An Influence Diagram Extension of the Unified Partial Method for Common Cause Failures

Abstract

Modelling Common Cause Failures (CCFs) is an essential part of risk analyses, especially for systems such as nuclear power plants, which are required to have high reliability. The Unified Partial Method (UPM) is the main approach of the UK for modelling CCFs. This paper presents an Influence Diagram model for CCFs which extends UPM and represents uncertainty on system performance. This allows more detailed modelling of CCFs in terms of root causes and coupling factors, creates a context for using information in the industry database, and captures the non-linearity in the way system defences influence reliability. A structured expert elicitation process is used to construct the Influence Diagram model and to identify the non-linear structure of the domain, using an example of Emergency Diesel Generators (EDGs) from nuclear power plants. Insights and experiences from the elicitation process are described.

Key Words:

• Common cause failures
• coupling factors
• epistemic uncertainty
• expert judgment
• influence diagram
• root causes
• Unified Partial Method

Additional information

Notes on contributors

Athena Zitrou

Athena Zitrou Has just submitted her PhD thesis in the Department of Management Science, University of Strathclyde, Glasgow. Her first degree is in Mathematics, and she holds an MSc in Operational Research. Her research interests are in the areas of risk assessment, expert judgment and decision making.

Tim Bedfor

Tim Bedford Professor of Decision and Risk Analysis in the Department of Management Science at the University of Strathclyde. His research interests are in reliability analysis, risk assessment and decision making. He is a Fellow of the Safety and Reliability Society in the UK and is on the Board of Directors of the European Safety Reliability and Data Association.

Lesley Walls

Lesley Walls Professor in the Department of Management Science at the University of Strathclyde. Her interests are in the areas of reliability data analysis and quality improvement. She is a Fellow of the Royal Statistical Society and an expert to the International Electrotechnical Committee, which has responsibility for reliability standards. Dr Walls has written numerous articles in the engineering and statistical literature.