Integration of Scanning Technology for Tool Wear Analysis in the Electrical Discharge Machining Process

There is a direct correlation between surface roughness and electrode tool status in the Electrical Discharge Machining (EDM) process. The quality of the machined surface of workpieces is becoming even more critical in recent industries. In general, electrode wear evaluation plays a vital role in the EDM process, affecting the operation cost and the accuracy of the required dimensions and geometric shape. This study presents a new method to evaluate the copper electrode wear during machining AISI 1005 carbon steel in the EDM process using a 3D laser scanner that measures the lost volume of the electrode. The results of the proposed method were compared with those of the conventional method. Laser technology was used to accurately measure the dimensions and surface characteristics of the electrode by scanning the electrode surface and the electrode view topology before and after the machining process. The processed data was saved on a computer connected to the laser scan device, converted to STL files, and sent to a 3D system (Geomagic Control X software). This software utilizes accurate mathematical algorithms to determine the available volumetric differences in the electrode. The experiments used Design-Expert 13 software, selecting three machining parameters: Current (Ip), pulse on time (Ton), and pulse off time (Toff). The results showed that the Tool Wear Rate (TWR) obtained by the two methods showed a mean absolute deviation of 3.6%, with an insignificant error on the effect of the machining parameters on TWR (1.01% for Ip, 1.92% for Ton, and 2.29% for Toff).

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Publication Details

Journal
Engineering Technology & Applied Science Research
Published
2024-10-09
DOI
https://doi.org/10.48084/etasr.7989
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
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article

Integration of Scanning Technology for Tool Wear Analysis in the Electrical Discharge Machining Process

Ali Abbar Khleif, Nader Abdulhameed, Baraa M.H. Albaghdadi, Osama Sameer Sabbar
Engineering Technology & Applied Science Research
Advanced Machining and Optimization Techniques
article

Integration of Scanning Technology for Tool Wear Analysis in the Electrical Discharge Machining Process

Ali Abbar Khleif, Nader Abdulhameed, Baraa M.H. Albaghdadi, Osama Sameer Sabbar
article en

Abstract

There is a direct correlation between surface roughness and electrode tool status in the Electrical Discharge Machining (EDM) process. The quality of the machined surface of workpieces is becoming even more critical in recent industries. In general, electrode wear evaluation plays a vital role in the EDM process, affecting the operation cost and the accuracy of the required dimensions and geometric shape. This study presents a new method to evaluate the copper electrode wear during machining AISI 1005 carbon steel in the EDM process using a 3D laser scanner that measures the lost volume of the electrode. The results of the proposed method were compared with those of the conventional method. Laser technology was used to accurately measure the dimensions and surface characteristics of the electrode by scanning the electrode surface and the electrode view topology before and after the machining process. The processed data was saved on a computer connected to the laser scan device, converted to STL files, and sent to a 3D system (Geomagic Control X software). This software utilizes accurate mathematical algorithms to determine the available volumetric differences in the electrode. The experiments used Design-Expert 13 software, selecting three machining parameters: Current (Ip), pulse on time (Ton), and pulse off time (Toff). The results showed that the Tool Wear Rate (TWR) obtained by the two methods showed a mean absolute deviation of 3.6%, with an insignificant error on the effect of the machining parameters on TWR (1.01% for Ip, 1.92% for Ton, and 2.29% for Toff).

Engineering Technology & Applied Science ResearchVol. 14(5)
University of Technology - Iraq (IQ), University of Florida (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 85%
Advanced Machining and Optimization Techniques
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