DC Field | Value | Language |
---|---|---|
dc.contributor.author | Marks, Philipp | - |
dc.contributor.author | Weyrich, Michael | - |
dc.contributor.author | Hoang, Xuan Luu | - |
dc.contributor.author | Fay, Alexander | - |
dc.date.accessioned | 2020-02-26T15:23:31Z | - |
dc.date.available | 2020-02-26T15:23:31Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Enthalten in: 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation / IEEE International Conference on Emerging Technologies and Factory Automation 22.. - [Piscataway, NJ] : IEEE, c2017. - 2018, insges. 8 S. | - |
dc.description | Enthalten in: 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation / IEEE International Conference on Emerging Technologies and Factory Automation 22.. - [Piscataway, NJ] : IEEE, c2017. - 2018, insges. 8 S. | - |
dc.description.abstract | Automated manufacturing machines need to evolve in order to compete in nowadays turbulent manufacturing environment. This evolution process is achieved by performing different adaptations of the system, i.e. mechanical changes, changes of sensors and actuators, software changes, or a combination thereof. Currently, this adaptation process is mostly based on the experience of experts and is time-consuming and error-prone. This contribution proposes an approach that integrates tool support in the adaptation process to assist the engineer in the overall process. The approach uses a multi agent system in order to analyze production change requests and to generate and evaluate possible adaptation options for the machine based on a mechatronic model of the system including interdependencies between products, processes and resources on parameter-level. Thus, adaptation options can be generated on a fine-grained level. An illustrative example for the concept is given by the application on a modular production system. | - |
dc.description.sponsorship | Automatisierungstechnik | - |
dc.language.iso | eng | - |
dc.publisher | IEEE | - |
dc.title | Agent-based adaptation of automated manufacturing machines | - |
dc.type | Conference Object | - |
dc.relation.conference | 22nd International Conference on Emerging Technologies and Factory Automation (ETFA) 2017 | - |
dc.identifier.doi | 10.1109/ETFA.2017.8247572 | - |
dcterms.bibliographicCitation.originalpublisherplace | Piscataway, NJ | - |
dcterms.bibliographicCitation.booktitle | 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Limassol, Cyprus, 12.-15. Sept. 2017 | - |
local.submission.type | only-metadata | - |
dc.type.conferenceObject | Conference Paper | - |
hsu.opac.import | opac-2018 | - |
hsu.identifier.ppn | 1020750669 | - |
hsu.peerReviewed | ✅ | - |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
item.fulltext_s | No Fulltext | - |
item.openairetype | Conference Object | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Automatisierungstechnik | - |
crisitem.author.orcid | 0000-0002-1922-654X | - |
crisitem.author.parentorg | Fakultät für Maschinenbau und Bauingenieurwesen | - |
Appears in Collections: | 3 - Publication references (without fulltext) |
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