Risk Assessment System Using Machine-Interpretable Semantics
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Solution Overview
Problem
Current risk modeling and assessment methods are inadequate for dynamically interacting systems, often requiring unrealistic uniform design methodologies, failing to assess external protective measures, and being limited by computational complexity and domain specificity, leading to inefficiencies and increased costs due to manual documentation and limited automation.
Innovation Solution
A system and method that automatically assesses safety and security compliance of industrial assets by mapping natural language risk descriptions to machine-interpretable semantics, using a modeling language based on set theory and type theory, enabling adaptive risk assessment and reduction, and integrating with existing workflows for improved speed and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual documentation methods are used for risk identification, then flexibility and adaptability to different systems are maintained, but labor intensity and human error increase
Solution Approach 1:
The system enables automated risk identification and assessment by having the system itself perform the documentation and analysis tasks that traditionally required manual human intervention. The automated system processes system specifications and generates risk assessments without requiring manual documentation, thereby reducing labor intensity while maintaining adaptability through configurable parameters and algorithms.
2Device complexity
If model-based engineering methods are used to integrate design and risk assessment, then a unified system view is achieved, but the ability to assess external protective measures is lost
Solution Approach 1:
The system separates the risk assessment function from the system design model, allowing independent evaluation of both internal system risks and external protective measures. By segmenting the assessment process into distinct modules that can independently analyze system specifications and protective measures, the system maintains the ability to assess external measures while still providing a comprehensive view when integrated with design information.
3Measurement precision
If formal modeling methods are used for risk assessment, then computational precision is improved, but computational complexity and resource requirements increase
Solution Approach 1:
The system transforms complex formal modeling problems into simplified parameter-based assessments by identifying and evaluating key risk parameters rather than performing exhaustive formal analyses. This approach maintains computational precision for critical parameters while reducing overall computational complexity through selective parameter evaluation and hierarchical assessment structures.
4Productivity
If automated risk assessment systems are implemented, then productivity and efficiency are improved, but the requirement for standardized methodologies increases
Solution Approach 1:
The system implements a universal risk assessment framework that can handle multiple assessment scenarios and methodologies through configurable parameters and modular components. The automated system maintains productivity by providing standardized processing while adapting to different assessment requirements through flexible configuration options, allowing the same system to accommodate various industry standards and methodologies without sacrificing efficiency.
Data Source
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AI summary
Disclosed are a system, method, and non-transitory computer readable medium to model risks and automatically evaluate safety and/or security compliance of a system under assessment (SUA). The disclosure is especially suited for an independent assessment of the SUA and does not form part of the SUA.