Course Overview
This 5-day intensive program equips maintenance professionals, reliability engineers, and plant managers with advanced methodologies to develop, implement, and optimize Preventive (PM) and Predictive (PdM) Maintenance Programs. Participants will gain hands-on experience with condition monitoring technologies, maintenance planning, and data-driven decision-making to enhance equipment reliability and reduce downtime.
Course Objectives
Upon completion, participants will be able to:
- Design and implement PM/PdM programs aligned with operational goals
- Select and apply predictive technologies (vibration analysis, thermography, oil analysis)
- Optimize maintenance intervals using failure mode analysis
- Integrate CMMS/EAM systems for work order management
- Calculate ROI for predictive maintenance investments
- Train teams on PM/PdM best practices
- Measure program effectiveness using KPIs
- Leverage Industry 4.0 technologies (IIoT, AI, digital twins)
Who Should Attend
This course is ideal for:
- Maintenance Managers & Supervisors
- Reliability Engineers
- Condition Monitoring Technicians
- Plant Operations Managers
- Asset Management Professionals
- Industrial Engineers
- Maintenance Planners
Course Modules
Module 1: Maintenance Strategy Fundamentals
- Evolution from reactive to predictive maintenance
- Reliability-Centered Maintenance (RCM) principles
- Criticality analysis (API 580)
- Maintenance maturity models
Module 2: Preventive Maintenance Optimization
| Component | Optimization Technique |
| Task Selection | Failure Mode & Effects Analysis (FMEA) |
| Frequency | Weibull analysis, historical data |
| Procedures | Standardized work instructions |
| Resources | Labor, materials, and tools planning |
Module 3: Predictive Maintenance Technologies
- Vibration Analysis (ISO 10816 standards)
- Infrared Thermography (ASTM E1934)
- Oil Analysis & Wear Particle Monitoring
- Ultrasound & Motor Current Analysis
Module 4: Program Implementation
- Technology selection matrix
- Baseline data collection
- Alarm threshold setting
- Integration with CMMS
Module 5: Data Analysis & Decision Making
- Fault pattern recognition
- Severity assessment
- Repair vs. replace decisions
- Root cause analysis (RCA)
Module 6: Financial Justification
- Cost-benefit analysis
- Equipment criticality weighting
- Life extension calculations
- Budgeting for PdM
Module 7: Digital Transformation
- IIoT sensor networks for real-time monitoring
- AI-driven failure prediction
- Digital twin applications
- Mobile workforce enablement