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

Yan He, Pengcheng Wu, Yuling Wang, Fei Tao, Bernard Hon

2020Procedia CIRP11 citationsDOIOpen Access PDF

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.

Topics & Concepts

Energy consumptionMachine toolEnergy (signal processing)EngineeringComputer scienceEfficient energy useConsumption (sociology)Mechanical engineeringStatisticsSocial scienceElectrical engineeringSociologyMathematicsEnergy Efficiency and ManagementBuilding Energy and Comfort OptimizationDigital Transformation in Industry
An OPC UA based framework for predicting energy consumption of machine tools | Litcius