The conflict between human and artificial
intelligence is a critical
issue, which has recently been introduced in Process System Engineering,
capturing the observation and action conflicts. Interpretation conflict
is another source of potential conflict that can cause serious concern
for process safety as it is often perceived as confusion, surprise,
or a mistake. It is intangible and associated with situation awareness.
However, interpretation conflict has not been studied with the required
emphasis. The current work proposes a novel methodology to quantify
interpretation conflict probability and risk. The methodology is demonstrated,
tested, and validated on a two-phase separator. The results show that
interpretation conflict is usually hidden, mixed, or covered by traditional
faults, and noises in observation and interpretation, including sensor
faults, logic errors, cyberattacks, human mistakes, and misunderstandings,
may easily trigger interpretation conflict. The proposed methodology
will serve as a mechanism to develop strategies to manage interpretation
conflict.