A mechanics based prediction model for tool wear and power consumption in drilling operations and its applications

We present a mechanics based model for predicting the power consumption of drilling operations. Different from existing power models in machining that ignore the tool wear, our model takes into full consideration the tool wear which is particularly pronounced in drilling and causes extra power consumption. For any given spindle speed n and feed rate f, our model establishes the relationship between the length of drill and the total power consumption as well as the amount of tool wear. With this prediction model established, we can then optimize the drilling parameters (n, f) towards different objectives, such as the two applications reported in this paper - to minimize the average power consumption per unit length of drill and to maximize the tool usage before its replacement. Physical drilling experiments of the proposed power prediction model and its two optimization applications are also reported in this paper which have validated the accuracy of the model and convincingly demonstrated its efficacy in deciding optimal drilling parameters (n, f) for energy minimization and other objectives. (C) 2019 Elsevier Ltd. All rights reserved.