Bio-Inspired Self-Organising Methodologies for Production Emergence

Joao Dias Ferreira, Luis Ribeiro, Mauro Onori, Jose Barata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

With the emergence of new modern manufacturing paradigms new concepts, originally from the complexity sciences started to be introduced in the manufacturing systems, rendering traditional control approaches insufficient. Therefore, new approaches were developed, supported by the modern manufacturing paradigms bio-inspired background. However, somehow along the way the physical and logical nature of the system was partially lost, leading to the convergence of approaches towards more traditional systems, 'neglecting' their bio-inspired principles.

With the present work the authors aim to introduce and analyse two new different self-organising approaches that try to bring the focus of manufacturing systems, again to the bio-inspired principles. For this purpose, in the context of this work, manufacturing systems are approached from a bottom-up perspective, in an attempt to reduce the specification of the production processes to the minimum and foster the production emergence. A test case is considered, to draw initial conclusions.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
PublisherIEEE
Pages3835-3841
Number of pages7
ISBN (Print)978-076955154-8
DOIs
Publication statusPublished - 2013
Event2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom
Duration: 13 Oct 201316 Oct 2013

Publication series

NameIEEE International Conference on Systems Man and Cybernetics Conference Proceedings
PublisherIEEE
ISSN (Print)1062-922X

Conference

Conference2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Abbreviated titleSMC 2013
CountryUnited Kingdom
CityManchester
Period13/10/1316/10/13

Keywords

  • Self-Organisation
  • Emergence
  • Bio-Inspired
  • Multi-Agent Systems
  • Evolvable Production Systems
  • MANUFACTURING SYSTEMS
  • OPTIMIZATION
  • ARCHITECTURE

Cite this

Ferreira, J. D., Ribeiro, L., Onori, M., & Barata, J. (2013). Bio-Inspired Self-Organising Methodologies for Production Emergence. In Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 (pp. 3835-3841). [6722408] (IEEE International Conference on Systems Man and Cybernetics Conference Proceedings). IEEE. https://doi.org/10.1109/SMC.2013.655