BigPro – Use of Big Data Technologies for Fault Management in Production

The aim of the project BigPro is to enable resilient and reactive production systems through the use of a real-time capable big data platform with reactive and proactive fault management.

Within the projects, FZI researchers deal with the conception and implementation of services for the reactive and proactive fault detection as well as the dynamic fault correction.

The reactive and proactive fault detection aims, on the one hand, at forecasting faults already before they occur, by means of CEP technologies and thus enabling an intervention at an early stage, even before a fault shuts down the production and therefore causes costs. On the other hand, a dynamic pattern management shall be implemented in the framework of the fault detection, which automatically suggests potentially new fault patterns or identifies optimisation opportunities for already existing patterns and proposes them to the user. The creation and maintenance of fault patterns shall be simplified in this way.

In the case that the entered or impeding fault is recognised, the FZI also develops a dynamic fault handling, which generates and evaluates dynamic reaction recommendations for the correction of this fault, based on the current situation and proposes them to the user for the implementation.

Both components process data from various sources. This includes sensor and system data as well as the experiences and observations of employees, which can deliver valuable information that have not been taken into account for the context of sensor and system data.

(Source: FIR e. V. at RWTH Aachen University)

Project partners

  • Asseco Solutions AG
  • cognesys gmbh
  • DFA Demonstrationsfabrik Aachen GmbH
  • EICe Enterprise Integration Center Aachen GmbH
  • EML European Media Laboratory GmbH
  • FIR e. V. at RWTH Aachen University
  • i2solutions GmbH
  • Robert Bosch GmbH
  • Software AG
  • Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University

Further information

Duration: 01.09.2014-31.08.2017

Funded by: BMBF


Research Sector: Production and Logistics, Knowledge and Information Services

Contact person

Natalja Kleiner (Pulter)

Department Manager



Natalja Kleiner studied Computer Science at the University of Karlsruhe. The main focus of the studies was on Telematics and Information Systems. In her diploma thesis she worked on the evaluation of fuel consumption and emission on intersections, which are managed by agend based assistance systems.

Since July 2008 she works in the Department Information Process Engineering at FZI. The main research topic is disruption management in logistic networks

Focus of research and work:

  • Disruption Management in Logistic Networks
  • Flexible Payment System for Services
  • Quality Management


  • How Agents Can Help Curbing Fuel Combustion - a Performance Study of Intersection Control
    Year: 2011
    Authors/Eds.: Natalja Pulter, Heiko Schepperle, Klemens Böhm
    Type of publication:
    Proceedings of the 10th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-2011)
  • Managing Contingencies in Timed Transportation Networks by Agent Technology
    Year: 2010
    Authors/Eds.: Natalja Pulter, Jens Nimis, Peter C. Lockemann
    Type of publication: Proceeding
    Source: Proceedings of the Workshop on Artificial Intelligence and Logistics (AILog-2010) at the 19th European Conference on Artificial Intelligence (ECAI 2010), Lisbon, Portugal
  • Störungsmanagement in offenen, getakteten Logistiknetzen
    Year: 2010
    Authors/Eds.: Natalja Pulter, Jens Nimis, Peter C. Lockemann
    Type of publication: Article
    Source: KI - Künstliche Intelligenz, 24(2), p. 131-136

zu den Publikationen


Phone: +49 721 9654-844

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