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Affiliation(s)

1. Conger Enterprises LLC, 4535 Ponte Vedra Drive, Marietta, GA 30067, USA
2. APOSS, Repovec 23B, Zabok 49210, Croatia

ABSTRACT

The paper discusses the framework for a risk-informed root cause analysis process. Such process enables scaling of the analysis performed based on the risk associated with the undesired event or condition, thereby creating tiers of analysis where the greater the risk, the more sophisticated the analysis. In a risk-informed root cause analysis process, a situation is normally not analyzed at a level less than what actually occurred. However, a situation may be investigated as though the consequence were greater than actually happened, especially if only slight differences in circumstances could result in a significantly higher consequence. While operational events or safety issues are normally expected to result only with negligible or marginal actual consequences, many of those would actually have certain potential to develop or propagate into catastrophic events. This potential can be expressed qualitatively or quantitatively. Risk-informing of root cause analysis relies on mapping the event or safety issue into a risk matrix which, traditionally, is a two-dimensional probability-consequence matrix. A new concept employed in the risk matrix for root cause analysis is that, while the probability reflects the observed or expected range of values (retaining, thus, its “traditional” meaning), the consequence reflects not only the observed or materialized impact (such as failure of equipment) but, also, its potential to propagate or develop into highly undesirable final state. The paper presents main elements of risk-informed root cause analysis process and discusses qualitative and quantitative aspects and approaches to determination of risk significance of operational events or safety issues.

KEYWORDS

Root cause, risk-inform, risk, probability, cause analysis, safety precedence, significance determination, risk matrix, probabalistic margin, conditional probability, conditional risk, analyst, training, methods.

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