Abstract
To cope with dynamic changes and disturbances, manufacturing systems are required to have constant adaptability, agility, stability, self-organization, intelligence and robustness. By referencing the biological organization structure and mechanism, the concept of Bio-inspired Manufacturing System (BiMS) is proposed. The model of BiMS is presented to be composed of Bio-inspired Manufacturing Cells (BiMCs). Taking BiMS as a biological body, BiMC can be looked as the organ at different levels. Inspired by the ultra-short feedback mechanism of the natural neuro-endocrine system, the control and coordination mechanism between BiMCs is investigated, and a bio-inspiredself-adaptive manufacturing system control architecture is established based on the neuro-endocrine-immunity system (NEIS). Meanwhile, the pheromone communication mechanism has been used to improve the robustness of BiMS. A simulation platform has been set up to verify the functions of BiMS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ueda, K., Vaario, J., Ohkura, K.: Modeling of biological manufacturing systems for dynamic reconfiguration. Annals of the CIRP 46(1), 343–346 (1997)
Wiendahl, H.P., Scholtissek, P.: Management and control of complexity in manufacturing. Annals of the CIRP 43(2), 533–540 (1994)
Ryu, K., Jung, M.: Modeling and specifications of dynamic agents in fractal manufacturing systems. Computers in Industry 52(2), 161–182 (2003)
Brussel, H.V., Wyns, J., Valckenaers, P., et al.: Reference architecture for holonic manufacturing systems: PROSA. Computers in Industry 37(3), 255–274 (1998)
Iwata, K., Onosato, M.: Random manufacturing system: a new concept of manufacturing systems for production to order. Annals of the CIRP 43(1), 379–384 (1994)
Ueda, K.: A concept for bionic manufacturing systems based on DNA-type information. In: Proceedings of the 8th International Prolamin Conference, Tokyo, pp. 853–863 (1992)
Rao, Y.Q., Li, P.G., Shao, X., et al.: Agile manufacturing system control based on cell re-configuration. International Journal of Production Research 44(10), 1881–1905 (2006)
Farhy, L.S.: Modeling of oscillations of endocrine networks with feedback. Methods Enzymology 384, 54–81 (2004)
Liu, B., Ren, L.H., Ding, Y.S.: A novel intelligent controller based on modulation of neuro-endocrine system. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005, vol. 3498, pp. 119–124. Springer, Heidelberg (2005)
Keenan, D.M., Licinio, J., Veldhuis, J.D.: A feedback-controlled ensemble model of the stress-responsive. In: Hypothalamo-Pituitary-Adrenal Axis, vol. 98, pp. 4028–4033 (2001)
Liu, B., Ding, Y.S., Wang, J.H.: An intelligent controller based on ultra-short feedback of neuro-endocrine system. Computer Simulation 21(1), 188–191 (2008)
Keenan, D.M., Licinio, J., Veldhuis, J.D.: A feedback-controlled ensemble model of the stress-responsive hypothalamo-pituitary-adrenal Axis. PNAS 98(7), 4028–4033 (2001)
Xie, S.S.: Neuro-endocrine-immunity network. Science & Technology Review (8), 11–12, 64 (1994)
Liu, B.: Intelligent control system and application on bio-network architecture. Shanghai, Donghua University (2006)
Hu, G., Mu, X., Duan, H.Q., et al.: Interrelationship among immune nervous and endocrine systems. Progress in Veterinary Medicine 24(1), 5–7 (2003)
Dan, G., Lall, S.B.: Neuro-endocrine modulation of immune system. Indian Journal of Pharmacology 30, 129–140 (1998)
Dorigo, M., Dicaro, G.: Gambardella L M. Ant algorithms for discrete optimization. Artificial Life 5(3), 137–172 (1999)
Leitao, P., Restivo, F.: ADACOR: A holonic architecture for agile and adaptive manufacturing control. Computers in Industry 57(2), 121–130 (2006)
Leitao, P.: A Bio-inspired Solution for Manufacturing Control Systems. In: Azevedo, A. (ed.) IFIP International Federation for Information Processing. Innovation in Manufacturing, vol. 266, pp. 303–314. Springer, Boston (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tang, D., Wang, L., Gu, W., Yuan, W., Tang, D. (2010). Modelling of Bio-inspired Manufacturing System. In: Huang, G.Q., Mak, K.L., Maropoulos, P.G. (eds) Proceedings of the 6th CIRP-Sponsored International Conference on Digital Enterprise Technology. Advances in Intelligent and Soft Computing, vol 66. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10430-5_89
Download citation
DOI: https://doi.org/10.1007/978-3-642-10430-5_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10429-9
Online ISBN: 978-3-642-10430-5
eBook Packages: EngineeringEngineering (R0)