Big Data as an Enabler to Prevent Failures in the Production Area
- 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.
Author: | Volker Stich, Kerem Oflazgil, Moritz Schröter, Felix Jordan, Gregor Josef Fuhs |
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ISBN: | 978-1-5090-3472-7 |
Parent Title (English): | 2016 IEEE International Conference on Knowledge Engineering and Applications - ICKEA 2016 |
Publisher: | IEEE |
Place of publication: | Piscatawa |
Editor: | Institute of Electrical and Electronics Engineers (IEEE) |
Document Type: | Conference Proceeding |
Language: | English |
Date of Publication (online): | 2023/10/30 |
Date of first Publication: | 2016/09/30 |
Release Date: | 2024/06/07 |
Tag: | Big Data; Produktionsmanagement; Störungsmanagement |
First Page: | 231 |
Last Page: | 236 |
FIR-Number: | SV6738 |
Name of the conference: | 2016 IEEE International Conference on Knowledge Engineering and Applications |
place of the conference: | Singapore |
Date of the conference: | 28.09.-30.09.2016 |
Institute / Department: | FIR e. V. an der RWTH Aachen |
Informationsmanagement | |
Produktionsmanagement | |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften |