Process Planning and Decentralised Process Control for Cybertronic Production Systems

Abstract:

Cybertronic systems which augment mechatronic basis systems by means of communication, collaboration and intelligence are proposed to be utilised to develop next generation production systems. A model-based development process is proposed to enable integrated design and development of the product and the production system. This paper will highlight the importance of process planning as collaborative activity within the integrated design and development process. A concept will be introduced how process planning can be conducted for cybertronic production systems, considering decentralised production planning and control already during the design phase.

• Periodical: Applied Mechanics and Materials (Volume 794)
• Pages: 486-493
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.794.486
• Online since: October 2015
• Authors: Christian Weidig*, Chantal Sinnwell, Jan Christian Aurich
• Keywords: Cybertronic Production Systems, Product Development, Production Planning

References

[1] M. Chemnitz, J. Kruger, M. Patzlaff, E. -O. Tuguldur, SOPRO - Advancements in the Self-organising Production, Proceedings of the IEEE Conference on Emerging Technologies and Factory Automation (2010) 1-4.

DOI: 10.1109/etfa.2010.5641198

[2] M. Broy, E. Geisberger, Cyber-Physical Systems - Innovationsmotor für Mobilität, Gesundheit, Energie und Produktion (acatech POSITION), Springer, Heidelberg, (2011).

[3] M. Eigner, D. Roubanov, R. Zafirov, Modellbasierte, virtuelle Produktentwicklung, Springer, Berlin, (2014).

DOI: 10.1007/978-3-662-45874-7

[4] H. Meissner, M. Cadet, N. Stephan, C. Bohr, Model-Based Development Process of Cybertronic Products and Production Systems, Advanced Materials Research Vol. 1018 – Proceedings of the WGP Congress 2014 – Progress in Production Engineering, (2014).

DOI: 10.4028/www.scientific.net/amr.1018.539

[5] M. Eigner, J.C. Aurich, W. Koch, Cybertronische Produkte und Produktionssysteme - Konzept zur integrierten Entwicklung, Prductivity Management 18 (2013) 1, pp.17-20.

[6] G. Pahl, W. Beitz, Konstruktionslehre, Methoden und Anwendung erfolgreicher Produktentwicklung, 8th ed,. Springer Vieweg, Heidelberg, (2013).

DOI: 10.1007/978-3-642-29569-0

[7] S. Friedenthal, R. Steiner, A. Moore, A Practical Guide to SysML – The Systems Modeling Language, Morgan Kaufmann, San Francisco, (2009).

[8] Technical Operations International Council on Systems Engineering (INCOSE): Systems Engineering Vision (2007).

[9] W. Kühn, Digital Factory – Simulation enhancing the product and production engineering process, Proceedings of the 2006 Winter Simulation Conference, (2006), p.1899-(1906).

DOI: 10.1109/wsc.2006.322972

[10] A. Verl, A. Lechler, Steuerung aus der Cloud, in: T. Bauernhansel, M. ten Hompel, B. Vogel-Heuser (Eds. ), Industrie 4. 0 in Produktion, Automatisierung und Logistik, Springer, Wiesbaden, 2014, pp.235-248.

DOI: 10.1007/978-3-658-04682-8_12

[11] B. Scholz-Reiter, M. Görges, T. Philipp, Autonomously controlled production systems - Influence of autonomous control level on logistic performance, CIRP Annals - Manufacturing Technology 58 (2009), p.395–398.

DOI: 10.1016/j.cirp.2009.03.011

[12] J. Gausemeier, U. Frank, J. Donoth, S. Kahl, Specification technique for the description of self-optimizing mechatronic systems, Research in Engineering Design 20 (2009), pp.201-223.

DOI: 10.1007/s00163-008-0058-x

[13] T. Philipp, C. de Beer, K. Windt, B. Scholz-Reiter, Evaluation of Autonomous Logistic Processes - Analysis of the Influence of Structural Complexity, in: M. Hülsmann, K. Windt (Eds. ), Understanding Autonomous Cooperation & Control in Logistics - The Impact on Management, Information and Communication and Material Flow, Springer, Berlin, (2007).

DOI: 10.1007/978-3-540-47450-0_20

[14] J. D. Gehrke, O. Herzog, H. Langer, R. Malaka, R. Porzel, T. Warden, An Agent-based Approach to Autonomous Logistic Processes, Künstliche Intelligenz, 24 (2010), pp.137-141.

DOI: 10.1007/s13218-010-0027-1

[15] M. Rubenstein, A. Cornejo, R. Nagpal, Programmable self-assembly in a thousand-robot swarm, Science, 345 (2014) 6198, pp.795-799.

DOI: 10.1126/science.1254295

[16] C. Laue, Methodik für eine selbstoptimierende Produktionssteuerung, Forschungsberichte IWB, Band 238, PhD Thesis, Univeristy of Munich, (2010).

[17] E. L. McDuffie, M. Cristofari, F. Caron, M. Tronci, W.J. Wolfe, S.E. Sorensen, Scheduling Systems and techniques in Flexible Manufacturing Systems, CRC Press, Boca Raton, (2001).

DOI: 10.1201/9780429124303-7

[18] A. McKay, G. N. Stiny, A. de Pennington, Principles for the definition of design structures, International Journal of Computer Integrated Manufacturing (2015).

DOI: 10.1080/0951192x.2014.1003412

[19] VDI 2218: Information technology in product development -Feature Technology, Beuth, Düsseldorf, (2003).

[20] F. J. A. M. van Houten, PART: A Computer Aided Process Planning System, University of Twente, Enschde, (1991).

[21] X. Xun, W. Lihui, S.T. Newman, Computer-Aided Process Planning – A Critical Review of Recent Developments and Future Trends, International Journal of Computer Integrated Manufacturing, 24/1, (2011), p.1–31.

DOI: 10.1080/0951192x.2010.518632

[22] mecPro² – Modellbasierter Entwicklungsprozess cybertronischer Produkte und Produktionssysteme, Information on www. mecpro. de/static/kt1_en [20th March 2015].

DOI: 10.1007/978-3-662-55124-0_24