Proactive Fault Management by Big Data Usage
| Author: | Gregor Fuhs |
|---|---|
| Publisher: | FIR e. V. an der RWTH Aachen |
| Place of publication: | Aachen |
| Document Type: | Lecture |
| Language: | English |
| Date of Publication (online): | 2024/06/21 |
| Date of first Publication: | 2015/10/16 |
| Release Date: | 2025/09/10 |
| Tag: | Störungsmangement |
| GND Keyword: | Big DataGND |
| Page Number: | 21 Folien |
| Note: | BigPro: Big-Data and event-based adjustment for the configuration of resilient production systems
Project goal is the development of a Big Data platform including algorithms for data pattern detection to implement a proactivce disturbance management system in the production. Human data is considered as an additional data source. The disturbance management is further supported by an visualization of the disturbances and respective counteractions.
Duration: 01.09.2014 – 30.11.2017
Funding no.: 01IS14011
Funding: Bundesministerium für Bildung und Forschung (BMBF)
Promoters: DLR Projektträger
Project partners:
Asseco Solutions AG, Karlsruhe
AUTO HEINEN GmbH, Bad Münstereifel
cognesys gmbh, Aachen
DFA Demonstrationsfabrik Aachen GmbH, Aachen
EICe Aachen GmbH, Aachen
EML European Media Laboratory GmbH, Heidelberg
FZI Forschungszentrum Informatik am Karlsruher Institut für Technologie, Karlsruhe
i2solutions GmbH, Stolberg
Robert Bosch GmbH, Gerlingen-Schillerhöhe
Software AG, Darmstadt
Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Aachen |
| FIR-Number: | SV6606 |
| oral presentation: | Transfervortrag |
| congress: | Data Science: Theory and Application |
| place: | Aachen |
| Date of the presentation: | 16.10.2015 |
| Institute / Department: | FIR e. V. an der RWTH Aachen |
| Informationsmanagement | |
| Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften |
