Industrial Equipment Impact Lists from Topology Graph Traversal
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Solution Overview
Problem
Existing industrial plants and processes face challenges in identifying and understanding the functional dependencies among equipment elements, particularly in complex networks where logical interdependencies are significant, which hinders effective maintenance and improvement efforts.
Innovation Solution
A method is introduced to generate an impact list of equipment elements affecting an industrial sub-process by traversing a topology model using a defined traversing strategy, adding elements with an affecting degree greater than a predefined threshold to the list, and utilizing machine learning for enhanced training and explainability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a comprehensive topology model of all equipment elements is analyzed to identify functional dependencies, then the completeness of dependency identification is improved, but the complexity of analysis and processing time increases significantly
Solution Approach 1:
The patent segments the comprehensive topology model into multiple sub-graphs based on spatial proximity and functional relationships. Each sub-graph contains a subset of equipment elements that are closely related, allowing for localized analysis rather than analyzing the entire plant-wide topology at once. This segmentation reduces the computational complexity while maintaining the ability to identify functional dependencies within each segment.
Solution Approach 2:
The patent applies partial action by focusing the analysis on equipment elements that meet specific selection criteria (spatial proximity, functional relationships) rather than analyzing all elements equally. The system performs exhaustive analysis only on relevant subsets of the topology model, achieving sufficient completeness for maintenance purposes without the overhead of analyzing every possible element combination.
2Measurement precision
If the traversing strategy analyzes all equipment elements in the topology model, then the completeness of impact identification is improved, but the time required for generating the impact list increases
Solution Approach 1:
The traversing strategy is applied separately to each sub-graph rather than to the entire topology model at once. This segmentation allows the system to process smaller, manageable portions of the data in parallel or sequentially, significantly reducing the time required for each traversal operation while collectively covering all relevant equipment elements.
Solution Approach 2:
The system applies different traversal depths and strategies to different sub-graphs based on their specific characteristics. Equipment elements that are more critical or have higher connectivity may receive more thorough analysis, while less critical elements receive shallower analysis. This local quality approach optimizes the balance between completeness and processing time for each region of the topology model.
3Measurement precision
If the impact list includes all equipment elements with any affecting degree, then the completeness of the list is improved, but the usefulness for maintenance decisions decreases due to information overload
Solution Approach 1:
The system changes the parameter of affecting degree from a binary inclusion/exclusion criterion to a continuous parameter that can be filtered and ranked. By quantifying the affecting degree and allowing users to set thresholds or sort by impact magnitude, the system transforms a potentially overwhelming list into a prioritized view that highlights the most significant equipment elements for maintenance attention.
Solution Approach 2:
The system provides the option to include all affecting elements in the complete impact list while simultaneously offering filtered views that show only the most significant elements. This partial action approach allows users to access the full completeness when needed while also having streamlined views for routine decision-making, avoiding information overload in normal operations.
Data Source
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AI summary
The invention relates to the field of industrial plants and processes, particularly for a method for maintaining and/or for improving the plants and processes. The method provides an impact list of affecting equipment elements that affect an industrial sub-process. The method comprises the steps of: selecting, in a topology model, the sub-process, wherein the sub-process is an equipment element that is a part of an industrial plant or process, and wherein the topology model is a graph, whose nodes represent equipment elements and whose edges represent interconnections between the equipment elements; traversing the nodes of the topology model, wherein the traversing starts from the selected sub-process and uses a traversing strategy; and for each of the at least one equipment elements, if the equipment element affects the industrial sub-process by an affecting degree greater than a first predefined affecting degree, adding the equipment element to the impact list of affecting equipment elements.