Exponential Superimposed Renewal Processes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Superimposed renewal processes arise when the events from multiple renewal processes and all labels, which allow us to identify where they have come from, are missing. In reliability engineering, individual renewal processes are stochastic failure time models for components, and the superimposed renewal process from them is the model for the system failure times. Labels are the identity information of individual failures, such as the serial number of the failed component, or the most recent failure time. When these labels are missing, it is challenging to conduct statistical inference on renewal processes because of the loss of information on identities. Recently a likelihood-based method is proposed under the assumption that all renewal processes under a superimposed process are homogeneous. This paper discusses the argument used in the method and tries to extend it for heterogeneous cases.

Original languageEnglish
Title of host publication2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728171029
DOIs
Publication statusPublished - 2020 Aug
Externally publishedYes
Event2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020 - Vancouver, Canada
Duration: 2020 Aug 202020 Aug 23

Publication series

Name2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020

Conference

Conference2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
Country/TerritoryCanada
CityVancouver
Period20/8/2020/8/23

Keywords

  • component
  • EM algorithm
  • incomplete data
  • label missing
  • stationary renewal processes
  • superposition

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Modelling and Simulation

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