Abstract
Traditional manufacturing solutions, based on centralized structures, are ineffective in unpredictable and volatile scenarios. Recent manufacturing paradigms, such as Holonic Manufacturing Systems, handle better these unpredictable situations but aren’t able to achieve the performance optimization levels displayed by the classical centralized solutions when the system runs without perturbations. This paper introduces a holonic manufacturing architecture that considers biological insights, namely emergence and self-organization, to achieve adaptation and responsiveness without degrading the performance optimization. For this purpose, self-organization and self-learning mechanisms embedded at micro and macro levels play an important role, as well the design of stabilizers to control the system nervousness in such dynamic and adaptive behaviour.
Chapter PDF
Similar content being viewed by others
Keywords
References
Ferber, J.: Multi-Agent System: An Introduction to Distributed Artificial Intelligence. Addison-Wesley Professional (1999)
Deen, S.: Agent-Based Manufacturing: Advances in the Holonic Approach. Springer, Heidelberg (2003)
Warnecke, H.J.: The Fractal Company. Springer, Heidelberg (1993)
Mehrabi, M.G., Ulsoy, G., Koren, Y.: Reconfigurable Manufacturing Systems: Key to Future Manufacturing. Journal of Intelligent Manufacturing 11(4), 403–419 (2000)
Ribeiro, L., Barata, J., Cândido, G., Onori, M.: Evolvable Production Systems: An Integrated View on Recent Developments. In: Huang, G.Q., Mak, K.L., Maropoulos, P.G. (eds.) DET2009 Proceedings. Advances in Intelligent and Soft Computing, vol. 66, pp. 841–854. Springer, Heidelberg (2010)
Koestler, A.: The Ghost in the Machine. Arkana Books (1969)
Leitão, P., Restivo, F.: ADACOR: a Holonic Architecture for Agile and Adaptive Manufacturing Control. Computers in Industry 57(2), 121–130 (2006)
Brussel, H., Wyns, J., Valckenaers, P., Bongaerts, L.: Reference Architecture for Holonic Manufacturing Systems: PROSA. Computers in Industry 37(3), 255–274 (1998)
Barbosa, J., Leitão, P., Trentesaux, D.: Bio-inspired Multi-Agent Systems for Re-configurable Manufacturing Systems, Engineering Applications of Artificial Intelligence, doi:10.1016/j.engappai.2011.09.025 (2012)
Leitão, P., Restivo, F.: Implementation of a Holonic Control System in a Flexible Manufacturing System. IEEE Transactions on Systems, Man and Cybernetics – Part C 38(5), 699–709 (2008)
Barbosa, J., Leitão, P.: Modelling and simulating self-organizing agent-based manufacturing systems. In: 36th Annual Conference on IEEE Industrial Electronics Society, pp. 2702–2707 (2010)
Leitão, P., Alves, J., Mendes, J.M., Colombo, A.W.: Energy Aware Knowledge Extraction from Petri Nets Supporting Decision-making in Service-oriented Automation. In: Proc. of the IEEE Int’l Symposium on Industrial Electronics, pp. 3521–3526 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Barbosa, J., Leitão, P., Adam, E., Trentesaux, D. (2012). Self-organized Holonic Manufacturing Systems Combining Adaptation and Performance Optimization. In: Camarinha-Matos, L.M., Shahamatnia, E., Nunes, G. (eds) Technological Innovation for Value Creation. DoCEIS 2012. IFIP Advances in Information and Communication Technology, vol 372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28255-3_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-28255-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28254-6
Online ISBN: 978-3-642-28255-3
eBook Packages: Computer ScienceComputer Science (R0)