Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
308 Learning about NPP Organizations through Root-Cause Analysis Using A-Catilac (PSAM-0400)
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Analysis of past incidents at Nuclear Power Plants (NPPs) has shown that incidents are typically caused by a combination of hardware failures and human actions, and that latent rather than active failures dominate. In addition, it is apparent from reviews of past event analyses that repeat-root-cause problems (for minor events) are fairly common. The goal of the root-cause analysis method presented in this paper is to help identify and correct latent conditions that create contexts for human errors, before they are revealed through incidents or accidents.
In this paper, we present the augmented CATILaC methodology. This methodology builds on extended root cause analyses for organizations, and the existing CATILaC (Computer-Aided Technique for Identifying Latent Conditions) approach and software. We take advantage of the fact that NPPs operate like machine bureaucracies, and analyze failures in terms of their locations within the organization — i.e., which program, which work process(es) (WP) within a program, which task within each work process, and so on. Furthermore, the approach presented here adds the dimension of the individual's perspective within the organization.
This approach provides a systematic way to guide root cause analysis to: (1) relate hardware failures to the operating organization and latent conditions within the organization; (2) relate latent conditions to organizational factors; (3) focus more explicitly on the decision-making perspective of individuals within the organization; (4) facilitate identifying more effective corrective actions to prevent repeat problems; (5) create an easily searchable summary database for the user.
The U.S. Nuclear Regulatory Commission's (NRC) Reactor Oversight Process (ROP) for NPPs collects a significant amount of information on NPP organizations through its inspection findings program. For example, the effectiveness of corrective action programs may be evaluated for licensees who have had risk-significant ROP inputs in either the performance-indicator or inspection areas. The augmented CATILaC method is demonstrated through application to some risk-significant inspection findings in the U.S. NRC's revised ROP.