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Can I read A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT on EtoBox?
A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT by Papacharalampopoulos, Alexios; Giannoulis, Christos; Stavropoulos, Panos; Mourtzis, Dimitris is a Engineering article available to read on EtoBox.
What is A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT about?
A dashboard application is proposed and developed to act as a Digital Twin that would indicate the Measured Value to be held accountable for any future failures. The current study describes a method for the exploitation of historical data that are related to production performance and aggregated from IoT, to eliciting the future behavior of the production, while indicating the measured values that are responsible for negative production performance, without training. The dashboard is implemented in the Java programming language, while information is stored into a Database that is aggregated by an Online Analytical Processing (OLAP) server. This achieves easy Key Performance Indicators (KPIs) visualization through the dashboard. Finally, indicative cases of a simulated transfer line are presented and numerical examples are given for validation and demonstration purposes. The need for human intervention is pointed out.
Who reads A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Papacharalampopoulos, Alexios; Giannoulis, Christos; Stavropoulos, Panos; Mourtzis, Dimitris
- Publisher
- MDPI AG; Multidisciplinary Digital Publishing Institute (MDPI); Basel: MDPI AG, 2011- (ISSN 2076-3417)
- Published
- 2020
- Language
- EN
- Field
- Engineering (Physical Sciences)