Automated CAP Report Analysis for Energy Facilities
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Solution Overview
Problem
Manual review of Corrective Action Program (CAP) reports in nuclear and regulated energy facilities is labor-intensive, resource-intensive, inconsistent, and prone to human error, leading to subjective assessment and variation in handling and remediation of negative conditions, which can compromise safety and compliance.
Innovation Solution
Implementing a system that uses trained machine-learning models to analyze CAP reports, identifying keywords, trends, and severity levels to automate the screening, prioritization, and remediation of negative conditions, ensuring consistent and accurate regulatory compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual review of CAP reports is used, then human judgment and flexibility are maintained, but labor intensity and resource consumption increase significantly
Solution Approach 1:
The patent introduces an automated analysis system as an intermediary between CAP report submission and human reviewer decision-making. The system processes reports, extracts key information, and generates preliminary assessments that human reviewers then evaluate, creating a layered approach that reduces manual labor while preserving human judgment for critical decisions.
Solution Approach 2:
The review process is segmented into distinct stages: automated initial screening, key information extraction, risk assessment, and final human review. This segmentation allows different types of tasks to be handled by appropriately suited methods, with routine analysis automated and complex judgment reserved for human reviewers.
2Adaptability or versatility
If manual review processes are used, then flexibility in handling diverse issues is maintained, but consistency and objectivity deteriorate due to subjective human assessment
Solution Approach 1:
The system transforms subjective human assessment parameters into objective, quantifiable metrics through automated analysis. By converting qualitative judgments into standardized parameters and applying consistent evaluation criteria, the system maintains adaptability to different issue types while ensuring uniform assessment standards across all reports.
Solution Approach 2:
The system implements feedback mechanisms where automated analysis results are continuously refined based on human reviewer corrections and outcomes. This creates a learning loop that improves consistency over time while maintaining the ability to adapt to new situations through updated evaluation criteria.
3Loss of information
If human reviewers assess CAP reports, then contextual understanding is achieved, but time consumption and operational costs increase
Solution Approach 1:
The system performs preliminary analysis of CAP reports before they reach human reviewers, extracting key contextual information, identifying critical issues, and preparing summary assessments. This preliminary action preserves essential contextual understanding while significantly reducing the time human reviewers need to spend on each report.
Solution Approach 2:
The system creates structured copies and representations of unstructured CAP report data, transforming narrative descriptions into standardized formats that retain contextual meaning while enabling efficient automated processing. This allows contextual information to be preserved and analyzed without requiring human reviewers to read and interpret raw text.
4Productivity
If automated systems are implemented, then processing speed and consistency improve, but complexity of the system increases
Solution Approach 1:
The patent designs a multi-functional automated system that performs multiple tasks including data extraction, risk assessment, trend analysis, and report generation within a single integrated platform. This universality improves processing speed across all functions while avoiding the complexity of multiple separate systems through centralized architecture.
Data Source
AI summary
Disclosed are techniques for evaluating a condition in a CAP report. The techniques can include receiving a CAP report from a computing device, extracting condition evaluation information from the CAP report based on structured and unstructured user-inputted information included in the CAP report to identify details regarding the condition in a regulated facility, retrieving models from a data store, each model being configured to use different portions of the conditions evaluation information to automatically assess different aspects of the condition, applying different portions of the extracted condition evaluation information to each model to generate assessments related to the condition, where each assessment includes a corresponding confidence value indicating a degree of certainty regarding an assessment's accuracy, determining at least one recommendation related to the condition based on the assessments and confidence values, and generating and transmitting output for the condition to the computing device.