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Self-organization in manufacturing systems: challenges and opportunities

dc.contributor.authorLeitão, Paulo
dc.date.accessioned2010-01-24T13:41:15Z
dc.date.available2010-01-24T13:41:15Z
dc.date.issued2008
dc.description.abstractThe current need for flexibility, re-configurability and robustness are crucial reasons for moving to new distributed manufacturing paradigms. Approaches that inherit biological concepts, such as Holonic Manufacturing Systems and Reconfigurable Manufacturing Systems, address this challenge. The self-organization concept offers an alternative way of designing adaptive systems, in which autonomy, emergence and distributed functioning replace preprogramming and centralized control. This paper discusses the benefits that bio-inspired theories can bring to the manufacturing world, and analyzes why in spite of their promising perspective their adoption by industry is extremely rare.pt
dc.identifier.citationLeitão, Paulo (2008). Self-organization in manufacturing systems: challenges and opportunities. In 2nd International Conference on Self-Adaptive and Self-Organizing Systems and Workshops. Venice, Italy. p. 174-179. ISBN 978-0-7695-3553-1pt
dc.identifier.doi10.1109/SASOW.2008.40
dc.identifier.isbn978-0-7695-3553-1
dc.identifier.otherDOI: 10.1109/SASOW.2008.40
dc.identifier.urihttp://hdl.handle.net/10198/1429
dc.language.isoengpt
dc.publisherIEEEpt
dc.subjectSelf-organizationpt
dc.subjectManufacturing systemspt
dc.subjectBio-inspirationpt
dc.titleSelf-organization in manufacturing systems: challenges and opportunitiespt
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.endPage179pt
oaire.citation.startPage174pt
person.familyNameLeitão
person.givenNamePaulo
person.identifierA-8390-2011
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.orcid0000-0002-2151-7944
person.identifier.scopus-author-id35584388900
rcaap.rightsrestrictedAccesspt
rcaap.typeconferenceObjectpt
relation.isAuthorOfPublication68d9eb25-ad4f-439b-aeb2-35e8708644cc
relation.isAuthorOfPublication.latestForDiscovery68d9eb25-ad4f-439b-aeb2-35e8708644cc

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