Reliability Analysis of Semiconductor Material Processing for Advanced Integrated Circuit Chip Manufacturing

Advanced integrated-circuit fabrication couples deposition, lithography, etching, implantation, annealing, and chemical–mechanical polishing, allowing local fluctuations to propagate into defects, electrical drift, yield loss, and premature failure. We develop a process-graph reliability framework combining physics-informed models, process-data analytics, and uncertainty quantification. A process–structure–property–reliability map is embedded in a directed fabrication graph, while a pathwise operator decomposes first-order uncertainty propagation into stage and cross-stage contributions. We derive sub-Gaussian and Wasserstein failure certificates, an independent-sample finite-data bound, and a risk-allocation scheme with explicit convergence conditions. In reproducible virtual-fab experiments, the cost-penalized implementation achieves 98.30% nominal yield and 82.2 kppm shifted failure. Under a matched-budget audit, all optimized policies fall within 81.2–82.5 kppm, indicating that the principal contribution is auditable cross-stage certification rather than unconditional empirical dominance.