A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT
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 fro...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-03-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/7/2377 |
| _version_ | 1797571900320251904 |
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| author | Alexios Papacharalampopoulos Christos Giannoulis Panos Stavropoulos Dimitris Mourtzis |
| author_facet | Alexios Papacharalampopoulos Christos Giannoulis Panos Stavropoulos Dimitris Mourtzis |
| author_sort | Alexios Papacharalampopoulos |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T20:47:10Z |
| format | Article |
| id | doaj.art-b721c2e3c45a4fa29e0fa86dcda262e1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T20:47:10Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b721c2e3c45a4fa29e0fa86dcda262e12023-11-19T20:13:03ZengMDPI AGApplied Sciences2076-34172020-03-01107237710.3390/app10072377A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoTAlexios Papacharalampopoulos0Christos Giannoulis1Panos Stavropoulos2Dimitris Mourtzis3Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceLaboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, GreeceA 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.https://www.mdpi.com/2076-3417/10/7/2377digital twindecision support systemfactor analysisKPIquantitative analysisroot-cause analysis |
| spellingShingle | Alexios Papacharalampopoulos Christos Giannoulis Panos Stavropoulos Dimitris Mourtzis A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT Applied Sciences digital twin decision support system factor analysis KPI quantitative analysis root-cause analysis |
| title | A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT |
| title_full | A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT |
| title_fullStr | A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT |
| title_full_unstemmed | A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT |
| title_short | A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT |
| title_sort | digital twin for automated root cause search of production alarms based on kpis aggregated from iot |
| topic | digital twin decision support system factor analysis KPI quantitative analysis root-cause analysis |
| url | https://www.mdpi.com/2076-3417/10/7/2377 |
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