Digital twin modeling of surface texture generation by the electrical discharge machining process

A digital twin model of the surface texture generated by the electrical discharge machining process is developed in three steps. The finite element method is used to model a crater formed by an individual spark. Subsequently, the single spark data is processed and stored in a form of a data set and used in the third phase to plot the real-time status of the machined surface using live data acquisition, data analysis, and multiple spark simulations. This real-time simulation enables more precise control over the EDM process and accurate prediction of surface roughness, contributing to enhanced surface quality and machining efficiency. The experimental specimen underwent R a value testing at various locations, revealing a close alignment between the measured values and the predicted range provided by the digital twin model

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Publication Details

Journal
Procedia CIRP
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procir.2025.03.077
Citations
1
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.73

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article

Digital twin modeling of surface texture generation by the electrical discharge machining process

K. P. Rajurkar, Trilochan Jamunkar, Murali Sundaram
1 citations
Procedia CIRP
Advanced Machining and Optimization Techniques
0.73
article

Digital twin modeling of surface texture generation by the electrical discharge machining process

K. P. Rajurkar, Trilochan Jamunkar, Murali Sundaram
article en
1 citations

Abstract

A digital twin model of the surface texture generated by the electrical discharge machining process is developed in three steps. The finite element method is used to model a crater formed by an individual spark. Subsequently, the single spark data is processed and stored in a form of a data set and used in the third phase to plot the real-time status of the machined surface using live data acquisition, data analysis, and multiple spark simulations. This real-time simulation enables more precise control over the EDM process and accurate prediction of surface roughness, contributing to enhanced surface quality and machining efficiency. The experimental specimen underwent R a value testing at various locations, revealing a close alignment between the measured values and the predicted range provided by the digital twin model

Procedia CIRPVol. 137
University of Nebraska–Lincoln (US), University of Cincinnati (US)
National Science Foundation
Affordable and clean energy
Openalex Percentile: Top 24%
Advanced Machining and Optimization Techniques
0.73
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