Automated Predictive Maintenance Risk Scoring Framework

Create a Python-based predictive maintenance risk scoring system that can process complex industrial equipment sensor data. Develop machine learning models using scikit-learn to predict potential failure probabilities, incorporating feature engineering techniques that handle missing data and temporal dependencies. The framework should generate a comprehensive risk dashboard with probability distributions, confidence intervals, and recommended preventative actions. Implement modular design to allow easy integration with different sensor data schemas and equipment types.