Manufacturing Network Anomaly Detection via Hierarchical Segmentation
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Solution Overview
Problem
Manufacturing networks face challenges in quickly identifying and addressing root causes of anomalies, leading to costly downtime due to their complex tree-like topology and the potential for upstream node issues to affect many downstream nodes, making it difficult to predict and prevent node failures.
Innovation Solution
A data analytics platform is configured to monitor manufacturing networks at various levels of granularity, identifying macro-network, micro-network, node path, and individual node anomalies by evaluating operational metrics and presenting alerts to users, enabling timely identification and resolution of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manufacturing networks use a tree-like topology to connect numerous manufacturing assets, then communication and control capabilities are improved, but the complexity of identifying root causes of network problems increases significantly
Solution Approach 1:
The patent segments the manufacturing network into hierarchical levels (enterprise level, control level, device level) and further divides it into communication zones and segments. This segmentation allows administrators to isolate and analyze specific portions of the network, making root cause identification manageable despite the overall network complexity.
Solution Approach 2:
The patent introduces network administrators as intermediaries who use specialized tools and methodologies to analyze network segments. These administrators act as mediators between the complex network infrastructure and the need for problem diagnosis, using structured approaches to trace issues through the hierarchical topology.
2Stability of the object's composition
If the manufacturing network topology remains static once established, then network stability is improved, but the ability to quickly adapt to and respond to new problems decreases
Solution Approach 1:
The patent implements preliminary monitoring and analysis capabilities that continuously assess network health across all segments. By maintaining ongoing awareness of network conditions and potential issues, the system can quickly respond to new problems without requiring time-consuming topology changes or reconfigurations.
3Reliability
If upstream node problems affect many downstream nodes in the tree-like topology, then network connectivity is maintained, but the impact of a single failure amplifies across the network
Solution Approach 1:
The patent divides the network into isolated segments and zones, allowing administrators to contain failures within specific segments. This segmentation prevents upstream node failures from propagating throughout the entire network, as issues can be isolated to affected zones while other segments continue operating normally.
Solution Approach 2:
The patent implements monitoring and alerting systems that detect potential failures before they cascade through the network. By identifying upstream node issues early, the system can take preventive actions to stop failure propagation, cushioning the network against the full impact of single point failures.
4Measurement precision
If network administrators manually determine root causes of network problems, then detailed analysis is possible, but significant time is lost leading to costly downtime
Solution Approach 1:
The patent implements automated monitoring systems that continuously collect network data and provide feedback to administrators. This feedback mechanism supplies real-time information about network conditions, anomaly detection, and potential root causes, enabling administrators to make informed decisions quickly without manual investigation of every issue.
Solution Approach 2:
The patent enables the network monitoring system to automatically detect, analyze, and report potential issues without requiring constant administrator intervention. The system performs self-diagnosis functions, identifying anomalies and providing preliminary root cause analysis, which reduces the time administrators need to spend on manual problem determination while maintaining detailed analysis capabilities.
Data Source
AI summary
A computing system may evaluate the operation of a manufacturing network using at least two of (a) macro-level threshold criteria indicating anomalous operation of the manufacturing network as a whole, (b) micro-level threshold criteria indicating anomalous operation of any of a plurality of micro-networks in the manufacturing network, (c) path-level threshold criteria indicating anomalous operation of any of a plurality of node paths in the manufacturing network, or (d) node-level threshold criteria indicating anomalous operation of any of a plurality of individual nodes in the manufacturing network. Based on the evaluating, computing system may identify at least one anomaly in the manufacturing network and then trigger at least one action that is directed to resolving the at least one anomaly.