Energy consumption modeling and prediction of the milling process: A multistage perspective

Abstract

In order to provide an accurate estimation of energy consumption, this work proposes a novel energy consumption modeling and prediction approach for a milling process from a multistage perspective. Based on its work stages, each stage’s energy consumption model is established by sliding filter, multiple linear regression, and improved gene expression programming (variable neighborhood search–based gene expression programming) methods and then the total energy consumption is predicted through their combination. A case study is given to illustrate the proposed model and its effectiveness. Compared with the full quadratic model, which can fully consider the interaction between cutting factors, the proposed method can achieve the higher accuracy to predict the energy consumption of the milling process.