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CPS-based fault-tolerance method for smart factories

Simulation-based framework and fault management application

  • Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea; and Chungnam National University, Daejeon, Republic of Korea

         ,

    Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea

         ,

    Chungnam National University, Daejeon, Republic of Korea

     EMAIL logo     and

    Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea
Published/Copyright: September 13, 2016
at - Automatisierungstechnik
From the journal at - Automatisierungstechnik Volume 64 Issue 9

Abstract

In this paper, we propose a fault tolerance method in smart factories which features a simulation-based framework and a fault management application, FORTUNA (Fault-tOleRanT and aUtomated decisioN making Application). The simulation-based framework is characterized by a Virtual Factory (VF) which plays an integrator role in CPS architecture for the smart factory. The VF provides two key functionalities, (1) a simulation of CPS models represented by ECML (ETRI CPS Modeling Language), and (2) a state estimation based on massive CPS data. By deploying Kalman filter, a predictor-corrector type estimator, FORTUNA not only detects faults through the realtime observation of CPS data but also predicts potential failures by the simulation. It is demonstrated that the method can work effectively in industrial systems with real dataset.

Zusammenfassung

In diesem Aufsatz schlagen wir eine Fehlertoleranzmethode in smarten Fabriksystemen vor, die einen simulationsbasierten Analyserahmen und eine Fehlermanagement-Anwendung umfasst, FORTUNA (Fault-tOleRanT and aUtomated decisioN making Application). Der simulationsbasierte Analyserahmen ist durch eine Virtuelle Fabrik (VF) gekennzeichnet, die eine integrierende Rolle in der CPS-Architektur des smarten Fabriksystems spielt. Die VF bietet zwei Schlüsselfunktionalitäten, (1) eine Simulation von CPS Modellen, die durch ECML (ETRI CPS Modellierungssprache) dargestellt werden, sowie (2) eine Zustandsschätzung auf der Grundlage einer Vielzahl von CPS-Daten. Durch Anwendung des Kalman-Filters, ein Prädiktor-Korrektor-Schätzverfahren, spürt FORTUNA Fehler nicht nur durch die Echtzeitbeobachtung von CPS-Daten auf, sondern prognostiziert ebenso potentielle Ausfälle durch die Simulation. Es wird gezeigt, dass die Methode in industriellen Systemen mit realen Datensätzen effektiv funtionieren kann.

Keywords: Smart factory; fault-tolerance; cyber-physical systems; modeling and simulation; Kalman filtering
Schlagwörter: Smarte Fabriksysteme; Fehlertoleranzmethoden; Cyber-Physikalische Systeme; Modellierung und Simulation; Kalman-Filterung

About the authors

Sungjoo Kang

Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea; and Chungnam National University, Daejeon, Republic of Korea

Jaeho Jeon

Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea

Hyeon-Soo Kim

Chungnam National University, Daejeon, Republic of Korea

Ingeol Chun

Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea

Acknowledgement

This work was supported by the ICT R&D program of MSIP/IITP. [R-20150505-000691, IoT-based CPS platform technology for the integration of virtual-real manufacturing facility]

Received: 2016-4-7
Accepted: 2016-6-20
Published Online: 2016-9-13
Published in Print: 2016-9-28

©2016 Walter de Gruyter Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Industrial Internet of Things supporting Factory Automation
  4. Übersicht
  5. IoT business models in an industrial context
  6. The Open Geospatial Consortium and Industrie 4.0
  7. Methoden
  8. Design of an ecosystem platform for manufacturing operations using loosely defined standards
  9. A common core for information modeling in the Industrial Internet of Things
  10. Semantic interoperability in IoT-based automation infrastructures
  11. CPS-based fault-tolerance method for smart factories
  12. IIoT in vehicle assembly
  13. Anwendungen
  14. Software-based smart factory networking
  15. Dissertation
  16. A Black-Box method for parametric model order reduction based on matrix interpolation with application to simulation and control
https://doi.org/10.1515/auto-2016-0065
Keywords for this article
Smart factory; fault-tolerance; cyber-physical systems; modeling and simulation; Kalman filtering

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Industrial Internet of Things supporting Factory Automation
  4. Übersicht
  5. IoT business models in an industrial context
  6. The Open Geospatial Consortium and Industrie 4.0
  7. Methoden
  8. Design of an ecosystem platform for manufacturing operations using loosely defined standards
  9. A common core for information modeling in the Industrial Internet of Things
  10. Semantic interoperability in IoT-based automation infrastructures
  11. CPS-based fault-tolerance method for smart factories
  12. IIoT in vehicle assembly
  13. Anwendungen
  14. Software-based smart factory networking
  15. Dissertation
  16. A Black-Box method for parametric model order reduction based on matrix interpolation with application to simulation and control
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