Besides IPLs, LOPA often uses two other kinds of factor. Both reduce the frequency, so both attract scrutiny.
Enabling conditions
The plant must be in a particular state for the cause to lead to the consequence. Examples:
- A reactor is in its exothermic phase 50 % of the batch cycle.
- The hazard exists only when a tank is being filled.
- Low ambient temperature needed for hydrate formation.
Rule of thumb: an enabling condition describes *when* the hazard exists, not *whether* a safeguard works.
Conditional modifiers
Applied after the release to reach the final consequence:
- probability of ignition,
- probability that a person is present (occupancy),
- probability that exposure is fatal.
They are allowed only if the company's tolerable frequency is defined for that final outcome (for example, fatality frequency), and only if the company rules permit them.
Double counting traps
- An occupancy factor and a TMEL that already assumes partial occupancy.
- Ignition probability applied for a toxic consequence.
- An enabling condition that is really the frequency of the operation already counted in the IEF ("transfers per year" in the IEF and "fraction of time transferring" as an enabling condition).
- A conditional modifier used to make a scenario "need no SIF" without challenge.
In First Out AI
The LOPA editor keeps enabling conditions and conditional modifiers in separate tables, and the frequency chart shows each factor, so a reviewer can see exactly how the MEF was reached.
Written for First Out AI as engineering guidance. It supports engineering work and does not replace it; check every value against your standards, certificates and company rules with a competent functional safety engineer.