigate the multi-objective optimization model. Non-dominated sorting genetic algorithm-II (NSGA-II) was adopted to obtain the Pareto-optimal solutions. A compromise solution was selected from the Pareto solutions by using the mapping method. Experiments with the same parameter settings were compared with the simulations. After conducting radial forging and mechanical property experimental study on the forging product by multi-objective optimization process parameters, the feasibility of the multiobjective optimization method for the precision forging product forming quality was verified.

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The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II

Cited by 59 publications

References 23 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

Multi-objective optimization method using an improved NSGA-II algorithm for oil–gas production process

Multi-objective optimization method of precision forging process parameters to control the forming quality

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