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Production Engineering

, Volume 7, Issue 2–3, pp 131–139 | Cite as

Validation of data fusion as a method for forecasting the regeneration workload for complex capital goods

  • Steffen C. Eickemeyer
  • Tim Borcherding
  • Sebastian Schäfer
  • Peter Nyhuis
Production Process

Abstract

The regeneration of complex capital goods is afflicted with a high degree of uncertainty. Neither the extent of the damage to the goods nor the resulting maintenance workload is known in advance, and that poses challenges for capacity planning. Data fusion in the form of Bayesian networks is used to prepare forecasts in order to estimate the workload in maintenance processes. The objective is to optimize the planability of the capacities required.

Keywords

Maintenance Capacity planning Data fusion Bayesian networks 

Notes

Acknowledgments

The authors would like to thank the DFG research organization for providing funding for this research project within the scope of the Collaborative Research Centres (CRC) 871.

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Copyright information

© German Academic Society for Production Engineering (WGP) 2013

Authors and Affiliations

  • Steffen C. Eickemeyer
    • 1
  • Tim Borcherding
    • 1
  • Sebastian Schäfer
    • 2
  • Peter Nyhuis
    • 1
  1. 1.Institute of Production Systems and Logistics (IFA), Hannover Centre for Production Technology (PZH)Leibniz University of HanoverHanoverGermany
  2. 2.Production Planning and ControlMTU Maintenance Hannover GmbHLangenhagenGermany

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