Monitoring and Controlling the E.D.M. Process

Bhattacharyya, S. K.; ElMenshawy, Mena

doi:10.1115/1.3183853

Cited by 15 publications

(4 citation statements)

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“…It has also been shown that the noise waveform of discharges between switch contacts is influenced by the choice of material [21] and electrode area [22]. In the late 1970s, early work showed that it was possible to use RF transmissions to distinguish between open-circuit, spark, arc, and short-circuit conditions in macroscale serial-mode EDM [23], [24]. At the microscale, particularly for batch mode, process monitoring is even more critical.…”

Section: B Sensing Debris-dominated Machiningmentioning

confidence: 98%

Wireless Monitoring of Workpiece Material Transitions and Debris Accumulation in Micro-Electro-Discharge Machining

Richardson

Gianchandani

2010

J. Microelectromech. Syst.

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Wireless signals are inherently generated with each discharge in micro-electro-discharge machining (μEDM), allowing direct observation of discharge quality. While traditional methods of monitoring machining quality rely on electrical characteristics at the discharge supply terminals, the wireless method provides more accurate information because it is less affected by electrical parasitics in the supply loop and by spatial averaging. The depth location of a metal-metal interface can be distinguished in the wireless signal. This is useful for determining the stop depth in certain processes. For example, in machining through samples of stainless steel into an electroplated copper backing layer, the metal transition is identified by a 10-dBm change in wireless-signal strength for the 300-350-MHz band and a 5-dBm average change across the full 1-GHz bandwidth. As debris accumulate in the discharge gaps, shifts in the wireless spectra can also indicate spurious discharges that could damage the workpiece and tool. For example, when copper micromachining becomes debris dominated, the 800-850-MHz band drops 4 dBm in signal strength, with a 2.2-dBm average drop across the full 1-GHz bandwidth.[ 2009-0109]Index Terms-Batch-mode micromachining, process monitoring, spurious discharges, stainless-steel machining, wireless feedback control.

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Section: B Sensing Debris-dominated Machiningmentioning

confidence: 98%

Wireless Monitoring of Workpiece Material Transitions and Debris Accumulation in Micro-Electro-Discharge Machining

Richardson

Gianchandani

2010

J. Microelectromech. Syst.

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“…In order to over come from such circumstances a skilled operator is required to take a corrective action to stable the machine by adopting proper corrective measures. Further different online controllers were developed; polynomial function based Abductive network [89,94], pulse discriminating type analyser [95], radio frequency analyser [96,97], neutral network base [90,98], fuzzy base pulse discriminator system [99,100] and digital signal procesing base [101]. These controllers identifies EDM process pulses and discriminates it and take proper corrective measures to stabilise the machine.…”

Section: Pulse Discriminatingmentioning

confidence: 99%

A Brief Review of Die Sinking Electrical Discharging Machining Process towards Automation

Pawade¹,

Banwait²

2013

AJME

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Electrical Discharge Machine (EDM) is especially used for the manufacturing of 3-D complex geometry and hard material parts that are extremely difficult-to-machine by conventional machining processes. In this paper authors have reviewed the research work carried out in the development of die-sinking EDM within the past decades for the improvement of machining characteristics such as Material Removal Rate (MRR), Surface Roughness (SR) and Tool Wear Ratio (TWR). In this review various techniques reported by EDM researchers for improving the machining characteristics have been categorized as process parameters optimization, multi spark technique, powder mixed EDM, servo control system and pulse discriminating. At the end, flexible machine controller is suggested for Die Sinking EDM to enhance the machining characteristics and to achieve high-level automation. Thus, die sinking EDM can be integrated with Computer Integrated Manufacturing (CIM) environment as a need of agile manufacturing systems.

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“…intense Radio Frequency (RF) signal is emitted due to the high rate of current change [93][94][95]. The intensity of this signal was found to drop rapidly as arcing is about to take place.…”

Section: Radio Frequencymentioning

confidence: 99%

Development of in situ monitoring for micro-electrical discharge machining

Kurnia¹

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With rapid technology advancement, the need for micro products is rapidly increasing in microelectronics, medical, automotive and telecommunication industries. Micro-Electrical Discharge Machining (EDM), the adaptation of conventional EDM, is an interesting way to realize micromachining process for the fabrication of three-dimensional complex microcomponents and microstructures from metallic and semiconductor substrate. This research work focus on the development of a micro-EDM analytical model, which is essential to provide a good approximation of the material removal. This approximation will provide a good guide in choosing the appropriate process parameters. The model is based on an electro-thermal theory to estimate the geometrical dimensions of micro craters produced on the electrode and workpiece surfaces. The model incorporates voltage, current and pulse-on-time during material removal to predict the temperature distribution in the workpiece due to single discharges in micro-EDM. It is assumed that the entire superheated area is ejected from the workpiece surface while only a small fraction of the molten area is expelled. For verification purposes, single discharge experiments using a Resistor-Capacitor (RC) pulse generator are performed with pure tungsten as the electrode and AISI 4140 alloy steel as the workpiece. For the pulse-on-time range of up to 1000 ns, the experimental and theoretical results are found to be in close agreement. The average volume approximation errors are found to be 2.7% and 6.6% for the anode and cathode respectively. An analytical model of the Micro-EDM process performances, namely Material Removal Rate (MRR), Tool Wear Ratio (TWR) and Surface Roughness (SR) are developed for the in situ monitoring of the machining process. The method is based on the crater geometry prediction using a developed theoretical model. Correction factors of removal, wear, and surface roughness are introduced in the approximation process to take into account the effects of undesirable discharges (open, short-circuit, arcing), machining time averaging error, overlapping craters, pockmarks, micro cracks, and reattachment of debris that result from the actual process. Based on the presented results, the analytical MRR approximation is able to provide a close approximation to the experimental results with up to 30% variation from the experimental MRR value. The analytical TWR presents a relatively better approximation with up to 24% variation from the experimental value. As for the SR-1

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Monitoring and Controlling the E.D.M. Process

Cited by 15 publications

References 0 publications

Wireless Monitoring of Workpiece Material Transitions and Debris Accumulation in Micro-Electro-Discharge Machining

Wireless Monitoring of Workpiece Material Transitions and Debris Accumulation in Micro-Electro-Discharge Machining

A Brief Review of Die Sinking Electrical Discharging Machining Process towards Automation

Development of in situ monitoring for micro-electrical discharge machining

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