An OPC UA based framework for predicting energy consumption of machine tools

Abstract

To improve the energy efficiency of the manufacturing industry, it is vital to correlate the energy consumption of machine tools with the machinery data. This paper proposes an OPC-UA based framework for predicting the energy consumption of machine tools, which includes the off-line learning stage and on-line exploitation stage. By using the proposed method, the gap between machinery data and energy data could be bridged. The experiment conducted on a milling machine has been exploited to validate the proposed framework. The results show that the proposed framework is feasible to predict the energy consumption of machine tools.