Publication:
Improved Domain Modeling for Realistic Automated Planning and Scheduling in Discrete Manufacturing

cris.virtual.departmentAutomatisierungstechnik
cris.virtual.departmentInformatik im Maschinenbau
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.departmentbrowseAutomatisierungstechnik
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseAutomatisierungstechnik
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtualsource.departmentd27eae86-6d38-489c-b4c3-2eed27fb81cc
cris.virtualsource.departmentf318ef77-db4b-4956-9a01-97eee1ab0454
cris.virtualsource.department#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.contributor.authorRogalla, Antje
dc.contributor.authorFay, Alexander
dc.contributor.authorNiggemann, Oliver
dc.date.issued2018-10-22
dc.description.abstractCurrent production planning and scheduling systems in automation do not meet the requirements of modern individualized production. Today's, static production processes impede customized manufacturing and small-scale production. A new way of thinking towards a dynamic control is required. This paper focuses on automated integrated process planning and scheduling on control level in discrete manufacturing. Existing algorithms in artificial intelligence planning are applied to solve process planning and scheduling problems. The challenge is to model the manufacturing system and products in a way that automated planners can generate efficiently process plans and schedules. Hence, based on a general classification of operations, different modeling options with regard to a successful automated process planning and scheduling are discussed. As a result, a domain modeling approach for discrete manufacturing is presented.
dc.description.versionNA
dc.identifier.doi10.1109/ETFA.2018.8502631
dc.identifier.isbn9781538671085
dc.identifier.issn1946-0740
dc.identifier.issn1946-0759
dc.identifier.scopus2-s2.0-85057238824
dc.identifier.urihttps://openhsu.ub.hsu-hh.de/handle/10.24405/14928
dc.language.isoen
dc.publisherIEEE
dc.relation.conferenceIEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), 04-07 September 2018, Turin, Italy
dc.relation.orgunitAutomatisierungstechnik
dc.rights.accessRightsmetadata only access
dc.titleImproved Domain Modeling for Realistic Automated Planning and Scheduling in Discrete Manufacturing
dc.typeConference paper
dcterms.bibliographicCitation.booktitle2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)
dcterms.bibliographicCitation.originalpublisherplacePiscataway
dspace.entity.typePublication
hsu.peerReviewed
hsu.uniBibliography
oaire.citation.endPage471
oaire.citation.startPage464
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