Decentralized Control of Logistic Processes in Cyber-physical Production Systems at the Example of ESB Logistics Learning Factory

Abstract The increasing emergence of cyber-physical systems (CPS) and a global crosslinking of these CPS to cyber-physical production systems (CPPS) are leading to fundamental changes of future work and logistic systems requiring innovative methods to plan, control and monitor changeable production systems and new forms of human-machine-collaboration. Particularly logistic systems have to obey the versatility of CPPS and will be transferred to so-called cyber physical logistic systems, since the logistical networks will underlie the requirements of constant changes initiated by changeable production systems. This development is driven and enhanced by increasingly volatile and globalized market and manufacturing environments combined with a high demand for individualized products and services. Also nowadays mainly used centralized control systems are pushed to their limits regarding their abilities to deal with the arising complexity to plan, control and monitor changeable work and logistic systems. Decentralized control systems bear the potential to cope with these challenges by distributing the required operations on various nodes of the resulting decentralized control system. Learning factories, like the ESB Logistics Learning Factory at ESB Business School (Reutlingen University), provide a wide range of possibilities to develop new methods and innovative technical solutions in a risk-free and close-to-reality factory environment and to transfer knowledge as well as specific competences into the training of students and professionals. To intensify the research and training activities in the field of future work and logistics systems, ESB Business School is transferring its existing production system into a CPPS involving decentralized planning, control and monitoring methods and systems, human-machine-collaboration as well as technical assistance systems for changeable work and logistics systems.

[1]  Willibald A. Günthner,et al.  Adaptive Logistiksysteme als Wegbereiter der Industrie 4.0 , 2017, Handbuch Industrie 4.0.

[2]  Eberhard Abele,et al.  Learning Factories for Research, Education, and Training☆ , 2015 .

[3]  Eberhard Abele,et al.  Wandlungsfähige Produktionssysteme: Heute die Industrie von morgen gestalten , 2008 .

[4]  Eberhard Abele,et al.  Effiziente Fabrik 4.0 , 2015 .

[5]  Thomas Bauernhansl,et al.  Die Vierte Industrielle Revolution - Der Weg in ein wertschaffendes Produktionsparadigma , 2017, Handbuch Industrie 4.0.

[6]  Dieter Wegener Industrie 4.0 - Chancen und Herausforderungen für einen Global Player , 2017, Handbuch Industrie 4.0.

[7]  M. Wilke Wandelbare automatisierte Materialflusssysteme für dynamische Produktionsstrukturen , 2006 .

[8]  Birgit Vogel-Heuser,et al.  Agentenbasierte dynamische Rekonfiguration von vernetzten intelligenten Produktionsanlagen – Evolution statt Revolution , 2014 .

[9]  Siegfried Dais Industrie 4.0 - Anstoß, Vision, Vorgehen , 2017, Handbuch Industrie 4.0.

[10]  Birgit Vogel-Heuser,et al.  Industrie 4.0 in Produktion, Automatisierung und Logistik. Anwendung · Technologien · Migration , 2014 .

[11]  Willibald A. Günthner,et al.  Internet der Dinge - Intelligent verteilt , 2008 .

[12]  Michael ten Hompel,et al.  Logistik 4.0 , 2015, Informatik-Spektrum.

[13]  Si’en Chen,et al.  Analytics: The real-world use of big data in financial services studying with judge system events , 2016, Journal of Shanghai Jiaotong University (Science).

[14]  Matthias Meyer Management Control in Unternehmenskooperationen , 2008 .

[15]  Willibald A. Günthner,et al.  Internet der Dinge - Steuern ohne Hierarchie , 2008 .