Industrial Asset Monitoring With Fault Severity Prioritization
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Solution Overview
Problem
Existing process control systems in industrial facilities lack the ability to dynamically assess the severity of faults in industrial assets, leading to delayed corrective actions, inefficient resource allocation, and prolonged downtime due to the inability to prioritize maintenance based on fault severity.
Innovation Solution
A system and method that monitors operating parameters of industrial assets, assigns severity indexes based on deviation magnitude, integrates these indexes using data fusion techniques to generate fault severity indicators, and triggers corrective actions when thresholds are exceeded, enabling proactive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional process control systems monitor operating parameters, then fault detection is possible, but fault severity assessment capability is lacking leading to delayed corrective actions
Solution Approach 1:
The system transforms the monitoring approach by introducing severity indexes that quantify the magnitude of deviation from normal operating parameters. Instead of merely detecting whether a parameter is out of range, the system calculates severity indexes based on the extent of deviation, enabling prioritization of corrective actions and reducing response time for critical faults.
Solution Approach 2:
The fault severity indicator acts as an intermediary between raw operating parameter data and corrective action decisions. By integrating multiple severity indexes through data fusion operations, the system produces a comprehensive fault severity indicator that guides maintenance prioritization, bridging the gap between detection and actionable insights.
2Measurement precision
If comprehensive monitoring of all operating parameters is implemented, then fault detection accuracy improves, but system complexity increases
Solution Approach 1:
The system applies local quality by assigning specific severity indexes to individual operating parameters based on their deviation from normal ranges. Each parameter is evaluated independently with its own severity metric, allowing precise fault detection at the component level while maintaining manageable system complexity through modular assessment.
Solution Approach 2:
The system merges multiple severity indexes from different operating parameters into a unified fault severity indicator through data fusion operations. This integration consolidates information from numerous monitoring points into a single actionable metric, improving comprehensive fault detection accuracy while avoiding the complexity of managing each parameter separately.
3Reliability
If multiple operating parameters are monitored simultaneously, then comprehensive fault detection is achieved, but data processing complexity increases
Solution Approach 1:
The system segments the data processing task by first calculating individual severity indexes for each operating parameter independently. This segmentation allows parallel processing of multiple parameters without overwhelming computational complexity, as each parameter is assessed separately before integration.
Solution Approach 2:
The system performs preliminary action by pre-calculating severity indexes for each operating parameter before integrating them into the final fault severity indicator. This preliminary assessment of individual parameters simplifies the subsequent data fusion process, as the complex integration work is reduced to combining already-processed severity metrics rather than raw parameter data.
Data Source
AI summary
Examples techniques to manage performance of assets installed in an industrial facility are described. Operating parameters of a component from amongst one or more components of an asset are monitored. A range of values indicative of normal operational behavior of the asset is predefined for each operating parameter of the component. One or more operating parameters of the component are identified to deviate from corresponding predefined range of values. Deviation in an operating parameter is a symptom of a fault. A severity index is assigned to each symptom of a fault based on an amount of the deviation in the respective operating parameter from corresponding predefined range of values. Further, a fault severity indicator is assigned for the fault associated with the component based on severity indexes of each symptom of the fault. A corrective action is caused when the fault severity indicator is above a predetermined threshold.