A HAZOP is a team-based process hazard analysis (PHA) method. Its purpose is to identify hazards and operability issues in a process design. In some HAZOPs, identified issues are evaluated for risk. An effective risk assessment method allows the HAZOP participants and the project team to focus their time and energy on the more significant hazards.
Risk assessments in HAZOPs are typically performed using a simple risk matrix (Figure 2). In the risk matrix approach, participants make judgments as to the potential severity and the likelihood of an event. The combination of severity and likelihood indicates the risk. The risk matrix will often be color coded with green areas (OK), red areas (Unacceptable) and yellow areas (improvement suggested, subject to ALARP).
This approach is problematic for a number of reasons:
The judgment of consequence severity is difficult and is often ambiguous. Any identified scenario could play out in multiple ways often with dramatically different severities.
Estimation of the frequency or likelihood of the event is also difficult; especially so if the frequency of the mitigated event is to be estimated.
The simple green, yellow, red bands do not provide sufficient resolution for ranking scenarios (the yellow band may span two or three orders of magnitude, for instance).
This paper presents a more rigorous and repeatable approach to making the severity and frequency judgments that is also simpler and quicker. The method is, in effect, a simplified layer of protection analysis (LOPA). The authors show how LOPA techniques can be simplified and applied in a HAZOP setting for both frequency and consequence severity judgments. These simplified techniques make such judgments more rigorous and repeatable. Also, because the guesswork is removed, this saves time in the HAZOP.
The proposed approach also yields a HAZOP record that is more easily used for a future LOPA study.
Number of Pages
American Institute of Chemical Engineers, 2001, Layer of Protection Analysis, Simplified Process Risk Assessment
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