TY  - CONF
A1  - Stich, Volker
A1  - Oflazgil, Kerem
A1  - Schröter, Moritz
A1  - Jordan, Felix
A1  - Fuhs, Gregor Josef
A2  - Institute of Electrical and Electronics Engineers (IEEE), 
T1  - Big Data as an Enabler to Prevent Failures in the Production Area
T2  - 2016 IEEE International Conference on Knowledge Engineering and Applications - ICKEA 2016
N2  - Failure management in the production area has been intensely analyzed in the research community. Although several efficient methods have been developed and partially successfully implemented, producing companies still face a lot of challenges. The resulting main question is how manufacturers can be assisted by a sustainable approach enabling them to proactively detect and prevent failures before they occur. A high-resolution production system based on analyzed real-time data enables manufacturers to find an answer to the main question. In this context, Big Data technologies have gained importance since the critical success factor is not only to collect real-time data in the production but also to structure the data. Therefore, we present in this paper the implementation of Big Data technologies in the production area using the example of an actual research project. After the literature review, we describe a Big Data based approach to prevent failures in the production area. This approach mainly includes a real-time capable platform including complex event processing algorithms to define appropriate improvement measures.
KW  - Big Data
KW  - Produktionsmanagement
KW  - Störungsmanagement
Y1  - 2023
UR  - https://epub.fir.de/frontdoor/index/index/docId/3090
SN  - 978-1-5090-3472-7
SP  - 231
EP  - 236
PB  - IEEE
CY  - Piscatawa
ER  -