Generation of Effective Cutting Conditions for Machining Safety in a Manufacturing Industry

As part of an effort to systematize the operation planning for cutting processes, the neural network method has been applied to model the process of selecting cutting conditions and subsequently to arrive at effective and safe cutting conditions through learning during training of the model. New cutting conditions that are more effective and safer for the given circumstance are obtained. The proposed algorithm deletes the old information previously learned, and then makes the network make at improvement by learning. As a result, the new algorithm provides useful cutting conditions for safer manufacturing environments. A variety of simulation cases illustrate the performance of the proposed methodology. The simulation results are provided and discussed.