Consistent Consequence Severity Estimation | AIChE

Consistent Consequence Severity Estimation

Type

Conference Presentation

Conference Type

AIChE Spring Meeting and Global Congress on Process Safety

Presentation Date

March 21, 2010

Duration

30 minutes

Skill Level

Intermediate

PDHs

0.50

LOPA, as a semi-quantitative analysis, often provides inconsistent results. This can be due to physical differences between units but often it is due to team's perceptual differences. Initiating event frequency evaluation using guidance tables is more consistent than consequence evaluation where qualitative expectations of severity dominate. Overstatement of the consequence severity creates excessive risk reduction requirements.

In response to this often seen issue, many proposed procedure modifications focus on adjusting the frequency of the event by invoking incident conditions that often cannot be verified by PHA/LOPA participants. An additional problem is that this often shifts the concept of the hazardous event from “loss of containment” to “harm.&' The shift of the analysis from prevention of release of highly hazardous chemicals to identifying potential &'luck factors&' results in the disengagement of operations personnel and disenfranchisement of process engineers. Industry is rapidly coming to consensus that these factors must be substantiated by documented justification.

Consequently, the challenge for many practioners of LOPA is how to achieve believable results from the LOPA without considering frequency factors that most team members are not qualified to estimate. LOPA can be substantially improved by implementing consequence estimation tools that assist team members in understanding the flammability, explosivity, and toxicity of process chemicals. This paper will discuss how a set of consequence estimation tables can be developed and implemented within a PHA/LOPA. Just as the frequency and risk reduction tables have greatly improved consistency of the hazardous event frequency, consequence tables can significantly increase the certainty in its estimate.

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