Neural Network Hyperparameter Optimization for the Assisted Selection of Assembly Equipment
| dc.contributor.author | Hagemann, Simon | |
| dc.contributor.author | Sünnetcioglu, Atakan | |
| dc.contributor.author | Fahse, Tobias | |
| dc.contributor.author | Stark, Rainer | |
| dc.date.accessioned | 2021-04-20T16:13:41Z | |
| dc.date.available | 2021-04-20T16:13:41Z | |
| dc.date.issued | 2019-12-16 | |
| dc.description.abstract | The design of assembly systems has been mainly a manual task including activities such as gathering and analyzing product data, deriving the production process and assigning suitable manufacturing resources. Especially in the early phases of assembly system design in automotive industry, the complexity reaches a substantial level, caused by the increasing number of product variants and the decreased time to market. In order to mitigate the arising challenges, researchers are continuously developing novel methods to support the design of assembly systems. This paper presents an artificial intelligence system for assisting production engineers in the selection of suitable equipment for highly automated assembly systems. | en |
| dc.identifier.isbn | 978-1-7281-3998-2 | |
| dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/13058 | |
| dc.identifier.uri | http://dx.doi.org/10.14279/depositonce-11854 | |
| dc.language.iso | en | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject.ddc | 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten | de |
| dc.subject.other | artificial intelligence | en |
| dc.subject.other | assembly system design | en |
| dc.subject.other | automotive | en |
| dc.subject.other | body-in-white | en |
| dc.subject.other | neural network | en |
| dc.subject.other | hyperparameter optimization | en |
| dc.title | Neural Network Hyperparameter Optimization for the Assisted Selection of Assembly Equipment | en |
| dc.type | Conference Object | en |
| dc.type.version | acceptedVersion | en |
| dcterms.bibliographicCitation.doi | 10.1109/ICMECT.2019.8932099 | en |
| dcterms.bibliographicCitation.originalpublishername | Institute of Electrical and Electronics Engineers (IEEE) | en |
| dcterms.bibliographicCitation.originalpublisherplace | New York, NY | en |
| dcterms.bibliographicCitation.proceedingstitle | 2019 23rd International Conference on Mechatronics Technology (ICMT) | en |
| tub.accessrights.dnb | free | en |
| tub.affiliation | Fak. 5 Verkehrs- und Maschinensysteme::Inst. Werkzeugmaschinen und Fabrikbetrieb::FG Industrielle Informationstechnik | de |
| tub.affiliation.faculty | Fak. 5 Verkehrs- und Maschinensysteme | de |
| tub.affiliation.group | FG Industrielle Informationstechnik | de |
| tub.affiliation.institute | Inst. Werkzeugmaschinen und Fabrikbetrieb | de |
| tub.publisher.universityorinstitution | Technische Universität Berlin | en |