Telecommunication Network Trouble Ticket Automation
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Solution Overview
Problem
Current fault management systems for network components rely heavily on human intervention, which can be inefficient and unreliable, especially when dealing with the high volume of alarms generated in network activities.
Innovation Solution
A system and method that utilize historical data to classify alarms, determine signatures, predict actions, and automate the process of assigning trouble tickets and actions, using a fault management platform that includes data stores, a processor, and an alarm process application to analyze and manage alarms based on their source and occurrence rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If human intervention is used to manage network alarms and fault resolution, then flexibility and adaptability in handling complex issues are improved, but productivity and efficiency deteriorate due to the high volume of alarms requiring manual processing
Solution Approach 1:
The system segments alarms into different categories based on their characteristics and assigns different handling approaches. Critical alarms requiring human intervention are separated from routine alarms that can be automatically resolved, enabling efficient processing of high-volume alarms while maintaining flexibility for complex issues.
Solution Approach 2:
The system implements self-service automation where the fault management platform automatically analyzes alarms, determines appropriate actions, executes resolution steps, and updates ticket statuses without human intervention for routine cases. This automates the self-resolution process while preserving human oversight for complex scenarios.
2Measurement precision
If more manual processes are used for fault management, then accuracy in handling complex situations is improved, but loss of time increases due to manual processing requirements
Solution Approach 1:
The system performs preliminary automated analysis and action execution for routine fault scenarios before human intervention is needed. By pre-configuring resolution workflows and automatically executing them for standard alarm patterns, the system eliminates time-consuming manual processing while maintaining accuracy through pre-validated procedures.
Solution Approach 2:
The system implements feedback mechanisms where automated actions are monitored and evaluated. When automated resolution actions are executed, their outcomes are tracked and fed back into the system to improve future automated decision-making, ensuring accuracy is maintained or improved over time while reducing manual processing time.
3Productivity
If automated processes are implemented for fault management, then productivity and speed of response are improved, but reliability may deteriorate due to potential automation errors
Solution Approach 1:
The system implements self-service automation with built-in validation and monitoring. Automated actions are executed only after confidence thresholds are met, and the system continuously learns from outcomes to improve reliability. Human operators remain available to review and correct automated decisions, ensuring reliability is maintained while preserving speed benefits.
Solution Approach 2:
The system replaces manual mechanical processes with automated electronic workflows that eliminate human error in routine operations. By substituting automated algorithms and decision-making systems for manual processes, the system improves speed and consistency while implementing monitoring mechanisms to detect and correct potential automation errors.
4Measurement precision
If comprehensive manual analysis is performed on all alarms, then measurement precision of alarm assessment is improved, but loss of time and productivity deteriorate due to processing volume
Solution Approach 1:
The system applies partial automated analysis to all alarms and reserves comprehensive analysis for alarms that exceed automated confidence thresholds. By performing automated preliminary assessment on the full alarm volume and applying more intensive analysis only when necessary, the system maintains precision for critical cases while dramatically reducing overall processing time.
Solution Approach 2:
The system segments alarm processing into multiple levels: automated preliminary analysis for all alarms, intermediate review for uncertain cases, and comprehensive manual analysis only for complex or critical alarms. This segmented approach maintains measurement precision where needed while minimizing time loss through automated handling of routine cases.
Data Source
AI summary
A system defining fault management actions for a network based on historical reference implemented by at least one computer. The system comprises the alarm process application stored in the memory. When executed by the processor, the alarm process application classifies the plurality of alarms that are stored in the alarm summary table based on which part of the network an alarm is from, scores a priority of each of the plurality of alarms based on the classification and a geographical location of an alarm, and determines a signature for some of the subset of the plurality of alarms to be stored in the matches table, wherein a signature is a set of column and value pairs that occur in alarm fields with an occurrence rate above a predefined threshold.