A review on optimization of machining performances and recent developments in electro discharge machining

Nahak, Binayaka; Gupta, Ankur

doi:10.1051/mfreview/2018015

Cited by 25 publications

(16 citation statements)

References 141 publications

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“…In 1980, the United States invented a computer-aided EDM called the computer numerical controlled EDM. Since then, the EDM machining process has attracted worldwide attention [1], [20].…”

Section: Literature Reviewmentioning

confidence: 99%

An Intelligent System for Improving Electric Discharge Machining Efficiency Using Artificial Neural Network and Adaptive Control of Debris Removal Operations

Lee

Lai

2021

IEEE Access

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Electrical discharge machining (EDM) can effectively solve the shortcomings of traditional machining processes that cannot process special materials, so it is widely used on workpieces with strong hardness materials, such as titanium alloys and tool steels to produce various molds and dies. However, the operating procedures of EDM are quite complicated and low machining productivity. To improve machining efficiency, this study develops an intelligent system that adaptively controls debris removal operations instead of using preset debris removal parameters. A feature extraction method is proposed in this study to effectively identify the machining states from streaming images of the machining curve for evaluating the appropriate time of the debris removal operation. Then, the extracted features feed into the artificial neural network model to establish a debris removal predicted model. The preliminary experimental result shows that the established predicted model can achieve an accuracy of 96.93% for a testing dataset containing 750 machining curve images. To further verify the effectiveness of the proposed intelligent system in improving EDM efficiency, we integrate the debris removal predicted model into the EDM machine and test it on the manufacturing site. Compared with the preset debris removal parameter, the proposed intelligent system can save nearly 38.60% of machining time for the machining depth of 6.45mm under specific EDM conditions. INDEX TERMS Artificial intelligence, debris removal operation, electric discharge machining, intelligent system, machining efficiency.

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“…In 1980, the United States invented a computer-aided EDM called the computer numerical controlled EDM. Since then, the EDM machining process has attracted worldwide attention [1], [20].…”

Section: Literature Reviewmentioning

confidence: 99%

An Intelligent System for Improving Electric Discharge Machining Efficiency Using Artificial Neural Network and Adaptive Control of Debris Removal Operations

Lee

Lai

2021

IEEE Access

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“…Among different cutting alternatives, electric discharge machining (EDM) has secured an important place due to its cutting versatility specifically for electrically conductive material regardless of their mechanical characteristics [2,3]. This process was introduced by B. R. Lazarenko et al [4] about six decades ago, who used repetitive sparks produced between the tool and workpiece to machine cavities in the substrate. Later on, the importance of EDM was emphasized, and it has been deployed in making dies and molds, biomedical parts, aerospace components, automobile, and military applications [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

EDM of Ti6Al4V under nano-graphene mixed dielectric: a detailed roughness analysis

Ishfaq

Maqsood

Anwar

et al. 2022

Int J Adv Manuf Technol

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Surface finish has an essential role in superior performance of machined products which becomes crucial for sophisticated applications like invasive biomedical implants and aerospace components. Ti6Al4V is popular in these applications due to its exceptional characteristics of weight-to-strength ratio. However, Ti6Al4V is a difficult-to-cut material; therefore, non-traditional cutting techniques especially, electric discharge machining (EDM), are widely adopted for Ti6Al4V cutting. The engagement of nano-powders are used to upsurge the cutting rate and surface quality. Among the different powders, a novel nano-powder additive, i.e., graphene, has not been tested in EDM of Ti6Al4V. Therefore, the potential of nano-graphene is comprehensively investigated herein for roughness perspective in EDM of Ti-alloy. The experimental design is based on Taguchi L18 orthogonal framework which includes six EDM parameters. The experimental findings are thoroughly discussed with statistical tests and physical evidence. The surface quality achieved with an aluminum electrode was found best amongst its competitors, whereas the worst surface asperities were noticed when brass electrode was used under graphene mixed dielectric. Moreover, it is conceived that the positive tool polarity provides lower roughness for all types of electrodes. Furthermore, optimal settings have been developed that warrant a reduction of 61.4% in the machined specimen’s roughness compared to the average roughness value recorded during the experimentation.

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“…As the electrode wears, the requisite geometrical characteristics of the electrode will not be replicated on the workpiece. The EWR is the ratio of the electrode weight difference before and after machining with EDM process to the time of machining [11,12].…”

Section: Introductionmentioning

confidence: 99%

Effect of Voltage on Electrode Wear Rate (EWR) in the Electrical Discharge Machining (EDM) for Stainless Steel AISI 444

Aghdeab¹,

Abdulnabi²

2022

ETJ

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 Using low levels of machining parameters (voltage, Ip and Ton) to achieve low EWR.  According to Factorial Design, model fits the data was 97.65% and 97.83% for 140 and 240 V, respectively.  Mathematical relationship between the input parameters and EWR has been gained for correlating EWR.Electrical Discharge Machining process (EDM) is a nontraditional metal removal technique that uses thermal energy to erode the workpiece without generating any physical forces of cutting between the tool and the machining part. It is used to cutting of hard and electrical conductivity materials and product intricate shapes of products. The aim of this work is to study the effect of changing voltage values on electrode wear rate (EWR). The machining parameters includes voltage (V), peak current (Ip), pulse duration (Ton) and finally, pulse interval (Toff). The results show that the EWR was increase with rising in voltage, peak current and pulse duration values but when the pulse interval value rises, the electrode wear rate reduce. The best (EWR) value was (0.093507) mm3/min that obtained at voltage (140) V, Ip (12) A, Ton (400) µs and Toff (12) µs.

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A review on optimization of machining performances and recent developments in electro discharge machining

Cited by 25 publications

References 141 publications

An Intelligent System for Improving Electric Discharge Machining Efficiency Using Artificial Neural Network and Adaptive Control of Debris Removal Operations

An Intelligent System for Improving Electric Discharge Machining Efficiency Using Artificial Neural Network and Adaptive Control of Debris Removal Operations

EDM of Ti6Al4V under nano-graphene mixed dielectric: a detailed roughness analysis

Effect of Voltage on Electrode Wear Rate (EWR) in the Electrical Discharge Machining (EDM) for Stainless Steel AISI 444

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