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<p>Component Importance Measure based on Birnbaums theory defines the measure considering independent component failure probability only. The assumption may be true in the case of the systems where s-identical redundant elements are not present. But in presence of such redundant elements ignoring the concept of Common Cause Failures or Dependent Failures may lead to a more optimistic result which may not be true in practical way. This paper has demonstrated the difference in estimating the component importance measure of different structured networks with and without incorporating effects of Common Cause Failures especially in cases of augmented networks. To validate the analysis, author has considered an existing optimized complex network with five subsystems and a series–parallel network with four subsystems. Some subsystems of these reconfigured optimized networks are consisting of multiple s-identical components. </p>

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Augmented networks component importance measure under common cause failures

  • 期刊论文

  • 发表日期：

    2025年7月24日

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  • Kalpana Hazarika,
  • Vikas Singh Bhadoria,
  • Manish Khemariya,
  • Vivek Shrivastava

摘要

Component Importance Measure based on Birnbaums theory defines the measure considering independent component failure probability only. The assumption may be true in the case of the systems where s-identical redundant elements are not present. But in presence of such redundant elements ignoring the concept of Common Cause Failures or Dependent Failures may lead to a more optimistic result which may not be true in practical way. This paper has demonstrated the difference in estimating the component importance measure of different structured networks with and without incorporating effects of Common Cause Failures especially in cases of augmented networks. To validate the analysis, author has considered an existing optimized complex network with five subsystems and a series–parallel network with four subsystems. Some subsystems of these reconfigured optimized networks are consisting of multiple s-identical components.