APPLICATION OF ANN TECHNIQUE TO PREDICT TOOL WEAR WITH VARIATION OF TURNING OPERATION PARAMETERS
Giriraj Garhewal, Vipin Katiyar, Shoaib Mohammed
ABSTRACT
Article History Received: Sept’ 2018 Accepted: Oct’ 2018 The quality of the machined piece and tool life are greatly influenced during the machining operation. For that reason, engineers waste a lot of time and efforts trying to reduce to the l wear according to the design drawing during the turning process. In this work, an artificial neural network (ANN) modeling is used to analyze tool wear an in cutting condition of carbide coated. Factors and responses parameters based an ANN technique has developed a model to predict the output. Multilayer perceptron artificial neural network or the tool wear monitoring in turning gives an optimized result. By observed ANN model provided decent satisfactory results, and that it can be used for online tool wear estimation.
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