Predict-It is a powerful analytical solution for OSIsoft PI
users that monitors the health of critical process equipment. Predict-It’s anomaly detection modules cover all
modes of operation, from start-up, through normal load,
and shut-down. Highly accurate anomaly detection and
correction of equipment degradation earlier in the development of faults help to keep your assets operating at
higher availability, reducing ancillary damage, minimizing
cost to repair while avoiding failures and lost revenue.
Advanced Pattern Recognition Module
Unlike products that monitor equipment using a first-principles approach, Predict-It employs Advanced Pattern
Recognition for early detection of significant events.
Modeling algorithms track trends in process variables on
a continuous basis and compare them to historical operation. This Digital Twin Technology acts as a virtual model
of an asset, creating a predicted trend that runs simultaneously with real-time equipment data.
Quickly changing conditions can cause deterioration of
mechanical assets, which will require additional a different type of monitoring. Predict-It’s Batch Module uses
Multivariant Data Analysis. MVDA provides a summary of
key variable influences, allowing faster interpretation and
interrogation of start-up, shut-downs, or batch processes.
Flagging batches, start-ups and shut-down that exceed
statistical limits shines a light on developing issues that
may not be seen during normal operation.
Diagnose Faults with Expertise
Once Predict-It detects an asset anomaly, engineers are
tasked with putting a plan in place for addressing that
situation. From compiling information on the anomaly
behavior to diagnosing a potential fault, Predict-It has
streamlined this process with the Diagnostic Reasoner
Module. The Diagnostic Reasoner unites the knowledge of
the Subject Matter Experts with a database of equipment
specific faults in a Bayesian framework, allowing differentiation and bringing clarity in scenarios that involve
uncertainty as an equipment issue evolves.
Diagnostic Reasoner Module
The Diagnostic Reasoner module capitalizes on the use
of Causal Asset Networks (CANs). CANs are designed for
the specific make and model of the assets they evaluate –
resulting in more precise diagnostic results. The Diagnostic Reasoner suggests multiple root causes for failures
and assigns exact probabilities for each outcome. CANs
can be configured by ECG, your reliability consultant, or
by your own subject matter experts, as well as purchased from
the ECG Fault Library. Capture the knowledge of an
SME within the Diagnostic Reasoner and never lose the
expertise of your most seasoned employees.
High Level Use Case
- Real Time Diagnosis
- Play out “What-If” Scenarios to support decision-making
- Differential Diagnosis helps to pinpoint equipment faults
- Shorten troubleshooting time
- Tailored Diagnostics for each asset manufacturer and mode
- Ability to assess multiple faults simultaneously
- ECG Fault Library provides quick time to value