TS-073254 — Industries operating safety‑critical and asset‑intensive systems struggle to leverage the full value of disparate maintenance data sources. Current maintenance management and optimization tools operate in silos, limiting real‑time decision‑making, automation, and scalability. No existing s…

TS-073146 — As industrial systems become increasingly digital and interconnected, traditional risk assessment tools struggle to capture how cyber threats interact with physical processes in real time. Existing methods typically assess hardware failures or isolated cyber events, but they cannot model how attac…

TS-073138 — Designing online monitoring (OLM) for safety‑critical systems is constrained by scarce early‑stage operational data and by quantitative models that are slow to build, brittle across configurations, and costly to iterate. This creates expensive sensor networks with blind spots, poor diagnosabil…

TS-073031 — Operators of large, complex facilities struggle to balance revenue, maintenance, and regulatory safety constraints under uncertainty. Existing tools typically optimize only a subset of factors without a unified, real‑time view of component health and future degradation. Advanced reactors and oth…

TS-072175 — The Need Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretabil…

TS-068440 — Accurate measurement of physical attributes, such as dimensions, alignments, and surface features, is essential for ensuring quality and consistency across industries. Traditional measurement methods, often reliant on manual tools and human oversight, are time-intensive, prone to errors, and lac…