• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1998.10a
• /
• pp.176-179
• /
• 1998

In general, machining time by electrical discharge machining (EDM) process is much longer than that of cutting process, so rough-cut has done for the purpose of reducing machining time prior to EDM Nowadays EDM speed is improving due to the advance of EDM capacity. Therefore a new method, machining a raw material directly by EDM without rough-cut, is used widely. EDM area is varies according to the EDM position in three-dimensional EDM process, so EDM parameters should be determined adaptively based on the EDM area to increase productivity. However it is difficult to calculate EDM area corresponding to the EDM position the EDM workers who have experience in shop floor determine machining parameters by experience. This paper proposes a method for determining EDM parameters based on EDM area corresponding to EDM position.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.7
• /
• pp.44-51
• /
• 1998

Two-step neural network is designed for determining electrical discharge machining parameters in low erosion. The first neural network, which is used as a classification network, checks whether the current conditions are appropriate to electrical discharge machining in low tool erosion. If the conditions are appropriate to EDM in low erosion, suitable EDM parameters are generated by the second neural network. Theoretically known EDM conditions are produced and also utilized for training the second neural network. The trained neural network is tested how well suitable EDM machining conditions are generated under unknown machining situations Experimental result shows that the proposed two-step neural network approach could be effectively used for determining EDM parameters in low tool erosion. The results also have a practical contribution to EDM area in that it could be applied for maintaining low tool wear as well as obtaining maximum machining rates simultaneously.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.1
• /
• pp.11-17
• /
• 2010

This study investigates the non-traditional manufacturing process of dry wire electrical discharge machining (EDM) in which liquid dielectric is replaced by a gaseous medium. Wire EDM experiments of thin workpieces were conducted both in wet and dry EDM conditions to examine the effects of spark cycle (T), spark on-time ($T_{on}$), thickness of work pieces, and work material on machining performance. The material removal rate (MRR) in the dry wire EDM case was much lower than that in the wet wire EDM case. In addition, the thickness of workpiece and work-material were found to be critical factors influencing the MRR for dry EDM process. The relative ratios of spark, arc and short circuit were also calculated and compared to examine the effectiveness of processes of dry and wet wire EDM.

• Korean Journal of Computational Design and Engineering
• /
• v.4 no.4
• /
• pp.355-359
• /
• 1999

This paper presents a method for determining machining parameters in electrical discharge machining process (EDM) based on discharge area. The parameters are the peak value of currents, the pulse-on time, and the pulse-off time, on which the EDM performance depends chiefly. The optimal machining parameters are closely related on discharge area, which can be calculated from a tool electrode and a discharge height. In the paper the discharge area is obtained from NC code for machining the tool electrode instead of its geometric model. The method consists of following three steps. First a Z-Map model is constructed from the NC code. Secondly, the discharge area is obtained from the Z-Map model and a Z-height. Finally, the machining parameters are calculated from the discharge area. An introduced example shows that the machining parameters are calculated by the using a Z-map model obtained from the machining data for a tool electrode.

• Journal of Advanced Marine Engineering and Technology
• /
• v.27 no.3
• /
• pp.429-436
• /
• 2003

The electrical discharge machining(EDM) with Si electrode instead of Gr or Cu electrode. made enormous effects on the surface. machining time, anti-caustic workpiece surface and so on In this paper. we experimented on the inter-role distance during discharge the electrical phenomenon of inter-pole, the distribution of discharge point. the distribution of off load time. etc., using Si electrode Cu electrode and Gr electrode under the same machining condition. As a result of a large quantity generated exclusive powders. the performance of the EDM using Si electrode. compared with EDM using others. is improved. We show that the quantities of those make far pole-gap discharge and discharge scatter under stable machining status possible.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1998.03a
• /
• pp.35-39
• /
• 1998

Determination of effective EDM parameters is significant to increase productivity. However, With the complexity of EDM phenomena, a universal selection method of EDM parameters has not been established yet. Moreover, No attempt has been tried before to suggest a logical method in determining essential machining parameters for effective electrical discharge machining. Peak current, one of the most significant factors in EDM, is proportional to EDM area. This paper presents a method that can be Z-map modeling from CMM data, and calculate EDM area using Z-map.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1571-1574
• /
• 2005

Generally, the kerosene or the deionized water has been used for dielectric fluid in the electrical discharge machining. The spark occurs when the voltage is over the breakdown voltage and induces high temperature. In this study, the Oxygen gas is used as the dielectric. The voltage behavior in the dry Micro Electrical discharge machining is compared with that of the conventional Micro Electrical discharge machining. The dry Micro EDM has some advantages. The electrode wear isvery smaller than that of the conventional Micro EDM. The contamination in the dry Micro EDM can be drastically reduced comparing to that of the conventional Micro EDM. The Oxygen gas can be replaced as the dielectric successfully.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1244-1247
• /
• 2005

The material removal mechanism of Electrical Discharge Machining (EDM) process has been studied for several decades. However, understanding of the material removal mechanism is still a difficult problem because the mechanism involves complicated physical phenomena including plasma. Especially, for a micro-EDM process, due to the influence of the debris that is generated during the machining process, quantitative modeling of EDM becomes more complex. To understand better the effects of the debris in the micro-EDM process experimentally, a new approach has been introduced in this study. Using a specially designed workpiece holder, the debris generated during the EDM with various process conditions has been collected. Then, using a simulated environment using micro-sized metal powders, the influence of the debris during the single EDM discharge has been observed. The effects of EDM process parameters on the debris size and product quality are discussed.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.5
• /
• pp.43-49
• /
• 1998

Adaptive neural network approach is presented for determining Electrical Discharge Machining (EDM) parameters. Electrical Discharge Machining has been widely used with its capability of machining hard metals and tough shapes. In the past few years, EDM has been established in tool-room and large-scale production. However. in spite of it's wide application, an universal selection method of EDM parameters has not been established yet. No attempt has been tried before to suggest a logical method in determining essential machine parameters considering the machining rate and resulting surface roughness integrity. The paper presents a method, which is focusing on determining appropriate machining parameters. Depending on the electrode wear and surface roughness, an adaptive neural network is designed for providing suitable machining guideline.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.604-607
• /
• 2005

In the electro-discharge machining the machining performance is closely related to the characteristics of discharge which can be identified from electrical behavior in gap between workpiece and electrode. Therefore, the accurate prediction of electrical behavior in electro-discharge machining (EDM) is useful to process control and optimization. However, any simulation model fur prediction of electrical behavior in EDM process has never been reported until now. In this study, a simulation model is developed to analyze the electrical behavior of electro-discharge plasma which significantly influences electrical behavior in EDM process. For the purpose of this the fundamentals of electro-discharge mechanism such as inception, propagation, formation of plasma channel and termination are investigated to accurately predict the cycle of discharge plasma in EDM. As a result, a mathematical model of electro-discharge plasma is constructed with considering the fundamentals of electro-discharge plasma. Consequently, it is demonstrated that the developed model can predict the electrical behavior of plasma such as electron density in various conditions.