Exception-Based Route Planning for Fault-Triggered Asset Monitoring
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Solution Overview
Problem
In industries like oil and gas exploration and power generation, manually collecting sensor data from numerous machinery assets is labor-intensive and risky, especially in hazardous environments, leading to inefficiencies and safety concerns due to the need for frequent, comprehensive monitoring.
Innovation Solution
A condition monitoring system that dynamically determines a route plan to collect additional data only from assets exhibiting fault conditions, reducing the workforce exposure to hazardous environments and minimizing computing resources required for data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection is performed from each and every machine using a comprehensive route plan, then complete monitoring coverage is achieved, but workforce exposure to hazardous environments increases and safety risks escalate
Solution Approach 1:
The patent applies local quality by differentiating monitoring intensity across different machines based on their operational status. Instead of uniform monitoring, the system applies enhanced monitoring (high-resolution data collection) only to machines exhibiting fault conditions, while normal machines receive standard monitoring. This resolves the contradiction by maintaining complete monitoring coverage through selective focus on problematic assets rather than blanket comprehensive monitoring of all assets.
Solution Approach 2:
The patent implements partial action by performing data collection only on machines that require it based on fault conditions. The system collects high-resolution data partially (only when needed) rather than excessively (from every machine continuously). This allows complete monitoring coverage to be achieved through targeted partial monitoring of affected machines, reducing workforce exposure while maintaining reliability.
2Measurement precision
If high-resolution sensor data is collected from each and every asset, then fault diagnosis precision is improved, but computing resources required for data storage and processing increase significantly
Solution Approach 1:
The system applies local quality by varying data collection resolution based on the specific needs of each asset. High-resolution data collection is applied locally only to assets exhibiting fault conditions, while standard-resolution collection is used for normal assets. This maintains fault diagnosis precision for problematic assets while significantly reducing overall computing resource consumption across the entire fleet.
Solution Approach 2:
The patent implements partial action by collecting high-resolution data only partially (when fault conditions are detected) rather than continuously from all assets. This selective approach ensures adequate measurement precision for diagnosis when needed, while minimizing computing resource consumption during normal operation across the asset fleet.
3Use of energy by moving object
If lower-resolution data is collected to reduce processing requirements, then computing costs are reduced, but data fidelity becomes insufficient for precise fault condition assessment
Solution Approach 1:
The patent applies partial action by using low-resolution data for routine monitoring of normal assets (reducing computing consumption) while switching to high-resolution data collection partially (when fault conditions are detected). This dynamic adjustment ensures adequate measurement precision for fault diagnosis when required, while maintaining low computing resource consumption during normal operation.
Solution Approach 2:
The system implements dynamics by making data collection resolution adaptive rather than static. The monitoring system dynamically adjusts between low-resolution and high-resolution data collection based on real-time fault condition detection. This resolves the contradiction by allowing the system to optimize computing resource consumption during normal operation while ensuring measurement precision is available when fault conditions require it.
4Reliability
If comprehensive monitoring of all assets is performed on scheduled visits, then complete asset coverage is achieved, but productivity decreases due to labor-intensive manual data collection
Solution Approach 1:
The patent applies partial action by performing monitoring activities only on assets that require attention based on fault conditions. Instead of scheduling comprehensive visits to all assets, the system selectively monitors assets exhibiting problems. This maintains complete asset coverage through targeted partial monitoring, significantly improving productivity by eliminating unnecessary visits to normal assets while ensuring all assets remain under the monitoring system's purview.
Solution Approach 2:
The system implements self-service by enabling assets to effectively identify their own monitoring needs through embedded sensors that detect fault conditions. Assets that are functioning normally do not require manual intervention, while those with problems automatically trigger monitoring activities. This resolves the contradiction by achieving complete coverage through asset-driven selective monitoring, improving productivity by eliminating manual scheduling and visits to healthy assets.
Data Source
AI summary
Systems and methods are provided for determining a route plan identifying a list of assets for which additional sensor data is to be acquired. A condition monitoring system can be communicatively coupled to sensors which are interfaced to assets in a collection of assets. Accordingly, the assets can be monitored for fault conditions associated with operating parameters of the assets. Based on a fault condition alarm generated for an asset, route plan input can be received by the condition monitoring system. The route plan input can be processed to determine a route plan based on matching condition monitoring attributes in the route plan input with condition monitoring attributes associated with the assets in the collection of assets. The route plan can identify a list of assets for which additional sensor data can be collected.