1. Introduction
In recent years, with the intense discussion of a low-carbon economy [
1] and carbon trading [
2], energy issues have once again caused widespread concern [
3]. As energy prices continue to rise, the manufacturing industry, which is the largest energy consumer industry, is paying more and more attention to energy consumption in the manufacturing process, and reducing energy consumption has become a goal pursued by the manufacturing industry. In particular, drilling is widely used in the aerospace manufacturing process [
4]. Studies have shown that, during the manufacture of a medium-sized aircraft, more than 6500 holes need to be machined, most of which are drilled [
5]. At the same time, drilling is the main processing technology for the roughing and semi-finishing of holes; however, the processing efficiency is relatively low which leads to huge levels of energy consumption during processing [
6]. Therefore, finding a solution to the problem of reducing energy consumption and increasing energy utilization during drilling processes is worth studying.
To obtain a high utilization of energy in manufacturing processes, the first step is to understand and characterize how energy is consumed in manufacturing [
7]. Recently, a number of energy consumption models have been proposed, particularly for machining. These existing models can be broadly classified into two categories: material removal rate (MRR)-based and detailed parameter (DPT)-based models [
8].
The MRR-based models predict total energy consumption based on the assumption that the total energy assumption and MRR are linearly related. Gutowski et al. [
9] pioneered the idea that machining energy consumption is related to the MRR. Kara and Li [
10] proposed a specific energy consumption model, which proved to be of high accuracy for both lathes and milling machines. Li et al. [
11] improved the MMR-based energy consumption model by considering the effects of no-load conditions and spindle speed on energy consumption. Costa et al. [
12] studied how to obtain the minimum roughness and maximum material removal rate. Zhong et al. [
13] proposed a decision rule for minimum energy consumption during turning based on the material removal rate.
Differently from MRR-based models, DPT-based models calculate the total energy consumption by using different parameters which are obtained based on different theories. Many studies have pointed out that the cutting parameters are the major factors affecting energy consumption. Guo et al. [
14] proposed an approach which combines energy consumption with surface roughness and applied it to finish turning; Xu et al. [
15] proposed a tool path planning algorithm for five-axis milling with the goal of minimizing energy consumption. However, the accuracy of their model was found to be less than satisfactory in some cases. Some energy models are based on cutting forces including the work of Draganescu et al. [
16] and Rodrigues and Coelho [
17] who noted that the transformation of the cutting force caused by the tool edge geometry directly affects specific energy consumption (SEC). Research by Li and Kara [
18] suggests that energy consumption models based solely on cutting forces only reflect the minimal energy consumption and not the maximum energy demand. To further improve the above energy models, Liu et al. [
19] proposed a method based on the cutting force to establish an energy consumption model for the milling. Shi et al. [
20] improved the energy consumption model of Liu [
19] by introducing no-load power to establish a milling energy consumption model and a milling energy consumption model considering tool wear [
21].
As already alluded to, although many of these existing energy models are comprehensive and detailed, most of the above energy models, whether MRR- or DPT-based, are built for turning or milling. There are very few studies on energy consumption for drilling. However, drilling is widely used in aerospace manufacturing processes [
22]. Whether these existing models can accurately describe the energy consumption of the drilling process is yet to be verified. Besides, as the name suggests, in an MRR-based model, the only considered variable is MRR. However, the same MRR can be combined from many different processing parameters; cutting experiments have shown that energy consumption is not always the same at the same MRR, as many other affecting factors need to be considered. In addition, DPT-based models, such as Liu et al. [
19], only consider the relationship between cutting power and total power; the coefficients in their model are purely obtained by mathematical regression thus lacking a clear theoretical basis.
In this paper, an energy consumption model for drilling processes was proposed. Idle power, cutting power, and auxiliary power were included in the proposed energy consumption model. The performance of the machine determines the idle power which can be calculated from the spindle speed. The cutting power was calculated from the cutting forces on the cutting edge. The auxiliary power was calculated from the cutting power by establishing its relationship to the cutting power. The model was validated in experiments and achieved high prediction accuracy.
5. Conclusions
In this paper, an energy consumption model for drilling processes was proposed. It is based on an equation consisting of the idle power, calculated based on the spindle speed, the cutting power, calculated from the cutting force, and the auxiliary power, calculated based on the cutting power. This proposed model was implemented and verified during the drilling process on a three-axis vertical machining center. Comparative experiments showed that the proposed model had higher accuracy than the existing MRR-based model, the model based on the MRR and spindle speed, and the model based only on cutting force.
Although the new power model from this work is only specific to the particular machine tool and the specific workpiece material on which the experiments were carried out, we believe they are applicable to the majority of machine tools and workpiece materials, albeit with different coefficients in the model.
On the potential future study of the subject, the effect of tool wear on energy consumption should be considered, especially in the drilling of difficult-to-machine materials wherein the roughing stage often has radical cutting parameters. This calls for the consideration of the impact of tool wear on energy consumption. Secondly, the proposed model only considers the energy consumption of simple holes, which may not be applicable for deep hole drilling, and further research on the energy consumption of deep hole drilling should be carried out.