Intelligent Monitoring and Compensation between EDM and ECM

Abstract

Electric discharge machining (EDM) is a type of high-precision machining usually applied to hard-material machining for mold manufacturing and in the aerospace industry. Longer process times typically reduce facility efficiency. The use of electrochemistry machining (ECM) can overcome this challenge to efficiently machine large workpieces. Some industries have adopted and combined these two processes for Inconel 718 material machining. However, the use of coordinate-measuring machine times to determine the machining accuracy of these two processes is difficult. This study matched process features by analyzing the electric driving pulses of ECM and EDM. Fitting intelligent sensing signals that respond to dimensional measurements can be used to analyze electrical pulse signals. For analyzing a cross-process model using extracted key features of the process, our feedback-based system determines lower machining measurement errors and improves geometric size. Finally, the processing time of experiments can be reduced by 80%, and our proposed model has a prediction accuracy of approximately 0.01 mm2.

Keywords

• electrical discharge machining (EDM)
• electrochemical machining (ECM)
• intelligent monitoring
• accuracy prediction