The Need

Complex systems are entering the market faster while safety verification grows harder, especially when detailed designs or operational data don’t yet exist. Traditional tools (FMEA, FTA, PRA) either require finalized designs, focus on forward propagation, or struggle with partial failures and functional interdependencies, leaving early-stage teams blind to root causes of critical outcomes. Industry needs a scalable, formal method to trace failures backward from a desired or undesired state and inform robust conceptual designs before costly prototyping and testing.

The Technology

OSU engineers have developed BLIPS (Backwards Logic Inference‑based Propagation for System analysis). BLIPS starts from a known functional state and systematically back‑infers relevant and adjacent component modes and variable relations, then estimates the states of other functions. Using formally reversed functional and behavioral rule sets, BLIPS generates mutually exclusive, exhaustive “branches” that describe plausible precursors to the condition of interest. An optional probabilistic augmentation (BLIPS‑PA) prioritizes branches to guide design decisions, instrumentation, and redundancy planning without requiring detailed physics or operational histories.

Commercial Applications

• Nuclear power secondary‑loop/plant systems design and monitoring
• Aerospace propulsion, thermal management, and flight‑critical subsystems
• Process industries (chemical/oil & gas) and industrial automation networks
• Electrical/energy systems and complex electromechanical platforms (e.g., autonomous vehicles)

Benefits/Advantages

• Works at the conceptual stage to reduce redesign cycles, testing costs, and schedule risk
• Provides formally proved, exhaustive backward sequences over the entire variable space
• Reveals functional interdependencies and partial‑failure conditions across hardware/software domains
• Adds probabilistic weighting (BLIPS‑PA) to rank scenarios and focus mitigation where it matters most