Deploy across your Enterprise in Weeks
Predict-It’s architecture and solution capabilities allow end users to deploy the solution across your enterprise in a matter of weeks.
Predict-It leverages automated asset model building & training techniques for easy deployment, and innovative quality control reviews to ensure asset model accuracy from Day one.
ECG can also deploy the solution for you or we can train your personnel in less than 1 week to deploy the solution yourself.
Detect with Advanced and Customizable Technology
Predict-It is an agnostic, real time Equipment Health Monitoring Solution that provides your first line of defense to equipment issues by providing accurate anomaly detection of developing equipment issues.
Diagnose leveraging built-in Subject Matter Expertise
Predict-It’s Diagnostic Reasoner provides expert level of developing equipment anomalies through the use of equipment fault networks and Bayesian Network algorithms.
The Diagnostic Reasoner technology provides a probabilistic assessment of the most probable faults and provides an accelerated start to analyzing and resolving the noted issues.
Customer subject matter experts can be trained on how to program the Diagnostic Reasoner for your particular assets or pre-configured Diagnostic Networks can be purchased from ECG for your specific equipment types.
Monitor, Detect, Analyze, and Diagnose
Real Time Equipment Health Monitoring – 24/7 365 days a Year
Predict-It tracks trends in process variables on a continuous basis and compares them to the standard for the operation. In this way, the drift of the process variable toward unacceptable areas of
operation may be recognized and a potential future equipment issue, production derate, or forced shutdown can be avoided through timely notification and with preventive management steps.
The Predict-It Diagnostic Reasoner module further leverages Predict-It by providing a reasoning mechanism to assist engineers in root cause determination upon the earliest symptom detection.
The Diagnostic Reasoner includes a Causal Asset Network (CAN) framework and integrated Bayesian Network. This module maps Predict-It alarms to fault likelihoods through knowledge elicitation by
subject matter experts as well as case histories. The tool contains a Diagnostic Reasoner that can exercise the preconfigured network to preform “What If” scenarios. Preconfigured asset fault
networks for specific machine types can be provided by ECG to aid in a fast startup and expert monitoring solution.
The application aids personnel in reviewing potential problem areas and escalating those requiring further action. The robust and accurate models provide reliable information to engineers
and maintenance staff for reducing cost, increasing efficiency, and safety.