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Gamma Degradation Models: Inference and Optimal Design

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Statistical Modeling for Degradation Data

Part of the book series: ICSA Book Series in Statistics ((ICSABSS))

Abstract

During the past two decades, degradation analysis has been widely used to assess the lifetime information of highly reliable products. Usually, random effect models and/or Wiener processes are well suited for modelling stochastic degradation. But in many situations, such as materials that lead to fatigue, it is more appropriate to model the degradation data by a gamma degradation process which exhibits a monotone increasing pattern. This article surveys the theoretical aspects as well as the application of gamma processes in degradation analysis. Some statistical properties of degradation models based on gamma processes under different tests are also given. Furthermore, the corresponding optimal designs for conducting the degradation experiments efficiently are reviewed. Finally, some extensions and their applications of gamma-process degradation model are presented.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada

    N. Balakrishnan

  2. Department of Mathematics, Tamkang University, Tamsui, Taiwan

    Chih-Chun Tsai & Chien-Tai Lin

Authors
  1. N. Balakrishnan
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  2. Chih-Chun Tsai
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  3. Chien-Tai Lin
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Corresponding author

Correspondence to N. Balakrishnan .

Editor information

Editors and Affiliations

  1. School of Social Work & Department of Biostatistics, Department of Statistics, University of North Carolina, University of Pretoria, Chapel Hill, North Carolina, USA

    Ding-Geng (Din) Chen

  2. Department of Mathematical Sciences, University of South Dakota, Vermillion, South Dakota, USA

    Yuhlong Lio

  3. Department of Statistical Science, Southern Methodist University, Dallas, Texas, USA

    Hon Keung Tony Ng

  4. Department of Statistics, Tamkang University, New Taipei City, Taiwan

    Tzong-Ru Tsai

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Balakrishnan, N., Tsai, CC., Lin, CT. (2017). Gamma Degradation Models: Inference and Optimal Design. In: Chen, DG., Lio, Y., Ng, H., Tsai, TR. (eds) Statistical Modeling for Degradation Data. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-5194-4_9

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