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In EDM, the cavity is directly replicated and molded by the tool electrode through galvanic corrosion, so the electrode design is directly related to the machining accuracy of the part. However, in the current CAD/CAM system, the processing of tool electrodes is done manually by technicians based on their experience and knowledge, which is very dependent on their professional skills and experience, and also unable to reuse the process, resulting in a large waste of process resources. To solve this problem, an intelligent CNC programming method for tool electrode is proposed, which organizes the historical machining cases of tool electrode to form a CNC parameter dataset, and then constructs a GA-BP network model to train and determine the CNC parameters required in the machining process, and finally generates the machining toolpaths of tool electrode in NX software. The experimental results prove that the integration of GA-BP neural network can effectively reuse the resources of manual programming process of tool electrode, reduce the dependence on technicians' professional skills, and promote the development of tool electrode machining programming in a more intelligent direction.
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Yang et al. (2024) studied this question.
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