Statistical Electromagnetics for EMC Risk Prediction: A Physics-Based Framework for Safety-Critical Systems

Electromagnetic compatibility (EMC) is typically assessed through standardized emissions and immunity tests that yield binary pass/fail outcomes. While such testing is essential for demonstrating compliance, it does not quantify the reliability of system operation in real electromagnetic environments. These environments are stochastic in nature, and devices respond nonlinearly near susceptibility thresholds, resulting in rare but consequential failure events that may not be in scope for compliance testing. The intention of this paper is to extend EMC assurance from compliance evaluation to probabilistic reliability prediction. A framework grounded in statistical electromagnetics is presented that incorporates random field theory, coupling-path characterization, and nonlinear response modeling. The framework defines the Probability of EMC-Induced Hazard (PEMH), a metric that quantifies how frequently electromagnetic disturbances produce functional failures that can propagate into hazardous failures. By following a structured execution process, the framework provides quantitative reliability data in addition to compliance results. A case study on industrial safety control input demonstrates that systems may satisfy regulatory standards yet still exhibit measurable failure probabilities. This approach reframes EMC from a conformity exercise into a predictive reliability discipline, directly supporting functional safety objectives.