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

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• 作者：Steffen C. Eickemeyer (1)
  Tim Borcherding (1)
  Sebastian Sch盲fer (2)
  Peter Nyhuis (1)
  
• 关键词：Maintenance ; Capacity planning ; Data fusion ; Bayesian networks
• 刊名：Production Engineering
• 出版年：2013
• 出版时间：3 - April 2013
• 年：2013
• 卷：7
• 期：2
• 页码：131-139
• 全文大小：561KB
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• 作者单位：Steffen C. Eickemeyer (1)
  Tim Borcherding (1)
  Sebastian Sch盲fer (2)
  Peter Nyhuis (1)
  
  1. Institute of Production Systems and Logistics (IFA), Hannover Centre for Production Technology (PZH), Leibniz University of Hanover, Hanover, Germany
  2. Production Planning and Control, MTU Maintenance Hannover GmbH, Langenhagen, Germany
  
• ISSN：1863-7353

文摘

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.