Causal Analytics in IIoT – AI That Knows What Causes What, and When
outcomes. The initial field study project was
aimed at three key objectives:
The innovative solution and integrated
application suite enables interoperability of
data feeds from sensors and devices, with
the associated referential information from
the asset registry and maintenance
framework. It combines data from both IT
and OT and this new information provides
insights that can be shared collaboratively
between OT, IT and Operations. It makes
new levels of operational excellence,
collaboration and sustained productivity
improvements possible.
E FFICIENT O PERATIONS AND M AINTENANCE
This project will drive down the costs of
reduced or lost production caused by
unplanned failures. Other operational
efficiency gains will be achieved by reducing
the risks of environmental impact caused by
operational failure and the risks to personnel
safety caused by breaches of operational
standards. Furthermore, the costs of asset
maintenance will be reduced and the
capability of diagnosing asset health in
remote
and
challenging
operating
environments is increased.
The project mirrored an upstream oil and gas
process flow including value-added services
at each stage of the supply chain leveraging
real-time IoT big data, machine learning and
artificial intelligence.
S AFETY AND S OCIAL L ICENSE TO O PERATE
Going beyond the obvious elements that
cause an interruption to production, rCA is
used to find root causes and inter-
dependency which may be overlooked or
not realized with current technology. This
will enable the operations team onboard the
FPSO to keep it in production without
interruption for long periods and, when
down, to be repaired and brought on-stream
faster.
Equipment failure and/or an unsafe work
environment can potentially result in harm
to humans or the environment, ultimately
increasing operational risk and impacting an
organization’s social license to operate.
This solution will assist in providing a safe
production environment. In addition,
through to the inbuilt predictive analytics,
further eliminate operational risks which
could impact the social license to operate if
undetected and left uninvestigated and
unaddressed.
Most importantly, these improvements
reduce the risk of events that impact the
safety of all personnel on the FPSO and
protect the environment on the vessel and in
the geographic vicinity.
E NABLING E FFECTIVE C OLLABORATION
Traditionally there exists a significant divide
between the operational technology (OT) in
heavy asset sectors like Oil & Gas and the
information technology (IT) arena. Not only
are they typically separated by physical,
geographical and network constraints, they
are also generally isolated philosophically.
IIC Journal of Innovation
Project Background
The FPSO plant had experienced