How to map and monitor the condition of your electromechanical installations?
One of the objectives of a modern maintenance strategy is to ensure the high reliability of the machine park. Predictive maintenance (Condition Based Maintenance) uses different techniques to map the "health" of the machine park without being intrusive. These techniques, such as vibration analysis, ultrasonic analysis, thermographic research or oil analysis, can detect machine failure at an early stage.
Each technique is instructive, but what is the best method of using them? Which failure modes can be detected? And with which technique and for which application?
This training creates competences for the participants so they can apply the basics of predictive technologies for electrical and mechanical machines and integrate them with other strategies.
Learning objectives
- Establishing an electrical and mechanical Asset Health Matrix.
- Knowing how to adjust the Predictive Maintenance Programme to the level of maturity.
- How to select which machines should be part of the Predictive Maintenance Programme.
- How to determine if a Preventive Maintenance task has an added value
- How to set up a proper Preventive Maintenance Task for failure modes not detectable by the selected Predictive Technologies.
Programme
Identification of electrical and mechanical failure modes in:
- AC and DC motors
- transformers
- switchgear
and identification of the pitfalls of each technique.
Learning to use vibration analysis to identify failure modes in:
- AC and DC motors
- mechanical applications
Learning to use ultrasonic analysis (airborne & structure-borne) to detect failure modes in:
- AC and DC motors
- transformers
- switchgear
- mechanical applications
Learn to use oil analysis for detecting failure modes in:
- transformers
- mechanical applications
Learn to use thermographic analysis for detection of failure modes in:
- AC and DC motors
- transformers
- switchgear
- mechanical applications
Who is this training for?
This training is suitable for maintenance managers, reliability engineers responsible for data transfer and integration with daily maintenance, of information derived from the Predictive Maintenance Programme.
Trainers
Kris Deckers, Tom Rombouts, Pedro Viña & Gunther Willems from I-care.