Advanced Predictive Maintenance and Condition Monitoring Techniques

Objectives:

• Understand the principles and importance of predictive maintenance.
• Learn about advanced condition monitoring techniques and technologies.
• Gain skills in implementing predictive maintenance systems.
• Analyze the impact of predictive maintenance on operational efficiency and cost reduction.

Condition Monitoring Fundamentals

• Overview of condition monitoring and predictive maintenance
• Types of equipment and systems suitable for condition monitoring
• Key parameters to monitor: vibration, temperature, pressure, and wear
• Benefits of predictive maintenance in reducing downtime and costs

Advanced Predictive Maintenance Technologies

• Vibration analysis techniques and tools
• Acoustic emission monitoring and its applications
• Infrared thermography for predictive maintenance
• Oil analysis and particle counting for machinery health monitoring

Data Analytics and Fault Detection

• Data collection methods for predictive maintenance
• Statistical and machine learning techniques for fault detection
• Predictive models: Regression analysis, neural networks, and decision trees
• Case studies on successful predictive maintenance applications

Implementation and Optimization of Predictive Maintenance

• Steps for implementing a predictive maintenance program
• Integrating condition monitoring data with maintenance management systems
• Optimizing maintenance schedules and resource allocation
• Evaluating the ROI of predictive maintenance strategies

DATE:

1ST BATCH:         3rd – 6th June,                  2025    

2ND BATCH:       16th – 19th Dec,               2025