• DocumentCode
    1161163
  • Title

    Composite importance measures for multi-state systems with multi-state components

  • Author

    Ramirez-Marquez, Jose E. ; Coit, David W.

  • Author_Institution
    Dept. of Syst. Eng. & Eng. Manage., Stevens Inst. of Technol., Hoboken, NJ, USA
  • Volume
    54
  • Issue
    3
  • fYear
    2005
  • Firstpage
    517
  • Lastpage
    529
  • Abstract
    This paper presents & evaluates composite importance measures (CIM) for multi-state systems with multi-state components (MSMC). Importance measures are important tools to evaluate & rank the impact of individual components within a system. For multi-state systems, previously developed measures do not meet all user needs. The major focus of the study is to distinguish between two types of importance measures which can be used for evaluating the criticality of components in MSMC with respect to multi-state system reliability. This paper presents Type 1 importance measures that are involved in measuring how a specific component affects multi-state system reliability. A Monte Carlo (MC) simulation methodology for estimating the reliability of a MSMC is used for computing the proposed CIM metrics. Previous approaches (Type 2) have focused on investigating how a particular component state or set of states affects multi-state system reliability. For some systems, it is not clear how to prioritize system component importance, collectively considering all of its states, using the previously developed importance measures. That detracts from those measures. Experimental results show that the proposed CIM can be used as an effective tool to assess component criticality for MSMC. Examples are used to illustrate & compare the proposed CIM with previous multi-state importance measures.
  • Keywords
    Monte Carlo methods; reliability theory; Monte Carlo simulation; composite importance measures; multi-state system reliability; Computational modeling; Computer integrated manufacturing; Current measurement; Degradation; Engineering profession; Monte Carlo methods; Power system reliability; Research and development management; State-space methods; Systems engineering and theory;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/TR.2005.853444
  • Filename
    1505057