Degradation Analysis with Measurement Errors

  • Chien-Yu Peng
  • Hsueh-Fang Ai
Conference paper
Part of the ICSA Book Series in Statistics book series (ICSABSS)


The lifetime information for highly reliable products is usually assessed by a degradation model. When there are measurement errors in monotonic degradation paths, non-monotonic model assumption can lead to contradictions between physical/chemical mechanisms and statistical explanations. To settle the contradiction, this study presents an independent increment degradation-based process that simultaneously considers the unit-to-unit variability, the within-unit variability, and the measurement error in the degradation data. Several case studies show the flexibility and applicability of the proposed models. This paper also uses a separation-of-variables transformation with a quasi-Monte Carlo method to estimate the model parameters. A degradation diagnostic is provided to evaluate the validity of model assumptions.



This work was supported by the Ministry of Science and Technology (Grant No: MOST-104-2118-M-001-007) of Taiwan, Republic of China. The authors would like to thank Ms. Ya-Shan Cheng for her assistance in the computations.


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Institute of Statistical ScienceAcademia SinicaTaipeiTaiwan

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