A load sharing system reliability model with managed component degradation

Research output: Contribution to journalArticle

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Abstract

Motivated by an industrial problem affecting a water utility, we develop a model for a load sharing system where an operator dispatches work load to components in a manner that manages their degradation. We assume degradation is the dominant failure type, and that the system will not be subject to sudden failure due to a shock. By deriving the time to degradation failure of the system, estimates of system probability of failure are generated, and optimal designs can be obtained to minimize the long run average cost of a future system. The model can be used to support asset maintenance and design decisions. Our model is developed under a common set of core assumptions. That is, the operator allocates work to balance the level of the degradation condition of all components to achieve system performance. A system is assumed to be replaced when the cumulative work load reaches some random threshold. We adopt cumulative work load as the measure of total usage because it represents the primary cause of component degradation. We model the cumulative work load of the system as a monotone increasing and stationary stochastic process. The cumulative work load to degradation failure of a component is assumed to be inverse Gaussian distributed. An example, informed by an industry problem, is presented to illustrate the application of the model under different operating scenarios.
Original languageEnglish
Pages (from-to)721-730
Number of pages10
JournalIEEE Transactions on Reliability
Volume63
Issue number3
Early online date22 Apr 2014
DOIs
Publication statusPublished - 22 Apr 2014

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Degradation
Random processes
Costs
Water
Industry

Keywords

  • cumulative work load
  • degradation failure
  • gamma process
  • load sharing system
  • managed degradation

Cite this

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A load sharing system reliability model with managed component degradation. / Ye, Zhisheng; Revie, Matthew; Walls, Lesley.

In: IEEE Transactions on Reliability , Vol. 63, No. 3, 22.04.2014, p. 721-730.

Research output: Contribution to journalArticle

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