Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.