Intelligent Energy Profiling for Decentralized Fault Diagnosis of Automated Production Systems

Abstract:

The proliferation of energy management systems leads to new potentials of data acquisition that can deliver improved machine information through intelligent linking. In addition to energy controlling, the newly gotten database creates further use cases for advanced purposes. This paper presents an exemplary application of a diagnostic scenario for industrial robots. For this objective, data fusion of energy data and operating logs is necessary to obtain detailed knowledge of the behavior of a production system. Hereby, an online measurement system will be described, which helps to uncover inefficiencies in production systems.

• Periodical: Applied Mechanics and Materials (Volume 805)
• Pages: 73-78
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.805.73
• Online since: November 2015
• Authors: Johannes Kohl*, Hans Fleischmann, Jörg Franke
• Keywords: Energy Management, Fault Diagnosis, OPC UA, Power Consumption

References

[1] International Organization for Standardization (ISO), DIN EN ISO 50001: Energy management systems – Requirements with guidance for use, Beuth Verlag, Berlin, (2002).

DOI: 10.3403/30279771

[2] M. Schenk, Instandhaltung technischer Systeme (Maintenance of technical systems), first ed., Springer Verlag, Heidelberg, (2010).

[3] T. Pavel, P. Kodet, V. Havlena, OPC-UA information model for large-scale process control applications, 38th Annual Conference on IEEE Industrial Electronics Society (IECON) (2012) 5793–5798.

DOI: 10.1109/iecon.2012.6389038

[4] D. Hastbacka, L. Barna, M. Karaila, Y. Liang, P. Tuominen, S. Kuikka, Device status information service architecture for condition monitoring using OPC UA, Emerging Technology and Factory Automation (ETFA) (2014) 1–7.

DOI: 10.1109/etfa.2014.7005141

[5] T. Bauernhansl, M. ten Hompel, B. Vogel-Heuser, Industrie 4. 0 in Produktion, Automatisierung und Logistik (Industry 4. 0 in production, automation and logistics), first ed., Springer-Verlag, Heidelberg, (2014).

DOI: 10.1007/978-3-662-45537-1

[6] M. Michl, Webbasierte Ansätze zur ganzheitlichen technischen Diagnose (Web-based approaches to holistic technical diagnosis), first ed., Meisenbach-Verlag, Bamberg, (2013).

[7] H. Fleischmann, J. Kohl, M. Schneider, J. Franke, Intelligente Fehlerdiagnose in Industrie 4. 0 (Intelligent fault diagnosis in Industry 4. 0), wt Werkstattstechnik online 105 (2015) 90–95.

DOI: 10.37544/1436-4980-2015-03-14

[8] M. Brossog, C. Hartmann, J. Kohl, J. Merhof, M. Reichenbach, D. Fey, J. Franke, Prozessflexible Steuerung von Industrierobotern (Flexible process control of industrial robots), wt Werkstattstechnik online 104 (2014) 535–540.

DOI: 10.37544/1436-4980-2014-9-535

[9] W. Mahnke, S. -H. Leitner, M. Damm, OPC Unified Architecture, third ed. Springer-Verlag, Heidelberg, (2009).

[10] S. Spreng, J. Kohl, J. Franke, Development of an adjustable measuring system for electrical consumptions in production, Applied Mechanics and Materials 655 (2014) 41–45.

DOI: 10.4028/www.scientific.net/amm.655.41