2023
DOI: 10.3390/ma16010434
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Design of Real-Time Extremum-Seeking Controller-Based Modelling for Optimizing MRR in Low Power EDM

Abstract: Electric discharge machining (EDM) is one of the non-conventional machining processes that supports machining for high-strength and wear-resistant materials. It is a challenging task to select the process parameters in real-time to maximize the material removal rate since real-time process trials are expensive and the EDM process is stochastic. For the ease of finding process parameters, a modelling of the EDM process is proposed. Due to the non-linear relationship between the material removal rate (MRR) and d… Show more

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Cited by 8 publications
(2 citation statements)
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“…Additionally, the presence of Al, Cr, and N elements suggests potential advantages such as improved mechanical properties and the potential to replace costly surface spray methods like PVD, PVC, etc. The protective role of the coating on the base electrode during machining contributes to enhanced working conditions of the electrode in micro-EDM [ 23 , 24 ].…”
Section: Resultsmentioning
confidence: 99%
“…Additionally, the presence of Al, Cr, and N elements suggests potential advantages such as improved mechanical properties and the potential to replace costly surface spray methods like PVD, PVC, etc. The protective role of the coating on the base electrode during machining contributes to enhanced working conditions of the electrode in micro-EDM [ 23 , 24 ].…”
Section: Resultsmentioning
confidence: 99%
“…Various process control systems have been proposed to enhance EDM quality [23,94,234,235], including fuzzy logic-based control [23], inverse modeling [94], and adaptive control systems that monitor the spark ratio as an indicator of gap voltage [234]. Another approach involves control focused on maximizing MRR by dynamically optimizing the unloading time [235]. The advancement of smart manufacturing in EDM will see greater progress with the expansion of mathematical and computer modeling capabilities.…”
Section: Smart Manufacturingmentioning
confidence: 99%