An IoT-enabled approach for energy monitoring and analysis of die casting machines

Die casting machines, widely used in manufacturing industry, consume a significant amount of energy. To reduce energy consumption, the primary task is to accurately characterize and evaluate the current performance. The ability to access energy-related data and, more importantly, effectively analyze these data to obtain key indicators is critical. In this paper, an Internet of Things (IoT) enabled method is proposed to stream online energy data for energy analysis of a die casting machine. The energy data captured by digital power meters and PLCs was transferred to a central server using real-time Ethernet. A set of indicators, including energy per part and energy per action, were developed to interpret the data and to evaluate the performance of a die casting machine. The feasibility of the developed energy monitoring and analysis approach was examined in a case study. Based on the results, several potential ways of energy savings were suggested. (C) 2018 The Authors. Published by Elsevier B.V.