Predictive Maintenance Strategies (ePDMS)
Condition-based maintenance, built on a predictive maintenance strategy, uses equipment operating condition to make data-driven decisions and improve quality, productivity and profitability. Beyond applying specific predictive technologies like vibration monitoring or oil analysis, this course focuses on establishing, managing and sustaining results from a comprehensive predictive maintenance program.
The course considers predictive maintenance and other techniques as a component of a larger asset-maintenance strategy to diagnose, prevent and postpone failures. Students will learn the theory and application of multiple PdM technologies, along with the critical success factors of results-producing programs. Using activities and case studies, learners determine which technologies to use, how to set goals for a program, track progress and communicate results to stakeholders.
Key Topics Covered
- How a combination of maintenance strategies mitigates risk and optimizes performance
- How risk mitigation tools are used as part of a condition-based maintenance program
- Selecting key performance indicators for maintenance strategy
- Understanding foundational PdM strategies, including vibration analysis, motor analysis, infrared analysis, oil analysis, ultrasound, non-destructive testing, and precision maintenance best practices
- Emerging technologies and the evolution of predictive maintenance
- Defining maintenance program objectives, measures of success, training needs, change management implications, and organizational sponsorship
- Drafting a business case for a PdM program
Who Will Benefit
The course is most suited to those involved in justifying or managing duties related to a condition-based monitoring program, including Maintenance Managers, PdM Managers, Maintenance professionals, and continuing education students.
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