Advertisement

Prototyping in Research Domains: A Prototype for Autonomous Production Logistics

  • Farideh Ganji
  • Marius Veigt
  • Bernd Scholz-Reiter
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 282)

Abstract

The employment of simulation tools is the established method to analyze and validate research results. Generally, simulation tools can represent certain key characteristics or behaviors of a selected real-life or abstract system. However, these tools simplify approximations and assume relevant information. Today, most research areas are interdisciplinary. Therefore, the presentation and validation of collective results are a difficult challenge. Demonstrators and prototypes consider these difficulties and relevant factors, which can range from determining the required data sources to the employment of technological devices. The research domain “Autonomous Logistics” is such an interdisciplinary research domain, which focuses on the decentralization of decision-making processes. The showcase demonstrator “factory of autonomous products” is a development of this research domain. This paper introduces this showcase from the demonstrator perspective and proves the benefits.

Keywords

Simulation Demonstrator Prototype Autonomous Logistics 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Sokolowski, J.A., Banks, C.M.: Principles of Modeling and Simulation: A Multidisciplinary Approach. John Wiley & Sons, Hoboken (2009)zbMATHGoogle Scholar
  2. 2.
    Sherman, W.R., Craig, A.B.: Understanding Virtual Reality. Morgan Kaufmann, San Francisco (2003)Google Scholar
  3. 3.
    Davidsson, P.: Multi Agent Based Simulation: Beyond Social Simulation. In: Moss, S., Davidsson, P. (eds.) MABS 2000. LNCS (LNAI), vol. 1979, pp. 97–107. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Van Dyke Parunak, H., Savit, R., Riolo, R.L.: Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users’ Guide. In: Sichman, J.S., Conte, R., Gilbert, N. (eds.) MABS 1998. LNCS (LNAI), vol. 1534, pp. 10–25. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  5. 5.
    Hülsmann, M., Windt, K.: Understanding Autonomous Cooperation and Control in Logistics: The Impact of Autonomy on Management, Information, Communication and Material Flow. Springer, Berlin (2007)CrossRefGoogle Scholar
  6. 6.
    Scholz-Reiter, B., Hildebrandt, T., Kolditz, J., Höhns, H.: Selbststeuerung in der Produktion – ein Modellierungskonzept. Ind. Manag. 21(4), 33–36 (2005)Google Scholar
  7. 7.
    Wiendahl, H.-P., Gers, D., Keunecke, L. (eds.): Variantenbeherrschung in der Montage: Konzept und Praxis der flexiblen Produktionsendstufe. Springer, Berlin (2004)Google Scholar
  8. 8.
    Scholz-Reiter, B., Windt, K., Kolditz, J., Böse, F., Hildebrandt, T., Philipp, T., Höhns, H.: New Concepts of Modelling and Evaluating Autonomous Logistics Processes. In: Chryssolouris, G., Mourtzis, D. (eds.) Manufacturing, Modelling, Management and Control 2004. IFAC Workshop Series, Elsevier Science, Amsterdam (2005)Google Scholar
  9. 9.
    Windt, K., Jeken, O.: Allocation Flexibility – A New Flexibility Type as an Enabler for Autonomous Control in Production Logistics. In: 42nd CIRP Conference on Manufacturing Systems, Grenoble (2009)Google Scholar
  10. 10.
    Meyer, G.G., Främling, K., Holmström, J.: Intelligent products: A survey. Comput. Ind. 60(3), 137–148 (2009)CrossRefGoogle Scholar
  11. 11.
    Kirn, S., Herzog, O., Lockemann, P., Spaniol, O. (eds.): Multiagent Engineering: Theory and Applications in Enterprises. Springer, Berlin (2006)Google Scholar
  12. 12.
    Hackstein, R.: Produktionsplanung und -steuerung (PPS) – Ein Handbuch für die Betriebspraxis. VDI-Verlag, Düsseldorf (1989)Google Scholar
  13. 13.
    Scholz-Reiter, B., Görges, M., Philipp, T.: Autonomously controlled production systems – Influence of autonomous control level on logistic performance. CIRP Ann. Manuf. Technol. 58, 395–398 (2009)CrossRefGoogle Scholar
  14. 14.
    Ganji, F., Morales Kluge, E., Scholz-Reiter, B.: Bringing Agents into Application: Intelligent Products in Autonomous Logistics. In: Artificial Intelligence and Logistics (AILog) – Workshop at ECAI 2010 (2010)Google Scholar
  15. 15.
    Pille, C.: Produktidentifikation, Intralogistik und Plagiatschutz – RFID-Integration in Gussbauteile. In: BDG-Fachtagung Gussteilkennzeichnung. Methoden und Datenmanagement – Praxisberichte, pp. V/1–V/4. VDG Akademie, Essen (2010)Google Scholar
  16. 16.
    Foundation for Intelligent Physical Agents (Fipa): Standard Status Specifications, http://www.fipa.org/repository/standardspecs.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Farideh Ganji
    • 1
  • Marius Veigt
    • 1
  • Bernd Scholz-Reiter
    • 1
  1. 1.BIBA, Bremer Institut für Produktion und Logistik GmbHUniversity of BremenBremenGermany

Personalised recommendations