New CIG method automates fault tree generation from knowledge graphs for reliable CPS
Automated reliability modeling with ontology-driven graph structures reduces expert reliance and documentation gaps.
A new paper from researchers at the University of Twente and others introduces the Capability Interaction Graph (CIG), a structured representation for Cyber-Physical Systems (CPS) reliability. CIGs are grounded in the Unified Foundational Ontology (UFO), providing a common semantic language across software, electrical, and mechanical engineering. Because CIGs are graph-based, they naturally form knowledge graphs that explicitly capture functional dependencies and system semantics, replacing fragmented documentation and tacit expert knowledge.
The key innovation is an automated synthesis algorithm that transforms CIG knowledge graphs directly into Fault Trees (FTs). Fault Tree Analysis is a standard method for identifying failure propagation paths and minimal cut sets, but manual construction is error-prone and time-consuming. This work automates that step, enabling engineers to quickly generate reliability models from a unified ontology-driven representation. The approach addresses a major challenge in CPS development: integrating reliability analysis early in the design lifecycle across different disciplines without relying on incomplete or undocumented failure modes.
- Capability Interaction Graphs (CIGs) are ontology-driven representations grounded in the Unified Foundational Ontology (UFO), enabling a common semantic framework across disciplines.
- CIGs are naturally encoded as knowledge graphs, capturing explicit functional dependencies and system semantics.
- An automated synthesis algorithm converts CIG knowledge graphs into Fault Trees, automatically generating failure propagation paths and minimal cut sets.
Why It Matters
Automates reliability modeling for complex cyber-physical systems, reducing manual effort and bridging gaps between engineering domains.