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Performance Evaluation of Nonparametric Age Replacement Methods —Survey and Comparison —

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Stochastic Modelling in Innovative Manufacturing

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 445))

Abstract

In general, it is not easy to estimate the optimal maintenance strategies from actual lifetime data. Thus, some parametric and nonparametric methods have been independently developed in the literature. The main purpose of this article is to review several statistical age replacement methods and to compare their performance. Three cases are considered; parametric case, empirical case and IFR case. In each case, two kinds of methods are explained and examined throughout numerical experiments. Finally, we refer to the relationships between precision of the optimal replacement policy based on each method and the size of lifetime data.

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Author information

Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Hiroshima University, 4-1 Kagamiyama 1 chome, Higashi-Hiroshima, 739, Japan

    Tadashi Dohi, Takashi Aoki & Shunji Osaki

  2. Department of Management Science, Hiroshima Shudo University, 1717 Ohtsuka, Numata-cho, Asaminami-ku, Hiroshima, 731-31, Japan

    Naoto Kaio

Authors
  1. Tadashi Dohi
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  2. Takashi Aoki
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  3. Naoto Kaio
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  4. Shunji Osaki
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Salford, Salford M5 4WT, Lancs., UK

    Anthony H. Christer Ph.D.

  2. Department of Industrial and Systems Engineering, Hiroshima University, Higashi-Hiroshima, 739, Japan

    Shunji Osaki Ph.D.

  3. Department of Business Studies, The University of Edinburgh, William Robertson Building 50 George Square, Edinburgh, EH8 9JY, UK

    Lyn C. Thomas Ph.D.

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© 1997 Springer-Verlag Berlin Heidelberg

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Dohi, T., Aoki, T., Kaio, N., Osaki, S. (1997). Performance Evaluation of Nonparametric Age Replacement Methods —Survey and Comparison —. In: Christer, A.H., Osaki, S., Thomas, L.C. (eds) Stochastic Modelling in Innovative Manufacturing. Lecture Notes in Economics and Mathematical Systems, vol 445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59105-1_12

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  • DOI: https://doi.org/10.1007/978-3-642-59105-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61768-6

  • Online ISBN: 978-3-642-59105-1

  • eBook Packages: Springer Book Archive

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