مصرف نیرو در عملیات حفاری
Abstract
Nomenclature
1. Introduction
2. Model of energy consumption considering tool wear in a drilling process
3. Energy consumption model calibration experiments
4. Model validations and discussion
5. Applications
6. Conclusions
Acknowledgements
References
Abstract
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 e 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.
Introduction
Drilling is a simple yet fundamental machining operation needed in many manufacturing applications. For example, it is estimated that there are more than 6500 holes in a medium-sized aeroplane (Portillo et al., 2012) and most of them are drilled. When drilling on hard materials (such as Nickel-based super-alloy) which are commonly used for aeronautical parts, the biggest concern is the wear of the tool as it typically deteriorates very fast due to the exceedingly large cutting force (Sun et al., 2015). As drilling is simple, when the tool is fixed, the only affecting machining parameters are the spindle rpm n and tool feed rate f. The fundamental process planning task is then to determine a best pair of (n, f) towards various objectives. In particular, amid today’s high societal attention on sustainability, the following objective on energy minimization naturally rises: how to plan (n, f) to minimize the average power consumption per unit length of drill? Another objective that is related to the cost of tool could be: given a tool replacement threshold on the tool wear (i.e., the maximum tool wear at which the tool must be replaced), how to find the best (n, f) so that the maximum length of drill can be achieved by a single tool? A similar minimization problem could also be defined on time efficiency. These objectives are different and may conflict each other. Regardless, the fundamental prerequisite is a correct modelling of the relationship among the tool wear, the length of drill, the power consumption, and the machining parameters (n, f).