A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT

Applied Sciences

Christos Giannoulis¹  Panos Stavropoulos¹  Alexios Papacharalampopoulos¹  Dimitris Mourtzis¹ 

[1] Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras,26504 Patras, Greece;

关键词: digital twin;    decision support system;    factor analysis;    KPI;    quantitative analysis;    root-cause analysis;   

DOI  :  10.3390/app10072377

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown