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

doi:10.1007/s11740-013-0444-8

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

MTU Maintenance

Research output: Contribution to journal › Article › Research › peer review

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.

Original language	English
Pages (from-to)	131-139
Number of pages	9
Journal	Production Engineering
Volume	7
Issue number	2-3
DOIs	https://doi.org/10.1007/s11740-013-0444-8
Publication status	Published - 1 Feb 2013

Keywords

Bayesian networks
Capacity planning
Data fusion
Maintenance

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

Access to Document

10.1007/s11740-013-0444-8

Cite this

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title = "Validation of data fusion as a method for forecasting the regeneration workload for complex capital goods",

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 = "Bayesian networks, Capacity planning, Data fusion, Maintenance",

author = "Eickemeyer, \{Steffen C.\} and Tim Borcherding and Sebastian Sch{\"a}fer and Peter Nyhuis",

note = "Funding information: 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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AU - Eickemeyer, Steffen C.

AU - Borcherding, Tim

AU - Schäfer, Sebastian

AU - Nyhuis, Peter

N1 - Funding information: 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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N2 - 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.

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KW - Capacity planning

KW - Data fusion

KW - Maintenance

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ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Collaborative Research Centre 871/2, sub-project D01: Capacity Planning and Coordination with Fuzzy Load Information

Collaborative Research Centre 871/2: Regeneration of Complex Capital Goods

Cite this

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Projects

Collaborative Research Centre 871/2, sub-project D01: Capacity Planning and Coordination with Fuzzy Load Information

Collaborative Research Centre 871/2: Regeneration of Complex Capital Goods

Cite this