Introduction:

• Welcome and introductions

• Course overview and objectives

• Importance of predictive maintenance in preventing equipment breakdowns, improving efficiency, and reducing costs

• Real-world case studies of successful implementation of predictive maintenance programs

Objectives:

• Define predictive maintenance and its benefits

• Identify various predictive maintenance techniques

• Understand the selection process for appropriate techniques.

Content:

Day 1: Understanding Predictive Maintenance and Techniques

• Overview of common predictive maintenance techniques:

• Vibration analysis

• Oil analysis (tribology)

• Thermography (infrared imaging)

• Ultrasonics

• Other non-destructive testing (NDT) methods

Day 2: Implementing a Predictive Maintenance Program

• Identifying critical equipment and potential failure points

• Establishing data collection procedures and tools

• Setting up a data management system

• Techniques for analyzing data from various predictive maintenance methods

• Setting thresholds and alarms for early detection of potential problems

Day 3: Maintaining and Optimizing your Predictive Maintenance Program

• Monitoring program effectiveness and adjusting approaches as needed

• Utilizing feedback loops to enhance data collection and analysis

• Integrating predictive maintenance with other maintenance strategies (preventive, corrective)

• Sensor technology and data integration

• Machine learning and artificial intelligence in predictive maintenance

Conclusion:

• Course review and key takeaways

• Action planning for implementing predictive maintenance in your workplace

• Resources and next steps