<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">050302</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.2007.05(3).351
</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Stochastic Diffusion Modeling of Degradation Data</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Tseng</surname>
            <given-names>Sheng-Tsaing</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">National Tsing-Hua University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Peng</surname>
            <given-names>Chien-Yu</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">National Tsing-Hua University</aff>
      </contrib-group>
      <volume>5</volume>
      <issue>3</issue>
      <fpage>315</fpage>
      <lpage>333</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: Accelerated degradation tests (ADTs) can provide timely relia bility information of product. Hence ADTs have been widely used to assess the lifetime distribution of highly reliable products. In order to properly predict the lifetime distribution, modeling the product’s degradation path plays a key role in a degradation analysis. In this paper, we use a stochastic diffusion process to describe the product’s degradation path and a recursive formula for the product’s lifetime distribution can be obtained by using the first passage time (FPT) of its degradation path. In addition, two approxi mate formulas for the product’s mean-time-to-failure (MTTF) and median life (B50) are given. Finally, we extend the proposed method to the case of ADT and a real LED data is used to illustrate the proposed procedure. The results demonstrate that the proposed method has a good performance for the LED lifetime prediction.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Accelerated degradation test</kwd>
        <kwd>degradation test</kwd>
        <kwd>stochastic diffusion process</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
