Machinery failure analysis and prevention using structured and systematic approaches are critical for every successful plant. This course is designed to build competency in machinery failure analysis and prevention in order to enhance machinery reliability and availability and overall plant productivity. It covers all the fundamentals, systematic and structured practical approaches, methods and applications that a professional would use in carrying out fully functional plant maintenance. In summary, the course provides a step-by-step practical guide to best practices of machinery failure analysis and prevention that will deliver maximum business benefits.
This training course is based on 35 years of real-life industrial experience of the trainer in machinery failure analysis and prevention.
The course covers:
- Systematic and structured analysis of machinery functional and potential failures, hidden and evident failures, failure modes, effects and consequences
- Advanced failure analysis techniques and 9 steps of the classical failure analysis
- Advanced machinery fault diagnosis and optimum combination of proactive tasks and default actions for machinery failure prevention
- A highly effective root cause analysis of machinery faults/failures providing next generation proactive maintenance
- Failure mode and effect analysis (FMEA) and failure mode, effect and criticality analysis (FMECA)
- Effective field-proven condition monitoring technologies (i.e. vibration, acoustic emission, infrared thermography and wear debris) that should be used to detect, locate, diagnose and assess severity of faults in machinery
- The most effective risk assessment techniques for machinery faults/failures and principles of advanced risk-based inspection for machinery failure prevention
- The best-of-class reliability centered maintenance, an efficient practical framework for machinery fault/failure prevention
- Practical implementation of advanced methods/technologies for machinery failure analysis and prevention and root cause analysis of machinery fault/failure via 52 industrial case studies
