Abstract: In according with the non-linear character in the process of EDMM, a tool wear prediction model is established based on artificial neural network. The tool relative wear and machining rate can be predicted by the network, which makes foundation for tool’s dynamic compensation in EDMM. An improved evolutionary algorithm which could adaptively adjust mutation rate and magnitude of mutation is presented to optimize the neural network’s weights and topology in case of local extre-mums obtained from traditional BP algorithm.

Key words: Electrical discharge milling machining, Evolutionary neural network, Tool wear prediction