Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

Huang, Yu; Ming, Wuyi; Guo, Jianwen; Zhang, Zhen; Liu, Guangdou; Li, Mingzhen

doi:10.1007/s00170-013-5037-3

Cited by 41 publications

(15 citation statements)

References 19 publications

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“…In statistical analyses, the factor effect is defined as the difference between the two extreme values of the response obtained for the corresponding factor, and the relatively factor effect is defined as Eq. 17, where RE i is the i th relatively factor effect, and E i is the i th factor effect [44,45]. The graphical assessment also can be depicted from Fig.…”

Section: Main Effect Analysis For Mrr and Ramentioning

confidence: 94%

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

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This paper proposed a hybrid intelligent process model, based on finite-element method (FEM) and Gaussian process regression (GPR), for electrical discharge machining (EDM) process. A model of single-spark EDM process has been constructed based on FEM method, considering the latent heat, variable heat distribution coefficient of cathode (f c ), and plasma flushing efficiency (PFE), to predict material removal rate (MRR) and surface roughness (Ra). This model was validated using reported analytical and experimental results. Then, a GPR model was proposed to establish relationship between input process parameters (pulse current, pulse duration, and discharge voltage) and the process responses (MRR and Ra) for EDM process. The GPR model was trained, tested, and tuned using the

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Section: Main Effect Analysis For Mrr and Ramentioning

confidence: 94%

A hybrid process model for EDM based on finite-element method and Gaussian process regression

Ming

Zhang

et al. 2014

Int J Adv Manuf Technol

Self Cite

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“…The minimum and maximum value of infeed were determined based on the previous research of the authors. The initial range of the infeed values calculated according to [ 49 ] was adapted in tests to find the minimum value allowing for the electric discharge between the wire electrode and the workpiece, and the maximum value allowing for the machining without short circuits or breaking the wire. Thus, the infeed range for finishing machining was z = 30–70 μm.…”

Section: Methodsmentioning

confidence: 99%

The Accuracy of Finishing WEDM of Inconel 718 Turbine Disc Fir Tree Slots

et al. 2021

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Servicing aircraft engines sometimes requires manufacturing only a single piece of a given part. Manufacturing a turbine disc using traditional methods is uneconomical. It is necessary to use a different machining method recommended for small lot production. One of the proposed methods is WEDM (wire electrical discharge machining). The article presents the results of the research on finishing WEDM of Inconel 718 turbine disc fir tree slots. The influence of infeed, mean gap voltage, peak current, pulse off-time, and discharge energy on the shape accuracy, surface roughness, microcracks, and the white layer thickness were determined. Mathematical models were developed based on the DoE (Design of Experiment) analysis. The statistical significance of the models was verified with the ANOVA (Analysis of Variance) test. The machining parameters control methods that allow achieving the required shape accuracy, surface roughness, and surface layer condition were presented. The obtained surface roughness was Ra = 0.84 μm, the shape accuracy of the slot in the normal-to-feed direction was Δd = 0.009 μm, the profile shape accuracy was Δr = 0.033 μm, and the thickness of recast (white) layer was approximately 5 μm.

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“…e ANOVA is carried out for the obtained GFRG which shows the impact of various process parameters from Table 10; it had been observed that the obtained ANOVA table does not give su cient results since the degrees of freedom (DOF) for the error term is zero. is happens due to the mismatching of the input parameters and the level of each parameter.…”

Section: Resultsmentioning

confidence: 99%

“…e experiments have been conducted by changing pulse on time, pulse off time, and peak current. Huang et al [10] observed the influence of various process parameters on surface quality, material removal rate, and average gap voltage in the WEDM of high hardness tool steel YG15. Regression models are used to obtain the optimum cutting parameter combination.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Machining Parameters in WEDM of Al/SiCp20 MMC Using Taguchi-Based Grey-Fuzzy Approach

Phate

Toney²,

Phate³

2019

Modelling and Simulation in Engineering

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Aluminium silicate metal matrix composite (AlSiC MMC) is satisfying the requirement of material with good mechanical, thermal properties, and good wear resistance. But the difficulties during the machining are the main hurdles to its replacement for other materials. Wire electric discharge machining (WEDM) is a very effective process used for this type of difficult-to-cut material. So an effort has been taken to find out the most favourable level of input parameters for WEDM of AlSiC (20%) composite using a Taguchi-based hybrid grey-fuzzy grade (GFG) approach. e plan for experimentation is designed using Taguchi's L 9 (2 3 ) array. e various process parameters considered for the investigation are pulse on time (T ON ), pulse off time (T OFF ), wire feed rate (WFR), and peak current (IP). Surface integrity such as surface roughness measured during the different types of cutting (along straight, inclined, and curvature directions) is considered in the present work. Grey relational analysis (GRA) pooled with the fuzzy logic is effectively used to find out the grey-fuzzy reasoning grade (GFRG). e Taguchi approach is coupled with the GFRG to obtain the optimum set of process parameters. From the experimental findings, it has been observed that the most economical process parameters for WEDM of AlSiCp20 were the pulse on time is 108 microsec, pulse off time is 56 microsec, wire feed rate (WFR) is 4 m/min, and peak current (IP) is 11 amp. From the analysis of variance (ANOVA), it is observed that the pulse on time is the foremost influencing parameters that contribute towards GFRG by 52.61%, followed by the wire feed rate (WFR) 38.32% and the current by 5.45%.

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Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

Cited by 41 publications

References 19 publications

A hybrid process model for EDM based on finite-element method and Gaussian process regression

A hybrid process model for EDM based on finite-element method and Gaussian process regression

The Accuracy of Finishing WEDM of Inconel 718 Turbine Disc Fir Tree Slots

Analysis of Machining Parameters in WEDM of Al/SiCp20 MMC Using Taguchi-Based Grey-Fuzzy Approach

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