Component Fault and Deficiency Tree Modeling for AI/ML Hazards
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Solution Overview
Problem
Traditional safety analysis techniques for safety-critical systems, such as Fault Tree Analysis and Component Fault Trees, fail to adequately address functional insufficiencies and deficiencies in AI/ML-based systems, leading to insufficient hazard mitigation and risk assessment.
Innovation Solution
A computer-implemented method for generating a Component Fault and Deficiency Tree (CFDT) that incorporates both failures and deficiencies, using a tree structure with internal fault tree logic and mitigation logic to model cause-effect relationships and provide safety analysis techniques for AI/ML-based systems, extending traditional CFTs to include functional insufficiencies and system hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional Component Fault Tree methods are used for safety analysis, then hardware and software failures can be modeled, but functional insufficiencies and deficiencies in AI/ML-based systems cannot be adequately addressed
Solution Approach 1:
The patent segments the safety analysis model into distinct components: traditional failure modes (hardware/software failures) and new deficiency modes (functional insufficiencies). This segmentation allows the CFDT to handle both conventional and AI/ML-specific safety concerns separately while maintaining a unified analysis framework, thereby improving adaptability to AI/ML systems without compromising reliability modeling capabilities.
Solution Approach 2:
The patent adds a new dimension to the traditional fault tree analysis by introducing deficiency events as a separate category alongside failure events. This dimensional expansion allows the model to capture functional insufficiencies in AI/ML systems that traditional binary failure models cannot represent, thus enhancing versatility while maintaining the structural integrity needed for reliability analysis.
2Object-affected harmful factors
If traditional Fault Tree_analysis is applied to AI/ML systems, then failure pathways can be identified, but functional insufficiencies leading to hazards cannot be sufficiently mitigated
Solution Approach 1:
The patent implements preliminary action by introducing deficiency events that proactively identify functional insufficiencies before they lead to actual hazards. The CFDT model allows deficiency events to be defined and analyzed in advance, enabling preventive measures to be taken against functional shortcomings in AI/ML systems, thereby improving hazard mitigation capability while maintaining comprehensive hazard identification.
Solution Approach 2:
The patent introduces deficiency events as intermediary elements that mediate between system functionality and hazard outcomes. These deficiency events act as intermediaries that capture functional insufficiencies in AI/ML components, providing a bridge between traditional failure analysis and the unique safety concerns of intelligent systems, thus enhancing both hazard identification and mitigation.
3Device complexity
If Component Fault Trees are used to model system architecture, then modular safety analysis is enabled, but functional dependencies and deficiencies cannot be comprehensively represented
Solution Approach 1:
The patent applies universality by designing the CFDT element to serve multiple functions: it can represent both traditional hardware/software failures and AI/ML functional deficiencies within a single unified structure. The element's ability to handle both failure modes and deficiency modes makes it universally applicable to diverse system architectures while maintaining modular analysis capabilities, thus resolving the contradiction between model simplicity and functional representation completeness.
Data Source
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AI summary
The invention is directed to A computer-implemented method for generating a Component Fault and Deficiency Tree (1) of a multi-component system comprising a plurality of components, wherein each component of the plurality of components of the multi-component system is a hardware component, a software component, or a hardware and software component, the method comprising the steps: a. modeling the multi-component system using a Component Fault and Deficiency Tree (1, S1), wherein b. the Component Fault and Deficiency Tree comprises a plurality of component fault and deficiency tree elements (10) associated with the respective components of the multi-component system and interconnections between the component fault and deficiency tree elements (10) associated with respective functional dependencies between the components; wherein c. each component fault and deficiency tree element (10) comprises at least one inport (IN) and at least one outport (OUT); wherein each component fault and deficiency tree element (10) comprises at least one output failure mode (OFM), connected to the at least one outport (OUT); wherein each component fault and deficiency tree element (10) comprises at least one input failure mode (IFM), connected to the at least one inport (IN); wherein d. each component fault and deficiency tree element (10) comprises at least two events as internal fault tree logic (22, 24); wherein one event of the at least two events is associated with at least one failure (22) and the other event of the at least two events is associated with at least one deficiency (24) of the component; e. at least one gate, configured to connect the at least two events (22, 24); f. each component fault and deficiency tree element (10) comprises at least one mitigation logic (30); wherein the at least one mitigation logic (30) is configured to mitigate the at least one failure and/or at least one deficiency by means of a mitigation measure; g. at least one Boolean AND-Gate, configured to connect the internal fault tree logic (20) and the at least one mitigation logic (30); and h. Providing the generated Component Fault and Deficiency Tree (1) of the multi-component system as output (S2). Further, the invention relates to a computing unit and a computer program product.