Maintenance Routing via Digital Twin Asset Visualization
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Solution Overview
Problem
Conventional sensor systems in industrial facilities lack the capability to provide optimal maintenance routes and prioritize tasks effectively, leading to inefficient maintenance operations and potential cascading failures due to unknown conditions and lack of relational data analysis.
Innovation Solution
A method that uses a digital model to visualize facilities, determines preferred service routes and sequences, and updates the model with graphical content indicative of the service plan, including path optimization and constraint adjustments, to enhance maintenance planning and predict potential failure modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional sensor systems are used to monitor asset health, then fault detection capability is provided, but maintenance route optimization and task prioritization are lacking
Solution Approach 1:
The patent introduces a digital twin model as an intermediary between sensor systems and maintenance planning. This digital twin integrates facility layout, asset locations, and operational data to generate optimized maintenance routes and task sequences, thereby completing the information gap without requiring direct complex integration of all sensor systems
Solution Approach 2:
The system enables self-service by automatically generating maintenance plans, routing optimizations, and task prioritizations based on sensor data and digital twin models, reducing the need for manual maintenance planning and information synthesis
2Productivity
If service workers manually plan maintenance routes based on facility knowledge, then flexibility is maintained, but route optimization and access efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimal maintenance routes and task sequences based on facility layout and asset locations before maintenance operations begin. This allows workers to simply follow predetermined optimized paths without needing deep facility knowledge
Solution Approach 2:
The patent replaces the mechanical reliance on worker knowledge and manual route planning with an automated computational system that uses digital twin models and algorithms to determine optimal maintenance paths and sequences
3Loss of information
If conventional sensor systems output text logs of detected issues, then fault information is provided, but maintenance plan formulation burden remains on service workers
Solution Approach 1:
The system enables self-service by automatically generating complete maintenance plans, including route optimization and task sequencing, based on sensor data and digital twin models, eliminating the time burden on workers to manually formulate maintenance plans from text logs
Solution Approach 2:
The patent transforms the output format from simple text logs to structured data integrated with digital twin models, enabling automated analysis and plan generation. This parameter change in information representation allows the system to process and act on fault data automatically
4Loss of time
If workers navigate facilities without route optimization, then simplicity is maintained, but access time to assets increases
Solution Approach 1:
The system performs preliminary route calculation based on facility layout and asset locations before maintenance operations begin, providing workers with pre-optimized paths that minimize travel time without requiring complex real-time decision-making during maintenance
Data Source
AI summary
A method is disclosed for inspection or maintenance planning at a facility, including receiving a fault message indicating a fault associated with an asset of the facility, retrieving from a plant model database location data associated with the asset, generating a digital model illustrating the location in the facility of the asset, determining a preferred route for providing service to the asset, determining a preferred sequence for providing service to the asset, generating a service plan based on the preferred route and the preferred sequence, and updating the digital model to include graphical content indicative of the service plan.