Big data analytics for proactive industrial decision support: Approaches and frst experiences in the FEE Project

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

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.

Details

Original languageEnglish
Pages (from-to)62-74
Number of pages13
JournalGWF, Wasser - Abwasser
Volume157
Issue number9
Publication statusPublished - 2016
Peer-reviewedYes

External IDs

ORCID /0000-0001-5165-4459/work/174432568

Keywords

DFG Classification of Subject Areas according to Review Boards

Subject groups, research areas, subject areas according to Destatis

ASJC Scopus subject areas

Keywords

  • Big data, Data analytics, Decision support