Establishment of an Improved Material-Drilling Power Model to Support Energy Management of Drilling Processes

Abstract

Drilling processes, as some of the most widely used machining processes in the manufacturing industry, play an important role in manufacturing process energy-saving programs. However, research focus on energy modeling of drilling processes, especially for the modeling of material-drilling power, are really scarce. To bridge this gap, an improved material-drilling power model is proposed in this paper. The obtained material-drilling power model can improve the accuracy of the material-drilling power and lay a good foundation for energy modeling and optimization of drilling processes. Finally, experimental studies were carried out on an XHK-714F CNC machining center (Hangzhou HangJi Machine Tool Co., Ltd., Hangzhou, China) and a JTVM6540 CNC milling machine (Jinan Third Machine Tool Co., Ltd., Jinan, China). The results showed that predictive accuracies with the proposed model are generally higher than 96% for all the test cases.

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

“…In their study, a deep-hole drilling process with two drills was considered and a particle swarm optimization-based algorithm was applied to find the best parameters setting. The energy prediction models in drilling [20,21] are useful tools to obtain energy savings.…”

An Improved Rapid Power and Energy Prediction Method of Drilling Process for Sustainable Manufacturing

“…Likewise, drilling is also a typical and broadly employed machining process in the manufacturing industry [41]. However, its energy modeling and energy efficiency enhancement has not been well-studied [16].…”

“…in addition, experimental studies were carried out to verify the effectiveness of the proposed method. In our previous studies, we proposed a drilling power model, which decomposed into the power of material-drilling, cutting-fluid-spraying, spindle-rotating, feeding, and standby operating [16]. The prediction accuracy of the above power prediction model of drilling is high.…”

“…The sampling frequency of the platform was set to 0.1 seconds. For detailed imfromation on the energy acquisition platform, please refer to literature [16]. The measure power profile for the experimental study is shown in Fig.…”

“…Due to the high computational complexity of drilling force and torque, the computational complexity of the above drilling power and energy models is very high. The other type of drilling power model is composed of sub-power models, such as standby operating power model, spindle-rotating power model, feeding power model, and so on [16]. Because of the accumulation of prediction errors of each sub-power model, the accuracy of total drilling power prediction needs to be further improved.…”