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PT Notes

Addressing Enablers in LOPA

PT Notes is a series of topical technical notes on process safety provided periodically by Primatech for your benefit. Please feel free to provide feedback.

Layers of protection analysis (LOPA) is used to determine the risk of a hazard scenario by accounting for its initiating event, protection layers and consequence. Some practitioners account for enabling events and conditions that do not directly cause a hazard scenario but are required to be present or active for the scenario to proceed. They are important not only because they influence the risk of hazard scenarios but also because they make scenarios possible.

Other scenario elements also influence scenario risk. The term enablers is used here to encompass the following scenario elements:

  • Enabling events and conditions. Must be present or active for the scenario to proceed.
  • Management systems. Account for inadequacies in, and failure to follow, policies, procedures and work instructions.
  • At-risk factors. Account for the time period in which a process is at risk.
  • Incident outcomes. Used to represent different possible consequences for the same initiating event.
  • Release conditions. Used to account for different release conditions or circumstances.
  • Conditional modifiers. Affect the scenario consequence.
  • Given conditions (also called "givens"). Enable a scenario but are always present.

Commonly, enablers are key parts of hazard scenarios and often they are part of actual incidents. Their exclusion from consideration in LOPA can result in overly conservative results. Their inclusion in LOPA studies arguably produces more accurate risk estimates. Furthermore, the effort to include enablers is not substantial in comparison to the overall effort required to perform LOPA.

Many enablers act to reduce scenario risk because their likelihoods of occurrence multiply the scenario frequency. Likelihoods may be quite low and reduce risk significantly. Some enablers can increase the risk; for example, lack of preventive maintenance (PM) on equipment that increases its failure rate. In some cases, scenario consequences are also impacted and risk may be increased or decreased.

As for other failure data used in LOPA, the values used to incorporate the effect of enablers on scenario risk for processes should reflect actual experience with the processes. Judgment also may be needed as often data are sparse, but the values used should be justified with process data or expert opinion.

Typically, only enablers that may impact the scenario risk by more than a significant amount, such as an order of magnitude, are included in the analysis, e.g. if a disabled alarm that allows a scenario to occur is in a disabled state 10% or less of the time so that it reduces scenario likelihood by a factor of 10 or more, or if lack of PM on a vessel increases the likelihood of a corrosion failure by a factor of 10 or more. In some cases, enablers that together produce an order of magnitude risk reduction may be credited but care must be exercised as the credits taken may produce a non-conservative result owing to possible dependencies between enablers.

For enablers that represent two or more alternative scenario paths, if one path has a probability of occurrence of 0.5 or above, the enabler multiplier may be assumed to be 1 for convenience and conservatism. Generally, such multipliers are used when the effect on the scenario risk is substantial, i.e. when their probabilities are 0.1 or less.

Various enablers may combine together to reduce the risk of a hazard scenario substantially. However, multipliers for enablers should not be used arbitrarily to meet risk tolerance criteria. The temptation to convince oneself that an extra order of magnitude risk reduction is possible by reducing the value of the multiplier for an enabler by a factor of 10, or that an additional enabler that reduces the risk to a tolerable level should be credited, must be resisted unless they can be credibly justified. All data used in LOPA must be justified and should favor conservative values.

These issues are discussed in greater detail in the article:

Addressing enablers in layers of protection analysis, Process Safety Progress, Vol. 33, Issue 3, pages 221-226, September 2014.

Another reference source on the subject is the book:

Guidelines for enabling conditions and conditional modifiers in layer of protection analysis, AIChE / CCPS, New York, New York, 2013.

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For information on certification of personnel in LOPA click here.

For information on a related software tool click here.

Click on the links below for information on related training courses:

Layers of Protection Analysis (LOPA) for Process Safety

Safety Integrity Level (SIL) Determination Using LOPA and Other Methods

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