Advertisement

Cyber-physical Approach for Integrated Energy and Maintenance Management

  • Benjamin Neef
  • Christopher Schulze
  • Gerrit Posselt
  • Christoph Herrmann
  • Sebastian Thiede
Chapter
Part of the Sustainable Production, Life Cycle Engineering and Management book series (SPLCEM)

Abstract

Because of nowadays complex and highly automated industrial production lines, every stoppage involves the danger of a massive economic harm. That’s why companies use already various production, quality and maintenance methods to reduce—or at least to handle—unforeseen stoppages. This paper presents a novel approach to improve the reliability of production fields by supporting predictive maintenance under the combination of systems from energy and maintenance management. Wireless sensor networks and mobile devices are integrated into a cyber-physical system to gain real-time transparency of energy demands within production environments. Being aware of challenges introducing cyber-physical systems into the brownfield, the proposed solution considers needs of data standardisations, IT security, staff participation, big data handling, long-term technical risk and cost-benefit estimations. The developed methods are considered by user-oriented design principles to deliver role-specific information. Therefore, the derivation of these informational requirements is based on production unique job activities. Allocating time and component-based energy demands whilst taking machine and environmental conditions into account enables a basis of comparison and a continuous improvement process of energy efficiency and maintenance. These demands are fulfilled by the methods of a continuous energy value stream mapping, an energy efficiency tracker and an integrating energy and maintenance monitoring. This proposed approach is based on the ESIMA project funded by the German Federal Ministry of Education and Research. The project aims for “Optimised resource efficiency in production through energy autarkic sensors and interaction with mobile users”.

Notes

Acknowledgements

This paper evolved of the research project ESIMA (improved resource efficiency by power-autonomous sensor systems and customised human–machine interaction) which is funded by the German Ministry of Education and Research (BMBF) within the “Energy self-sufficient mobility—reliable energy self-sufficient systems for the mobile human” research and development programme and managed by the Project Management Agency VDI/VDE IT. Visit http://www.esima-projekt.de/ for more information.

References

  1. Bauernhansl T, Ten Hompel M, Vogel-Heuser B (2014a) Industrie 4.0 in produktion, automatisierung und logistik: anwendung technologien migration. Springer, Berlin, Heidelberg, New York, p 399Google Scholar
  2. Bauernhansl T, Ten Hompel M, Vogel-Heuser B (2014b) Industrie 4.0 in produktion, automatisierung und logistik: anwendung technologien migration. Springer, Berlin, Heidelberg, New York, p 525fGoogle Scholar
  3. Bogdanski G, Schönemann M, Thiede S, Andrew S, Herrmann C (2013) An extended energy value stream approach applied on the electronics industry. In: Emmanouilidis C, Taisch M, Kiritsis D (eds) Advances in production management systems. Competitive manufacturing for innovative products and services. APMS 2012. IFIP advances in information and communication technology, vol 397. Springer, Berlin, HeidelbergGoogle Scholar
  4. Bundesministerium für Bildung und Forschung (2018). http://www.bmbf.de/de/9072.php
  5. Chamberlain S, Sharp H, Maiden N (2006) Towards a framework for integrating agile development and user-centred design. In: Marchesi M, Abrahamsson P, Succi G (eds) Extreme programming and agile processes in software engineering. 7th International Conference, XP 2006, Oulu, Finland, 17–22 June 2006. Proceedings 2006. Aufl. Springer, Berlin, Heidelberg, p 143fCrossRefGoogle Scholar
  6. DFKI (2014) 6th innovation day of the SmartFactoryKLGoogle Scholar
  7. DIN EN 13306 (2010–12) Maintenance—Maintenance terminologyGoogle Scholar
  8. DIN EN ISO 9241-210 (2011) p 19Google Scholar
  9. DIN EN ISO 50001 (2011–12) Energy management systems—requirements with guidance for useGoogle Scholar
  10. Erlach K, Westkämper E (2009) Energiewertstrom – Der Weg zur energieffizienten Fabrik. Fraunhofer Verlag, Stuttgart. ISBN 978-3-8396-0010-8Google Scholar
  11. Fallenbeck N, Eckert C (2014) IT-Sicherheit und cloud computing; Bauernhansl T, Ten Hompel M, Vogel-Heuser B. Industrie 4.0 in produktion, automatisierung und logistik: anwendung technologien migration. Springer, Berlin, Heidelberg, New York, p 398fGoogle Scholar
  12. Ganschar O, Gerlach S, Hämmerle M, Krause T, Schlund S (2013) Produktionsarbeit der Zukunft - Industrie 4.0. In: Spath D (ed) IAO, Stuttgart, Fraunhofer, p 56fGoogle Scholar
  13. Gorecky D, Loskyll M (2014) Mensch-maschine-interaktion im industrie 4.0-zeitalter. In: Bauernhansl T, Ten Hompel M, Vogel-Heuser B (eds) Industrie 4.0 in produktion, automatisierung und logistik: anwendung technologien migration. Springer, Berlin, Heidelberg, New York, p 525; Zamfirescu CB, Pirvu BC, Schlick J, Zühlke D (2013) Preliminary insides for an anthropocentric cyber-physical reference architecture of the smart factory. Stud Inform Control 22(3)Google Scholar
  14. Hermann M, Pentek T, Otto B (2015) Design principles for industrie 4.0 scenarios: a literature review. Dortmund, Technische Universität Dortmund, p 4fGoogle Scholar
  15. Herrmann Christoph (2010) Ganzheitliches life cycle management, nachhaltigkeit und lebenszyklusorientierung in unternehmen. Springer, Berlin, Heidelberg, New York, p 360fCrossRefGoogle Scholar
  16. Kara Sami, Mazhar Muhammad, Kaebernick Hartmut, Ahmed Noor-E-Alam (2005) Determining the reuse potential of components based on life cycle data. CIRP Ann Manuf Technol 54(1):1–4CrossRefGoogle Scholar
  17. May G et al (2015) Energy management in production: a novel method to develop key performance indicators for improving energy efficiency. J Appl Energy 149:46–61CrossRefGoogle Scholar
  18. Neef B, Schulze C, Herrmann C, Thiede S (2017) Integriertes Energie- und Instandhaltungsmanagement im Kontext Industrie 4.0—Verbesserte Energieeffizienz und Instandhaltung durch Smart Devices und energieautarke kabellose Sensoren, in: Industrie Management 4.0, Ausgabe 1/2017, Energie- und Ressourceneffiziente ProduktionGoogle Scholar
  19. Posselt G et al (2014) Extending energy value stream models by the TBS dimension—applied on a multi product process chain in the railway industry. In: Proceedings of 21st CIRP conference on life cycle engineering 2014, pp 80–85CrossRefGoogle Scholar
  20. Posselt G (2015) Towards energy transparent factories. Springer. ISBN 978-3-329-20868-8Google Scholar
  21. Reichel J, Müller G, Mandelartz J (2009) Betriebliche instandhaltung. Springer, Berlin, Heidelberg, New York, p 137fGoogle Scholar
  22. Seera M, Lim CP, Nahavandi S, Loo CK (2014) Condition monitoring of induction motors: a review and an application of an ensemble of hybrid intelligent models. J Expert Syst Appl 41:4891–4903CrossRefGoogle Scholar
  23. Sheikh AK, Al-Sulaiman FA, Baseer MA (2005) Use of electrical power for online monitoring of tool condition. J Mater Process Technol 166:364–371Google Scholar
  24. Thiede S (2018) Environmental sustainability of cyber physical production systems. Procedia CIRP 69:644–649CrossRefGoogle Scholar
  25. Tole A (2013) Big data challenges. Database Syst J IV:3:31ffGoogle Scholar
  26. Umweltbundesamt (2018). https://www.umweltbundesamt.de/daten/energie/energie verbrauch-nach-energietraegern-sektoren
  27. US EPA (2011) Lean, energy & climate toolkit. EPA-100-K-07-003Google Scholar
  28. Ziesemer M (2015) So sieht Industrie 4.0 aus - ZVEI stellt, Referenzarchitektur Industrie 4.0 (RAMI)‘ vor und definiert die, Industrie 4.0 Komponente, in: Technik und Wirtschaft für die deutsche Industrie—Produktion, Nr. 13, p 17Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Machine Tools and Production TechnologyTechnical University BraunschweigBraunschweigGermany
  2. 2.Daimler AG Technology ManagementMannheimGermany

Personalised recommendations