Failure Prediction System Using Text Analytics

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Solution Overview

Problem

The increasing complexity of computer systems makes it difficult to fully test interactions between hardware and software components, leading to costly downtime and delays due to potential failures.

Innovation Solution

A failure detection system that analyzes current and historical information to predict future failures by using text analytics algorithms to identify causal factors in event data, allowing for proactive measures to prevent outages and disruptions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If computer systems increase in complexity to provide more functionality, then system capability and versatility improve, but the potential for failures and difficulty in testing interactions increases

Engineering Contradiction:

Improvesystem capabilityVSAvoidfailure potential

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary analysis of event data using text analytics algorithms to identify causal factors before failures occur. By proactively detecting patterns in historical and current event data, the system predicts potential failures and enables preventive actions, thus improving reliability while maintaining system complexity.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If comprehensive testing of hardware and software component interactions is attempted, then failure detection capability improves, but testing complexity and resource requirements increase

Engineering Contradiction:

Improvefailure detection capabilityVSAvoidtesting complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces traditional mechanical/manual testing methods with automated text analytics algorithms that process event data. This substitution enables comprehensive failure detection without proportionally increasing testing complexity, as the automated system can analyze multiple data sources simultaneously to identify causal factors.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces event data as an intermediary between system operations and failure detection. By analyzing event data that captures system behavior, the system indirectly detects potential failures without directly testing all component interactions, thus improving detection capability while managing complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Device complexity

If traditional reactive failure response is used, then system simplicity is maintained, but downtime and operational delays increase

Engineering Contradiction:

Improvesystem simplicityVSAvoiddowntime

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The system performs preliminary prediction of failures by analyzing patterns in event data before actual failures occur. This enables administrators to take preventive actions ahead of time, significantly reducing downtime and operational delays while maintaining relatively simple system architecture through automated analysis.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11231984B1Failure prediction system

Publication Date: 2022.01.25 WELLS FARGO BANK NA

AI summary

Among other things, embodiments of the present disclosure can help improve the functionality of failure prediction systems by identifying potential future failure events in a hardware or software component based on an analysis of current and historical information for the system. Embodiments of the present disclosure may use historical data associated with past technology failures to identify causal factors identified in current event data to help predict future outages and disruptions.