Using LGM analysis to identify hidden contributors to risk in the operation of a nuclear power plant

Cherng G. Ding*, Hang Rung Lin, Chiu Hui Wu, Ten Der Jane

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

In this study, an approach is proposed to identify hidden contributors to risk in the operation of a nuclear power plant. Hypotheses linking safety performance to its influential factors are developed based on theory and literature. The failure to support the relational hypotheses with longitudinal safety performance data from a plant signifies hidden contributors to risk in the operation of the plant, which can be specifically identified by looking into the empirical results inconsistent with theoretical expectations. To demonstrate the use of the approach, we develop five hypotheses and analyze the longitudinal failure data for 28. years collected from 342 pumps in a large nuclear power plant by using latent growth modeling (LGM). The average trajectory of pump failures for the entire plant is inverted-U-shaped. Four hidden risk contributors in the operation of the sample plant have been identified. We suggest that, in addition to the adequacy of training and safety management systems, crew resource management be used to enhance nuclear safety for the sample plant. We recommend that the proposed approach be used for any other nuclear power plant to help identify hidden risk contributors and in other similar situations.

Original languageEnglish
Pages (from-to)64-71
Number of pages8
JournalSafety Science
Volume75
DOIs
StatePublished - 1 Jun 2015

Keywords

  • Crew resource management
  • Hidden risk contributors
  • Latent growth modeling
  • Safety climate

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