The growing volatility, interconnectedness, and disruption risks of modern global supply chains demand intelligent logistics systems that can operate adaptively across multiple spatial and temporal scales. This study proposes an integrated Digital Twin–FKF transform framework for intelligent and resilient logistics by combining Digital Twins, the Internet of Things (IoT), Artificial Intelligence (AI), sustainable mobility, Blockchain, and quantum optimization with advanced spectral analysis. Digital Twins provide dynamic representations of logistics assets and processes, enabling real-time synchronization, monitoring, simulation, and disruption-scenario evaluation, while IoT and AI facilitate intelligent sensing, prediction, and adaptive decision-making. The bivariate Fourier–Kontorovich–Lebedev (FKF) transform supplies a joint temporal–scale spectral representation of supply-chain signals, enabling the identification of time shifts, exponential modulation, multiscale behavior, and lead-time dynamics. These spectral characteristics are converted into informative features for AI-driven forecasting, anomaly detection, and resilience assessment. The proposed FKF-enabled intelligent supply-chain framework therefore integrates spectral intelligence with AI, Blockchain, IoT, Digital Twins, and quantum optimization to support predictive, transparent, sustainable, and resilient logistics operations.