Non-pulsed Energy Modeling Based on Energy Consumption Subunits in Wire Electrical Discharge Machining (WEDM) Process

Zheng, Jun; Lai, Xuwei; Zhou, Xinmei; Chen, Ankai; Wang, Zheng

doi:10.1007/s12541-019-00107-y

Cited by 16 publications

(4 citation statements)

References 14 publications

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“…Hence, such respawn nature of the game was used in the BRO algorithm to prevent early convergence and better exploration of search space for search agents. The mathematical equation used for respawning search agents in BRO is expressed in Equation (5).…”

Section: Meta-heuristic Algorithm Designmentioning

confidence: 99%

“…Even conventional machining of several super‐alloys offers poor surface nature, discomfort efficiency, lesser dimensional accuracy, etc., [ 3 ] The effective application of knowledge in the manufacturing process can significantly improve productivity and efficiency. Therefore, in both cases, for the machining of ceramics and super‐alloys, various non‐traditional approaches such as Electrochemical Discharge Machining (ECDM), [ 4 ] Wire Electrical Discharge Machining (WEDM), [ 5 ] Abrasive Water Jet Machining (AWJM), [ 6 ] Laser Beam Machining (LBM), [ 7 ] etc., play a vital role in resolving such machining issues.…”

Section: Introductionmentioning

confidence: 99%

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Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

2023

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Alumina‐Zirconium dioxide (Al2O3‐ZrO2) Ceramic Composite Material (CCM) is specifically known for its enhanced mechanical and corrosion resistance properties and is widely used as raw material for mechanical parts like, pump components, die inserts, bearings, etc. As a result, industrialists are searching for an efficient method for machining this Al2O3‐ZrO2 material. In this regard, a hybrid unconventional machining process called Electrochemical Discharge Machining (ECDM) is adapted to analyze the machinability of Al2O3‐ZrO2 CCM. Besides, to ensure the efficiency of the ECDM process, a magnetic field is also given to the tool electrode during this study to improve the Material Removal Rate (MRR) of the ECDM machine. The experiment is designed using Response Surface Methodology (RSM) by changing the magnitudes of input controls, namely Electrolytic Concentration (EC), Inter‐electrode Gap (IEG) and Applied Voltage (AV). Moreover, a novel hybrid machine learning optimization strategy called Deep Belief Network based Battle Royal Optimization (DBN‐BRO) algorithm is developed to predict and optimize the ECDM process. Finally, the optimum results are perceived from 55 V AV, 22.727% EC and 40.909 mm IEG input levels. The proposed method shows less than 0.6207 Root Mean Square Error (RMSE) and tools nearly 80 iterations for optimizing the results.

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Section: Meta-heuristic Algorithm Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

2023

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“…Other scholars have reduced energy consumption by controlling the pulse power or improving the processing technology [25][26][27][28], which is easy to achieve in actual processing and reduces power consumption to some extent. Jun Zhen [29] et al analyzed the energy characteristics of WEDM based on a nonpulse energy consumption unit and established the prediction model of nonpulsed auxiliary energy consumption and feed energy. The accuracy of the prediction model was 96%.…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Modeling for EDM Based on Material Removal Rate

Yang

Zhang

et al. 2020

IEEE Access

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In recent years, the energy problem has caused widespread concern in the manufacturing industry. The energy consumption in traditional turning and milling processes has been widely studied. However, there are few studies on the energy consumption of the EDM (Electric Discharge Machining) process, which is also widely used. This paper proposed a modeling method for the energy consumption model of EDM based on the discharge between electrodes. The proposed model is composed of processing energy consumption caused by electrode-to-electrode discharge and no-load energy consumption of the machine tool. Based on the discharge principle of EDM and the relationship between EDM machining parameters and MRR (Material Removal Rate), an energy consumption model for EDM machining is established. In this paper, validation experiments are designed for important machining parameters, and the prediction accuracy of the theoretical model established in this paper is higher than 96%. The energy efficiency in electric machining is also analyzed, and the influence relationship between energy consumption and machining parameters is revealed, which can effectively reduce the energy consumption of electric spark punching.

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“…The published literature indicate that just few studies have reported on the analysis of minimizing the shape deviation in WEDM by taking into account the electrical discharge parameters [28][29][30][31][32]. Therefore, in this paper, theoretical and experimental investigation of the WEDM condition and parameters like the dielectric volumetric flow Q v , wire tension F n and wire speed on shape deviation for the cut parts was conducted.…”

Section: Introductionmentioning

confidence: 99%

Archives of Metallurgy and Materials

Świercz

Oniszczuk-Świercz

Zawora

et al. 2019

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New materials require the use of advanced technology in manufacturing parts of complex shape. One of the modern nonconventional technology of manufacturing difficult to cut materials is the wire electrical discharge machining (WEDM). The article presents the results of theoretical and experimental research in the influence of the WEDM conditions and parameters on the shape deviation during a rough cut. A numerical model of the dielectric flow in the gap (ANSYS) was developed. The influence of the dielectric velocity field in the gap on the debris evacuation and stability of WEDM process was discussed. Furthermore, response surface methodology (RSM) was used to build empirical models for influence of the wire speed V d , wire tension force F n , the volume flow rate of the dielectric Q v on the flatness deviation after the WEDM.

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Non-pulsed Energy Modeling Based on Energy Consumption Subunits in Wire Electrical Discharge Machining (WEDM) Process

Cited by 16 publications

References 14 publications

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

Energy Consumption Modeling for EDM Based on Material Removal Rate

Archives of Metallurgy and Materials

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