Skip to main content
Book cover

Handbuch Industrie 4.0 pp 1–36Cite as

Implementierung von autonomen I4.0-Systemen mit BDI-Agenten

  • 666 Accesses

Part of the Springer Reference Technik book series

Zusammenfassung

Der Anforderung von Industrie 4.0 nach flexiblen Software-Architekturen für eine digitale Vernetzung kann durch Multiagenten-Systeme begegnet werden, die Integration autonomer Problemlösung erfordert aber kognitive Software-Architekturen, die über regelbasierte Systeme hinausgehen. BDI-Agenten sind durch ihre Ziel- und Kontext-Orientierung ein Lösungsansatz, da sie mit verschiedenen Stufen kognitiver Komplexität zur Bearbeitung von Aufgaben eingesetzt werden können. Ihre Kommunikation kann durch serviceorientierter Architekturen gewährleistet werden, wodurch auch die Anbindung an andere IT-Systeme erfolgen kann. Steuerungskonzepte für eine Supply Chain, ein Transportsystem und ein Produktionssystem demonstrieren den Einsatz von BDI-Agenten. Daraus wird eine Klassifikation von Agenten für industrielle Anwendungen abgeleitet. Abschließend wird eine ganzheitliche Industrie 4.0-Architektur durch das Framework Arrowhead, die Verwaltungsschale und BDI-Agenten beschrieben.

Schlüsselwörter

  • Industrie 4.0
  • I4.0-System
  • BDI-Agent
  • Multiagenten-System
  • I4.0-Architektur
  • Framework
  • Middleware
  • Agentenplattform
  • Active-Component
  • Active-Component-Shell
  • Serviceorientierte Architektur
  • Systemintegration
  • Kognitive Komplexität
  • Zeitsensitivität
  • Autonomie
  • RAMI4.0
  • Interoperabilität
  • KoWest
  • Supply Chain
  • Produktionssystem

This is a preview of subscription content, access via your institution.

Abb. 1
Abb. 2
Abb. 3
Abb. 4
Abb. 5
Abb. 6
Abb. 7
Abb. 8
Abb. 9
Abb. 10
Abb. 11

Literatur

  • Adeyeri MK, Mpofu K, Olukorede TA (2015) Integration of agent technology into manufacturing enterprise: a review and platform for industry 4.0. In: International Conference on Industrial Engineering and Operations Management (IEOM). Dubai, United Arab Emirates, S 1–10

    Google Scholar 

  • Ahn HJ, Lee H, Park SJ (2003) A flexible agent system for change adaption in supply chains. Expert Syst Appl:603–618

    Google Scholar 

  • Baumgärtel H (2019) Electronics and ICT as enabler for digital industry and optimized supply chain management covering the entire product lifecycle, Projektbericht, Productive 4.0 Project Consortium (ID: 737459)

    Google Scholar 

  • Baumgärtel H, Ehm H, Laaouane S, Gerhardt J, Kasprzik A (2018) Collaboration in supply chains for development of CPS enabled by semantic web technologies. In: 2018 Winter Simulation Conference (WSC). IEEE Press, Gothenburg, Sweden, S 3627–3638

    Google Scholar 

  • Bearzotti L, Salomone E, Chiotti O (2012) An autonomous multi-agent approach to supply chain event management. Int J Prod Econ:468–478

    Google Scholar 

  • Bellifemine F, Poggi A, Rimassa G (2001) JADE: a FIPA2000 compliant agent development environment. In: Proceedings of the 5th international conference on Autonomous agents. Montreal, Canada, S 216–217

    Google Scholar 

  • Bicaku A, Maksuti S, Hegedus C, Tauber M, Delsing J, Eliasson J (2018) Interacting with the arrowhead local cloud: on-boarding procedure, In: Proceedings 2018 IEEE Industrial Cyber-Physical Systems (ICPS), IEEE, Piscataway, USA, S 743–748

    Google Scholar 

  • Bogon T (2012) Agentenbasierte Schwarmintelligenz. Dissertation

    Google Scholar 

  • Bratman M (1987) Intention, plans, and practical reason. Harvard University Press, Cambridge

    Google Scholar 

  • Braubach L, Pokahr A (2012) Developing distributed systems with active components and Jadex. Scalable Comput Pract Exp:100–120

    Google Scholar 

  • Braubach L, Lamersdorf W, Pokahr A (2003) Implementing a BDI-infrastructure for JADE agents. EXP, S 76–85

    Google Scholar 

  • Bussmann S (2012) Production 2000+. http://www.stefan-bussmann.de/en/agents/p2000p.html. Zugegriffen am 25.10.2019

  • Bussmann S, Schild K (2001) An agent-based approach to the control of flexible production systems. In: 8th International Conference on Emerging Technologies and Factory Automation. Boston, USA, S 481–488

    Google Scholar 

  • Bussmann S, Jennings NR, Wooldridge MJ (2013) Multiagent systems for manufacturing control: a design methodology. Springer Science & Business Media. Springer-Verlag Berlin Heidelberg

    Google Scholar 

  • D’Andrea R, Wurman P (2008) Future challenges of coordinating hundreds of autonomous vehicles in distribution facilities. In: International Conference on Technologies for Practical Robot Applications (TePRA). Woburn, USA, S 80–83

    Google Scholar 

  • Delsing J (2017a) IoT automation: arrowhead framework. CRC Press, Taylor & Francis Group, Boca Raton

    CrossRef  Google Scholar 

  • Delsing J (2017b) Local cloud internet of things automation: Technology and business model features of distributed internet of things automation solutions. IEEE Ind Electron Mag:8–21

    Google Scholar 

  • Derhamy H, Eliasson J, Delsing J, Priller P (2015) A survey of commercial frameworks for the internet of things. In: 20th Conference on Emerging Technologies & Factory Automation. Luxembourg City, Luxembourg, S 1–8

    Google Scholar 

  • DIN. 16593-1 (2018) Reference model for industrie 4.0 service architectures. DIN, Beuth Verlag GmbH, Berlin

    Google Scholar 

  • DIN. 19233 (1999) Leittechnik – Prozessautomatisierung – Automatisierung mit Prozessrechensystemen. DIN, Beuth Verlag GmbH, Berlin

    Google Scholar 

  • FIPA (2019) FIPA. http://www.fipa.org/index.html. Zugegriffen am 05.06.2019

  • Fortino G, Russo W, Savaglio C, Shen W, Zhou M (2017) Agent-oriented cooperative smart objects: from IoT system design to implementation. IEEE Trans Syst Man Cybern:1–18

    Google Scholar 

  • Fujita K, Bai Q, Ito T, Zhang M, Ren F, Aydoğan R, Hadfi R (2017) Modern approaches to agent-based complex automated negotiation, Bd 674. Springer International Publishing, Cham

    CrossRef  Google Scholar 

  • George M, Lansky A (1987) Reactive reasoning and planning: an experiment with a mobile robot. In: Proceedings of the 6th National Conference on Artificial Intelligence (AAAI 1987). Seattle, USA, S 677

    Google Scholar 

  • Grangel-González I, Halilaj L, Coskun G, Auer S, Collarana D, Hoffmeister M (2016) Towards a semantic administrative shell for industry 4.0 components. In: 10th International Conference on Semantic Computing (ICSC). Laguna Hills, USA, S 230–237

    Google Scholar 

  • Guerra-Hernández A, El Fallah-Seghrouchni A, Soldano H (2004) Learning in BDI multi-agent systems. In: International workshop on computational logic in multi-agent systems. Springer, Berlin/Heidelberg, S 218–233

    Google Scholar 

  • Herron D, Castillo O, Lewis R (2015) Systems and methods for individualized customer retail services using RFID wristbands: U.S. Patent Application(14/034,395)

    Google Scholar 

  • Jabeur N, Al-Belushi T, Mbarki M, Gharrad H (2017) Toward leveraging smart logistics collaboration with a multi-agent system based solution. Procedia Comput Sci:672–679. https://doi.org/10.1016/j.procs.2017.05.374

  • Kamdar R, Paliwal P, Kumar Y (2018) A state of art review on various aspects of multi-agent system. J Circuit Syst Comp:1830006. https://doi.org/10.1142/S0218126618300064

  • Kantamneni A, Brown L, Parker G, Weaver WW (2015) Survey of multi-agent systems for microgrid control. Eng Appl Artif Intell:192–203

    Google Scholar 

  • Khare AR, Kumar BY (2015) Multiagent structures in hybrid renewable power system: a review. J Renew Sustain Energy:63101. https://doi.org/10.1063/1.4934668

  • Kinny D, Georgeff M, Rao A (1996) A methodology and modelling technique for systems of BDI agents. In: European workshop on modelling autonomous agents in a multi-agent world. Springer, Berlin/Heidelberg, S 56–71

    Google Scholar 

  • Kirn S, Herzog O, Lockermann P, Spaniol O (2006) Multiagent engineering: Theory and applications in enterprises. International handbooks on information systems. Springer, Berlin/New York

    CrossRef  Google Scholar 

  • Kravari K, Bassiliades N (2015) A survey of agent platforms. J Artif Soc Soc Simul:11

    Google Scholar 

  • Kunze O, Baumgärtel H, Neitmann A, Rosemeier S (2012) Dynamic Truck Meeting (DTM): Ein Prozess- & Schnittstellenstandard zur Realisierung von dynamischen Begegnungsverkehren mit Hilfe von Dispositions- und Telematik-Systemen (ca. 2012). https://edocs.tib.eu/files/e01fn12/731853814.pdf. Zugegriffen am 23.01.2020

  • Laird J (2012) The Soar cognitive architecture. MIT Press, Cambridge, MA/London

    CrossRef  Google Scholar 

  • Lu Y (2017) Industry 4.0: a survey on technologies, applications and open research issues. J Ind Inf Integr:1–10

    Google Scholar 

  • Malakuti S, Bock J, Weser M, Venet P, Zimmermann P, Wiegand M, Grothoff J, Wagner C, Bayha A (2018) Challenges in skill-based engineering of industrial automation systems *. In: 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, Turin, Italien, S 67–74

    Google Scholar 

  • Mayer S (2009) Development of a completely decentralized control system for modular continuous conveyors. Dissertation, Karlsruhe Institute of Technology

    Google Scholar 

  • Park HS, Tran NH (2011) An autonomous manufacturing system for adapting to disturbances. Int J Adv Manuf Technol:1159–1165

    Google Scholar 

  • Pokahr A, Braubach L (2011) Active components: a software paradigm for distributed systems. In: Proceedings of International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2011). Lyon, France, S 141–144

    Google Scholar 

  • Pudāne M, Lavendelis E (2017) General guidelines for design of affective multi-agent systems. Appl Comput Syst:5–12. https://doi.org/10.1515/acss-2017-0012

  • Rao AS (1996) AgentSpeak (L): BDI agents speak out in a logical computable language. In: European workshop on modelling autonomous agents in a multi-agent world. Springer, Berlin/Heidelberg, S 42–55

    Google Scholar 

  • Riehle D (2000) Framework design: a role modeling approach. Dissertation, ETH Zürich

    Google Scholar 

  • Russell SJ, Norvig P (2016) Artificial intelligence: a modern approach. Pearson Education, Pearson Verlag, Boston Columbus Indianapolis

    Google Scholar 

  • Sun R, Merrill E, Peterson T (2001) From implicit skills to explicit knowledge: a bottom-up model of skill learning. Cogn Sci:203–244

    Google Scholar 

  • Tjahjono B, Esplugues C, Ares E, Pelaez G (2017) What does industry 4.0 mean to supply chain? Procedia Manuf:1175–1182

    Google Scholar 

  • Trunzer E, Cala A, Leitao P, Gepp M, Kinghorst J, Lüder A, Schauerte H, Reiferscheid M, Vogel-Heuser B (2019) System architectures for industrie 4.0 applications-derivation of a generic architecture proposal. Prod Eng:247–257

    Google Scholar 

  • Varga P, Blomstedt F, Ferreira LL, Eliasson J, Johansson M, Delsing J, Martínez de Soria I (2017) Making system of systems interoperable: the core components of the arrowhead framework. J Netw Comput Appl:85–95. https://doi.org/10.1016/j.jnca.2016.08.028

  • VDI/VDE. 2653 (2010) Agentensysteme in der Automatisierungstechnik. VDI/VDE, Berlin/Heidelberg

    Google Scholar 

  • VDI/VDE. 2653 (2013) Agentensysteme in der Automatisierungstechnik. VDI/VDE, Berlin/Heidelberg

    Google Scholar 

  • Vogel-Heuser B, Diedrich C, Pantforder D, Gohner P (2014) Coupling heterogeneous production systems by a multi-agent based cyber-physical production system. In: 12th International Conference on Industrial Informatics (INDIN). Porto Alegre, Brazil, S. 713–719

    Google Scholar 

  • Wang K (2016) Intelligent predictive maintenance (IPdM) system–industry 4. 0 scenario. WIT Trans Eng Sci:259–268

    Google Scholar 

  • Wooldridge MJ (2009) An introduction to multiagent systems, 2. Aufl. Wiley, Chichester

    Google Scholar 

  • Wooldridge M, Jennings NR, Kinny D (2000) The Gaia methodology for agent-oriented analysis and design. Auton Agent Multi-Agent Syst:285–312

    Google Scholar 

  • Wörn H, Brinkschulte U (2006) Echtzeitsysteme. Grundlagen, Funktionsweisen, Anwendungen. Springer, Berlin

    MATH  Google Scholar 

  • Ye X, Hong SH (2019) Toward industry 4.0 components: insights into and implementation of asset administration shells. IEEE Ind Electron Mag:13–25. https://doi.org/10.1109/MIE.2019.2893397

Download references

Author information

Authors and Affiliations

  1. Institut für Betriebsorganisation und Logistik, Technische Hochschule Ulm, Ulm, Deutschland

    Richard Verbeet & Hartwig Baumgärtel

Authors
  1. Richard Verbeet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hartwig Baumgärtel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Richard Verbeet .

Editor information

Editors and Affiliations

  1. Dortmund, Nordrhein-Westfalen, Germany

    Prof. Dr. Michael ten Hompel

  2. LS. AIS /MW, Technische Universität München, Garching b. München, Bayern, Germany

    Prof. Dr. Birgit Vogel-Heuser

  3. Stuttgart, Germany

    Thomas Bauernhansl

Section Editor information

  1. Lehrstuhl Automatisierung und Informationssysteme, Technische Universität München, Garching, Deutschland

    Birgit Vogel-Heuser

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature

About this entry

Verify currency and authenticity via CrossMark

Cite this entry

Verbeet, R., Baumgärtel, H. (2020). Implementierung von autonomen I4.0-Systemen mit BDI-Agenten. In: ten Hompel, M., Vogel-Heuser, B., Bauernhansl, T. (eds) Handbuch Industrie 4.0. Springer Reference Technik (). Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45537-1_130-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-45537-1_130-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45537-1

  • Online ISBN: 978-3-662-45537-1

  • eBook Packages: Springer Referenz Technik & Informatik

Chapter History

  1. Latest

    Implementierung von autonomen I4.0-Systemen mit BDI-Agenten
    Published:
    24 June 2021

    DOI: https://doi.org/10.1007/978-3-662-45537-1_130-2

  2. Original

    Implementierung von autonomen I4.0-Systemen mit BDI-Agenten
    Published:
    27 February 2020

    DOI: https://doi.org/10.1007/978-3-662-45537-1_130-1