DIV Deutscher Industrieverlag GmbH / Vulkan-Verlag GmbH


Big data analytics for proactive industrial decision support

Approaches and first experiences in the FEE Project

Autoren: Martin Atzmueller/University Of Kassel / Benjamin Klöpper/Abb Corporate Research Center Germany / Hassan Al Mawla/Abb Corporate Research Center Germany / Benjamin Jäschke/University Of Kassel / Martin Hollender/Abb Corporate Research Center Germany / Markus Graube/Technische Universität Dresden / David Arnu/Rapidminer / Andreas Schmidt/University Of Kassel / Sebastian Heinze/Technische Universität Dresden / Lukas Schorer/Abb Corporate Research Center Germany / Andreas Kroll/University Of Kassel / Gerd Stu

atp edition, vol. 58, no. 09, pp. 62-74, 2016

Veröffentlicht in atp edition

15,00 EUR

Seiten 62-74


Big data technologies offer new opportunities for analyzing historical data generated by process plants. The development of new types of operator support systems (OSS) which help the plant operators during operations and in dealing with critical situations is one of these possibilities. The project FEE has the objective to develop such support functions based on big data analytics of historical plant data. In this contribution, we share our first insights and lessons learned in the development of big data applications and outline the approaches and tools that we developed in the course of the project.

Schlagwörter: big data / data analytics / decision support

Title: Big data analytics for proactive industrial decision support

Subtitle: Approaches and first experiences in the FEE Project

Abstract: Big-Data-Technologien eröffnen neue Optionen zur Analyse historischer Anlagendaten in der Prozessindustrie. Eine Möglichkeit ist die Entwicklung neuer Operator-Unterstützungssysteme (OSS), die dem Anlagenfahrer im Betrieb und bei der Behandlung kritischer Situationen assistieren. Das Projekt FEE hat das Ziel, derartige Unterstützungsfunktionen basierend auf Big Data Analytics unter Nutzung historischer Anlagendaten zu entwickeln. In diesem Beitrag teilen wir erste Erfahrungen und Lessons Learned hinsichtlich der Entwicklung von Big-Data-Applikationen.Weiterhin stellen wir im Projektentwickelte Lösungsansätze und Werkzeuge dar.

Keywords: Big Data / Data Analytics / Entscheidungsunterstützung

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