Abstract
In this study, the effects of cutting parameters (i.e., cutting speed, feed rate) and deep cryogenic treatment on thrust force (Ff) have been investigated in the drilling of AISI 316 stainless steel. To observe the effects of deep cryogenic treatment on thrust forces, M35 HSS twist drills were cryogenically treated at –196 °C for 24 h and tempered at 200 °C for 2 h after conventional heat treatment. The experimental results showed that the lowest thrust forces were measured with the cryogenically treated and tempered drills. In addition, artificial neural networks (ANNs) and multiple regression analysis were used to model the thrust force. The scaled conjugate gradient (SCG) learning algorithm with the logistic sigmoid transfer function was used to train and test the ANNs. The ANN results showed that the SCG learning algorithm with five neurons in the hidden layer produced the coefficient of determinations (R 2) of 0.999907 and 0.999871 for the training and testing data, respectively. In addition, the root mean square error (RMSE) was 0.00769 and 0.009066, and the mean error percentage (MEP) was 0.725947 and 0.930127 for the training and testing data, respectively.
Highlights
In recent years, applying different heat treatments to tool steels has been widely executed in order to increase productivity [1]
Cryogenic treatment has proved for many years to be an effective method to improve tool life and to eliminate residual stress [2] and [3]
The objectives of this study are to determine the effects of three different heat treatments and cutting parameters on the thrust force in drilling of AISI 316 stainless steel, and to predict the thrust force using multiple regression analysis and artificial neural networks (ANNs), without the need for complex and time-consuming experimental studies
Summary
In recent years, applying different heat treatments to tool steels has been widely executed in order to increase productivity [1]. Cryogenic treatment has proved for many years to be an effective method to improve tool life and to eliminate residual stress [2] and [3]. Cryogenic treatment increases the wear resistance of materials by providing a more intensive and homogeneous distribution of carbides due to transformation of the retained austenite into martensite [6]. The cryogenic treatment significantly increases the lifetime of the HSS cutting tools. The improvements in tool life vary from 65 to 343% depending on the cutting conditions used [7]
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