Real-Time Supply Chain Anomaly Detection System

Create an advanced anomaly detection system for manufacturing supply chain data using time-series analysis and machine learning. Develop a solution that can process streaming logistics data, detect statistically significant deviations in shipping times, inventory levels, and cost metrics. Implement both statistical (Z-score) and machine learning (isolation forest) detection methods with automated alerting and root cause hypothesis generation.