Predictive Maintenance Anomaly Detection System

Create a Python-based predictive maintenance system using advanced time series analysis and machine learning techniques. Develop a solution that can ingest sensor data, perform real-time anomaly detection, and predict potential equipment failures with configurable confidence levels. Implement a modular architecture supporting multiple sensor types, with automatic feature engineering, ensemble machine learning models, and a comprehensive reporting system that provides actionable maintenance recommendations.