Cold Chain Logistics Thermal Reliability: Modeling Temperature Excursions, Sensor Uncertainty, and Time-to-Intervention for Perishable Supply Chains

Abstract

This article advances a thermal reliability engineering framework for perishable cold chains that explicitly links (i) excursion event structure (probability, cumulative excursion minutes, and maximum duration), (ii) sensor uncertainty (noise, bias, drift, and missingness), and (iii) time-to-intervention (detection latency plus operational response delay) into a unified decision model for quality protection and compliance risk governance. The framework decomposes risk by process stage (warehouse, loading/staging, line-haul, cross-dock, last-mile) and treats monitoring as a decision pipeline whose performance is evaluated by missed-excursion rate, false-alarm rate, and tail-risk sensitivity rather than by point accuracy alone. A representative case-based analysis, calibrated to typical refrigerated vehicle dynamics reported in the literature, demonstrates that operational exposure during staging and cross-docking dominates excursion minutes and upper-tail risk, often outweighing marginal benefits from lowering refrigeration setpoints. Results further show that multi-sensor placement improves detection of localized hot spots only when persistence logic and stage-aware thresholds are applied; otherwise, false alarms rise and intervention effectiveness falls. The paper concludes with governance recommendations for stage-specific thresholds, drift-aware calibration policies, and intervention prioritization rules that are immediately usable for KPI reporting and audit-ready cold chain control.