Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Axel Börold"'
Publikováno v:
Machines, Vol 6, Iss 4, p 53 (2018)
In many current supply chains, transport processes are not yet being monitored concerning how they influence product quality. Sensor technologies combined with telematics and digital services allow for collecting environmental data to supervise these
Externí odkaz:
https://doaj.org/article/bf406378c447425292279d248e08f21c
Publikováno v:
IFAC-PapersOnLine. 53:10645-10650
Complex distributed supply chains, e.g., in the automotive industry, need to cope with high product variety. Digital image processing can use specific geometric and optical properties of parts and components for determining their type and thus needs
Publikováno v:
Procedia CIRP. 93:377-382
In the automotive industry, the ”completely knocked down” (CKD) business requires the identification and verification of a large number of unmarked parts. This is often a manual activity with a high risk of failure. Deep learning methods offer fl
Autor:
Axel Börold, Eike Broda, Nicolas Jathe, Dirk Schweers, Tobias Sprodowski, Waldemar Zeitler, Michael Freitag
Publikováno v:
Dynamics in Logistics ISBN: 9783031053580
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5fd0fabe9cff82aa5da659371adfc67
https://doi.org/10.1007/978-3-031-05359-7_37
https://doi.org/10.1007/978-3-031-05359-7_37
Autor:
Michael Freitag, Axel Börold
Publikováno v:
Procedia CIRP. 81:252-257
Industrial vehicles often operate in the same environment as employees do. Monitoring their environment in real-time is essential to prevent accidents and injuries to employees. Machine learning methods are well-suited for people detection, but they
Publikováno v:
Machines
Volume 6
Issue 4
Machines, Vol 6, Iss 4, p 53 (2018)
Volume 6
Issue 4
Machines, Vol 6, Iss 4, p 53 (2018)
In many current supply chains, transport processes are not yet being monitored concerning how they influence product quality. Sensor technologies combined with telematics and digital services allow for collecting environmental data to supervise these