Cable Routing Simulator for Large-Scale Capital Projects
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Solution Overview
Problem
Large-scale capital projects face inefficiencies and high costs due to inefficient cable routing, which is complex and costly, especially in projects like power plants and offshore oil platforms, where hundreds of thousands of cables require precise management to minimize costs and logistical issues.
Innovation Solution
A simulator with a project modeler and cable router configures a virtual model of the project, using a routing manager to determine optimized cable routes and effectiveness ratios, identifying cables with significant deviations for re-routing, and a model controller to visually highlight inefficiencies, allowing for iterative improvements in cable layout.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If comprehensive plant design programs are used to manage large-scale capital projects, then project management capability is improved, but device complexity increases
Solution Approach 1:
The system segments cable routing management into distinct functional modules: a project modeler for creating virtual models, a cable router for automated cable layout, and a routing manager for optimization. This modular segmentation allows comprehensive project management while reducing overall system complexity through divided responsibilities.
Solution Approach 2:
The system performs preliminary actions by creating virtual models and simulating cable routes before actual construction. The cable router pre-calculates optimal paths and the routing manager pre-optimizes routes, allowing issues to be resolved in the virtual domain before physical implementation, thereby improving management capability while controlling complexity.
2Adaptability or versatility
If cable routing is manually configured in large-scale projects, then flexibility is maintained, but loss of time increases
Solution Approach 1:
The system combines dynamic manual adjustment capabilities with automated routing optimization. The cable router provides automated dynamic path calculation, while the routing manager allows dynamic re-optimization when design changes occur, maintaining flexibility while dramatically reducing routing time through automated processes.
Solution Approach 2:
The system implements feedback mechanisms where the routing manager continuously monitors cable routes and provides feedback for optimization. When design changes are made, the system automatically re-evaluates and re-optimizes routes, maintaining adaptability while reducing time loss through automated feedback-driven improvements.
3Ease of operation
If cable trays are used to direct cables, then cable organization is improved, but manufacturing precision requirements increase
Solution Approach 1:
The system performs preliminary placement of cable trays in the virtual model before finalizing cable routes. The project modeler pre-positions trays at optimal locations, and the cable router plans cable paths based on these pre-placed trays, reducing the need for high manufacturing precision during actual installation by resolving spatial relationships in advance.
Solution Approach 2:
The virtual model acts as an intermediary between cable tray placement and cable routing. The system first places trays virtually, then uses this virtual configuration as a mediator to plan cable routes, allowing organization to be optimized without requiring extremely precise physical manufacturing, as adjustments can be made in the virtual domain.
4Loss of substance
If cable routes are optimized to reduce cable length, then cost is reduced, but device complexity increases
Solution Approach 1:
The routing optimization function is segmented as a separate routing manager module that focuses specifically on length optimization. This segmentation allows cost reduction through optimized routing while containing optimization complexity within a dedicated module rather than spreading it throughout the entire system.
Solution Approach 2:
The routing manager performs self-service optimization by automatically calculating and optimizing cable routes to minimize length. The system serves itself by autonomously identifying and implementing shorter paths without requiring complex external intervention, reducing cable material cost while managing optimization complexity through automated self-optimization.
Data Source
AI summary
A large-scale capital project simulator has a project modeler configured to model the project as a virtual model having cable trays directing cables across the large-scale capital project. The simulator also has a cable router to lay out cables across the virtual model of the large-scale capital project. Each cable has a laid-out cable length. The simulator also has a routing manager to determine optimized routes of the cables across the virtual model. In this case, each cable has an optimized cable length along at least one of the optimized routes. The routing manager formulates an effectiveness ratio for each cable, where each effectiveness ratio uses the laid-out cable length and the optimized cable length. A filter determines whether any of the effectiveness ratios exceeds a prescribed deviation amount. A model controller transforms the virtual model to identify cable(s) exceeding the prescribed deviation amount.