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Degradation modeling and reliability prediction of products with indicators influenced by clusters in a dynamic environment

Author

Listed:
  • Xin Wu
  • Tingting Huang
  • Kun Zhou
  • Wei Dai

Abstract

Modern products have tended to gain increasingly complex structures, and most of them have multiple dependent performance indicators (PIs), which makes the degradation modeling and reliability prediction of such products challenging. For some products, based on the design of the products, their PIs are influenced by some common underlying components called clusters in this paper, thus they are correlated. Besides, in engineering practice, products may suffer from a dynamic environment that causes difficulties in reliability analyses. To address these situations, this paper proposes a multivariate degradation model based on the Wiener process and establishes the correlation among the PIs in a flexible and intelligible way. The effect of the dynamic environment on the degradation rate is considered to be a multiplication form. The expectation-maximization (EM) algorithm is utilized to achieve an accurate estimation of the model parameters. The expression of the reliability function of the product is obtained by a tangent approximation approach. In the end, a simulation study and a case study are presented to demonstrate the effectiveness and application of the proposed model.

Suggested Citation

  • Xin Wu & Tingting Huang & Kun Zhou & Wei Dai, 2023. "Degradation modeling and reliability prediction of products with indicators influenced by clusters in a dynamic environment," Journal of Risk and Reliability, , vol. 237(1), pages 80-97, February.
    • Handle: RePEc:sae:risrel:v:237:y:2023:i:1:p:80-97
    DOI: 10.1177/1748006X221083417
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    References listed on IDEAS

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