Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Nikolai West"'
A requirement-driven approach for competency-based collaboration in industrial data science projects
Publikováno v:
International Journal of Production Management and Engineering, Vol 12, Iss 1, Pp 79-90 (2024)
The ongoing digitization of online learning resources has led to a proliferation of collaboration platforms for specific areas of application and disciplines. Simultaneously, especially manufacturing companies need to gain and secure knowledge in the
Externí odkaz:
https://doaj.org/article/ad63498064f84450bc2183d9af5cc641
Publikováno v:
International Journal of Production Management and Engineering, Vol 10, Iss 1, Pp 1-12 (2022)
Industrial Engineering, through its role as design, planning and organizational body of the industrial production, has been crucial for the success of manufacturing companies for decades. The potential, expected over the course of Industry 4.0 and th
Externí odkaz:
https://doaj.org/article/53c1aeae3e1a49128230ad9026caf306
Dieses Open Buch schlägt eine Brücke zwischen Theorie und Praxis für das produzierende Gewerbe im Zeitalter der Digitalisierung, der Industrie 4.0 und der Künstlichen Intelligenz. Es ist das Resultat eines vierjährigen Forschungsprojekts, das un
Publikováno v:
Journal of Software. :1-14
This paper presents the application of a Natural Language Processing (NLP) pipeline, which automatically extracts procedural knowledge in a standardized way from assembly instructions. The developed pipeline is able to parse and process written Germa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80e8b9a34d06ad4cdd6c295ea338f880
https://doi.org/10.17706/jsw.18.1.1-14
https://doi.org/10.17706/jsw.18.1.1-14
Publikováno v:
Journal of Process Control. 117:52-64
Manually defined control limits remain a common strategy for quality control in manufacturing due to their ease of deployment on the shop floor compared to more advanced data analysis approaches. Despite their continued importance, there is no system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::780121b40ba7f88d26129585af64ede1
https://doi.org/10.1016/j.jprocont.2022.07.002
https://doi.org/10.1016/j.jprocont.2022.07.002
Publikováno v:
Proceedings of Data Analytics and Management ISBN: 9789811976148
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82f0f83534e94df113455ec08bfe060e
https://doi.org/10.1007/978-981-19-7615-5_7
https://doi.org/10.1007/978-981-19-7615-5_7
Publikováno v:
Lecture Notes on Data Engineering and Communications Technologies ISBN: 9783031279140
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4d8c075dd91189b8b9e5115eeb639be
https://doi.org/10.1007/978-3-031-27915-7_12
https://doi.org/10.1007/978-3-031-27915-7_12
Publikováno v:
Procedia CIRP. 104:1547-1552
Anomaly detection in manufacturing systems has great potential for the prevention of critical quality faults. In recent years, unsupervised deep learning has shown to frequently outperform conventional methods for anomaly detection. However, tuning,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36d3c0231e5ac28d3b32d939878e6ef4
https://doi.org/10.1016/j.procir.2021.11.261
https://doi.org/10.1016/j.procir.2021.11.261
Improving the recall of information retrieval systems for similarity search in time series databases is of great practical importance. In the manufacturing domain, these systems are used to query large databases of manufacturing process data that con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27584500471e26fffc3345343aac126c
https://hdl.handle.net/10453/166941
https://hdl.handle.net/10453/166941
Autor:
Orheim, Nikolai West
Publikováno v:
Orheim, Nikolai West. Beamforming for condition monitoring. Master thesis, University of Oslo, 2017
Externí odkaz:
http://hdl.handle.net/10852/61513
https://www.duo.uio.no/bitstream/handle/10852/61513/5/Orheim_Nikolai_Master.pdf
https://www.duo.uio.no/bitstream/handle/10852/61513/5/Orheim_Nikolai_Master.pdf