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Course Outline
Introduction to Predictive Maintenance for Government
- What is predictive maintenance?
- Comparative analysis of reactive, preventive, and predictive approaches
- Real-world return on investment (ROI) and industry case studies
Data Collection and Preparation for Government
- Utilization of sensors, Internet of Things (IoT), and data logging in industrial environments
- Techniques for data cleaning and structuring to support analysis
- Methods for handling time series data and failure labeling
Machine Learning for Predictive Maintenance for Government
- Overview of machine learning models, including regression, classification, and anomaly detection
- Criteria for selecting the appropriate model for predicting equipment failure
- Processes for model training, validation, and evaluation using performance metrics
Building the Predictive Workflow for Government
- Development of an end-to-end pipeline encompassing data ingestion, analysis, and alerts
- Leveraging cloud platforms or edge computing for real-time analysis in government settings
- Integration with existing Computerized Maintenance Management Systems (CMMS) or Enterprise Resource Planning (ERP) systems
Failure Mode and Health Index Modeling for Government
- Techniques for predicting specific failure modes
- Methods for calculating Remaining Useful Life (RUL)
- Development of asset health dashboards to support decision-making
Visualization and Alerting Systems for Government
- Strategies for visualizing predictions and trends in a government context
- Setting thresholds and creating alerts to inform timely action
- Designing actionable insights tailored for operators in government agencies
Best Practices and Risk Management for Government
- Addressing data quality issues in government datasets
- Ensuring ethics and explainability in industrial AI systems used by government entities
- Implementing change management strategies to facilitate adoption across government teams
Summary and Next Steps for Government
Requirements
- Knowledge of industrial equipment and maintenance workflows for government operations
- Basic understanding of artificial intelligence and machine learning principles
- Experience with data collection and monitoring systems in public sector environments
Audience
- Maintenance Engineers for government facilities
- Reliability Teams within public sector organizations
- Operations Managers in government agencies
14 Hours
