Optimization of Machining Parameters for Corner Accuracy Improvement for WEDM Processing

Wang, Shih-Ming; Wu, Jiaxuan; Gunawan, Hariyanto; Tu, Ren-Qi

doi:10.3390/app122010324

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…Although a higher R-square value can make the model more accurate, there may be some independent variables (X) that are not related to the dependent variable (Y), and, therefore, will not improve the model fit and prediction accuracy. Consequently, most scholars prefer to use the adjusted R-square to avoid poor predictions by the regression model [32]. Furthermore, analysis of variance (ANOVA) and the significance test (F test, t-test) of the regression model were conducted.…”

Section: Experiments Condition and Equipmentmentioning

confidence: 99%

“…If the machining depth is set to the initial depth of cut (h0) during the EDM process, the finished workpiece cavity depth is shorter (h1) due to the electrode wear in front-end face (h), as shown in Figure 4. Therefore, an additional height, Metals 2023, 13, x FOR PEER REVIEW accurate, there may be some independent variables (X) that are not related to the dep ent variable (Y), and, therefore, will not improve the model fit and prediction accu Consequently, most scholars prefer to use the adjusted R-square to avoid poor predic by the regression model [32]. Furthermore, analysis of variance (ANOVA) and the s icance test (F test, t-test) of the regression model were conducted.…”

Section: (W Is Height Of Protrusion H Is Width Of Protrusion R Is Rad...mentioning

confidence: 99%

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A Novel Electrode Front-End Face Design to Improve Geometric Accuracy in Electrical Discharge Machining Process

Wang

Peng

Gunawan

et al. 2023

Metals

Self Cite

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Electrical discharge machining (EDM) is one of the important machining processes to produce mold components. When using the EDM process, surface quality, processing time, accuracy, and electrode cost must be considered. The electrode wear is the main factor that causes error on the geometric accuracy, especially the workpiece corner. Therefore, this study proposes a novel electrode design to improve the geometric accuracy for the EDM process. Firstly, the effect of discharge current, electrode diameter, and depth of cut on the electrode wear and workpiece corner were investigated. Multiple regression and analysis of variant were used to analyze the experiment data. The electrode end-face design with compensation rule and algorithm was established based on the data analysis and error value. Furthermore, a compensated electrode end-face design system with human machine interface, which has a procedure guiding function, was developed. The system can design the electrode end-face for minimizing workpiece corner error and improve geometric accuracy. Finally, cutting experiments were conducted to verify the proposed method, and the results show that the proposed method can effectively enhance the geometric accuracy by around 22~37%.

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Section: Experiments Condition and Equipmentmentioning

confidence: 99%

Section: (W Is Height Of Protrusion H Is Width Of Protrusion R Is Rad...mentioning

confidence: 99%

A Novel Electrode Front-End Face Design to Improve Geometric Accuracy in Electrical Discharge Machining Process

Wang

Peng

Gunawan

et al. 2023

Metals

Self Cite

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“…For today's modern industry, the influence of machining factors on overall performance is important, especially in terms of achieving a higher MRR, good dimensional accuracy, and excellent SR [49][50][51][52]. At the same time, the problems of low productivity in precision WEDM continue to persist.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

Straka,

Čorný

2024

Machines

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This article describes a proposed procedure for multiparametric optimization of the quality of machined surfaces, including mathematical models that can predict the high quality of a precisely machined surface and, at the same time, the high productivity of the process in WEDM of tool steels. The experimental research was carried out using the full DoE factorial design method, which has four technological parameters. The measured output qualitative parameter Surface Roughness (SR) and the output quantitative parameter Material Removal Rate (MRR) were evaluated using the Grey Relational Analysis (GRA) and Analysis of Variance (ANOVA) methods. Multiple Regression Models (MRM) were developed to represent the multiple responses of the investigated tool steels using a regression tool set. The results of the multiparametric optimization revealed a correlation between the input variable parameters of the electrical discharge process, while the favorable results of the observed output-dependent parameters SR and MRR were coupled to the parameters of low peak current I, low value of pulse on-time duration ton, low voltage of discharge U, and high value of pulse off-time duration toff. Based on the multiparametric optimization, key results were obtained that demonstrated the mutual dependence of the observed output process parameters. An optimum SR value of 1.50 μm was obtained with L8-level settings for the input variable parameters I, ton, U, and toff (2 A, 32 μs, 90 V, and 20 μs, respectively) and an MRR value of 12.50 mm3·min−1 was achieved.

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“…The input machining indicators include electrode materials [5][6][7][8], dielectric used during machining [9], spark variables (e.g., pulse-on time, pulse-off time, spark gap voltage, current, frequency, etc.) [10], flushing pressure [11], etc. The process parameters play an important role in the intensity of discharge energy [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Perspective to the Investigation of Surface Integrity of Al/SiC/Gr Composite on EDM

Abbas,

Sharma,

Al-Bahkali

et al. 2023

JMMP

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Conventional mechanical machining of composite is a challenging task, and thus, electric discharge machining (EDM) was used for the processing of the developed material. The processing of developed composite using different electrodes on EDM generates different surface characteristics. In the current work, the effect of tool material on the surface characteristics, along with other input parameters, is investigated as per the experimental design. The experimental design followed is an RSM-based Box–Behnken design, and the input parameters in the current research are tool material, current, voltage, pulse-off time, and pulse-on time. Three levels of each parameter are selected, and 46 experiments are conducted. The surface roughness (Ra) is investigated for each experimental setting. The machine learning approach is used for the prediction of surface integrity by different techniques, namely Xgboost, random forest, and decision tree. Out of all the techniques, the Xgboost technique shows maximum accuracy as compared to other techniques. The analysis of variance of the predicted solutions is investigated. The empirical model is developed using RSM and is further solved with the help of a teaching learning-based algorithm (TLBO). The SR value predicted after RSM and integrated approach of RSM-ML-TLBO are 2.51 and 2.47 µm corresponding to Ton: 45 µs; Toff: 73 µs; SV:8V; I: 10A; tool: brass and Ton: 47 µs; Toff: 76 µs; SV:8V; I: 10A; tool: brass, respectively. The surface integrity at the optimized setting reveals the presence of microcracks, globules, deposited lumps, and sub-surface formation due to different amounts of discharge energy.

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Optimization of Machining Parameters for Corner Accuracy Improvement for WEDM Processing

Cited by 6 publications

References 28 publications

A Novel Electrode Front-End Face Design to Improve Geometric Accuracy in Electrical Discharge Machining Process

A Novel Electrode Front-End Face Design to Improve Geometric Accuracy in Electrical Discharge Machining Process

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

A Machine Learning Perspective to the Investigation of Surface Integrity of Al/SiC/Gr Composite on EDM

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