Development of a Transient Energy Prediction Model for Machine Tools

Abstract

Machine tools are one of the vital equipment in the manufacturing sector and consume a significant amount of energy during the steady state and transient state. An extensive amount of research work had conducted to model energy consumption in a steady state of machine tools. The researchers generally neglect the transient state because the profile of transient state energy consumption is stochastic, and time duration is concise, which results in a significant error during the prediction of total energy consumption of machine tools. This work presents an experimental study to acquire the transient state energy consumption of a machine tool. The Matlab software is used to process the captured data, and an empirical model is developed for the prediction of energy consumed by a machine tool in a transient state. The coefficient of determination is determined to evaluate the fitness of the empirical model. The results indicate that the model can predict the transient state energy consumption accurately. This approach can be conveniently applied to predict the total energy consumption of machine tools accurately. The accurate energy consumption model of machine tools is the foundation for selection of optimal process parameters of a machining process that leads to sustainable manufacturing