Causal Analytics in IIoT – AI That Knows What Causes What, and When
Figure 2: XMPro IoT Process Stream for rCA
analyses are automated at different time
intervals such as daily for high impact
equipment and weekly or monthly for other
areas. This is configurable by the end users
and ad hoc analysis can also be performed.
In this example, event data is ingested from
their
Honeywell®
historian
and
contextualized with asset data from their
IBM Maximo® EAM system. Further context
is provided from operational data stores.
This information is passed to the rCA Causal
Analytics AI algorithm that creates the causal
coefficient matrix and other outputs
described later in the article.
C USTOMER E XAMPLE : R CA IN O IL
AND G AS P ROCESSING
Background to the Application of rCA in Oil
& Gas
This automated, process-based approach
ensures repeatability, consistency and that it
can be done at scale for a large number of
assets in a process stream. The automated
process can process and analyze much larger
volumes of IoT data than human RCA
analysts. In the FPSO example different
The example demonstrates how rCA can
enable an FPSO to optimize production and
productivity as well as predict and avoid
incidents which threaten health, safety,
environment, community and financial
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June 2018