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A Multi-level Trend-Renewal Process for Modeling Systems with Recurrence Data
Statistics Preprints
  • Zhibing Xu, Virginia Tech
  • Yili Hong, Virginia Tech
  • William Q Meeker, Iowa State University
  • Brock E. Osborn, GE Global Research Center
  • Kati Illouz, GE Global Research Center
Publication Date
4-1-2015
Series Number
Preprint #2015-01
Abstract
A repairable system is a system that can be restored to an operational state after a repair event. The system may experience multiple events over time, which are called recurrent events. To model the recurrent event data, the renewal process (RP), the nonhomogeneous Poisson process (NHPP), and the trend-renewal process (TRP) are often used. Compared to the RP and NHPP, the TRP is more flexible for modeling, because it includes both RP and NHPP as special cases. However, for a multi-level system (e.g., system, subsystem, and component levels), the original TRP model may not be adequate if the repair is effected by a subsystem replacement and if subsystem level replacement events affect the rate of occurrence of the component-level replacement events. In this paper, we propose a general class of models to describe replacement events in a multilevel repairable system by extending the TRP model. We also develop procedures for estimation of model parameters and prediction of future events based on historical data. The proposed model and method are validated by simulation studies and are illustrated by an industrial application.
Comments

This preprint was published as Zhibing Xu, Yili Hong, William Q. Meeker, Brock E. Osborn, and Kati Illouz, "A Multi-level Trend-Renewal Process for Modeling Systems with Recurrence Data".

Language
en
Citation Information
Zhibing Xu, Yili Hong, William Q Meeker, Brock E. Osborn, et al.. "A Multi-level Trend-Renewal Process for Modeling Systems with Recurrence Data" (2015)
Available at: http://works.bepress.com/wqmeeker/39/