Publication: Collective intelligence for monitoring innovation and change in manufacturing industry
| dc.contributor.authors | Ayhan M.B., Aydin M.E., Oztemel E. | |
| dc.date.accessioned | 2022-03-28T15:01:34Z | |
| dc.date.accessioned | 2026-01-11T15:58:07Z | |
| dc.date.available | 2022-03-28T15:01:34Z | |
| dc.date.issued | 2012 | |
| dc.description.abstract | Change monitoring and management become an unavoidable necessity for companies in order to stay competitive in global market.This requires thorough handling models for change management to attain a systematic approach. In this paper, monitoring models for innovation and changes in manufacturing environments are investigated using two collective intelligence approaches. The first approach is based on a multi agent system designed in a tree-structured, where expert operational agents are strictly organised under sub-chair agents. The second approach uses a swarm intelligence approach, namely bee-colony algorithm to achieve collective intelligence for monitoring innovation and change across the manufacturing companies. © 2012 Newswood Limited. All rights reserved. | |
| dc.identifier.isbn | 9789881925220 | |
| dc.identifier.issn | 20780958 | |
| dc.identifier.uri | https://hdl.handle.net/11424/256805 | |
| dc.language.iso | eng | |
| dc.publisher | Newswood Limited | |
| dc.relation.ispartof | Lecture Notes in Engineering and Computer Science | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Change Management | |
| dc.subject | Collective Intelligence | |
| dc.subject | Innovation Monitoring | |
| dc.subject | Multi Agent Aystems | |
| dc.subject | Swarm Intelligence | |
| dc.title | Collective intelligence for monitoring innovation and change in manufacturing industry | |
| dc.type | conferenceObject | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 1400 | |
| oaire.citation.startPage | 1395 | |
| oaire.citation.title | Lecture Notes in Engineering and Computer Science | |
| oaire.citation.volume | 3 |