Felrisk

Felrisk is a quantitative risk assessment metric used to estimate the probability and impact of discrete failure events within complex systems. The concept typically treats felrisk as a combined score that reflects both how likely a failure is and how severe its consequences would be. In common practice, felrisk is expressed as felrisk = L × C, where L denotes a likelihood score and C denotes a consequence score. Values are often normalized to a 0–1 or 0–100 scale, and multiple failure modes can be aggregated to produce an overall risk profile for a system.

Methodology: The likelihood component L is derived from historical data, sensor readings, fault-tree or event-tree analyses, and expert judgment, with updates using Bayesian methods as new information becomes available. The consequence component C accounts for factors such as direct costs, downtime, safety and environmental harm, and reputational impact, with potential weighting for stakeholders affected. The resulting felrisk scores are used to rank risks and guide mitigation priorities.

Applications: Felrisk has been proposed for use in engineering, manufacturing, software reliability, energy systems, and infrastructure projects to prioritize mitigation actions, allocate resources, and compare design alternatives. It is commonly employed in risk registers and decision-support tools as a compact summary metric alongside qualitative assessments.

Limitations: Felrisk depends on the quality and completeness of input data and on the explicit assumptions used to define L and C. It can oversimplify interdependencies between failure modes or fail to capture time-varying risk factors if not modeled explicitly. Therefore, felrisk should be used in conjunction with other risk analysis methods and domain-specific judgment.

See also: risk assessment, fault tree analysis, event tree analysis, Bayesian networks, reliability engineering.