COURSE OVERVIEW

  This practical and highly-interactive course includes practical sessions and exercises. Theory learnt will be applied using the iLearn Vibration simulator.

Preventive maintenance and condition monitoring techniques provide data that define required servicing and inspection periods so that maintenance departments can determine in advance when equipment must be shutdown for overhaul. Statistics are proving that these programs, when properly implemented, can minimize equipment and system breakdowns, resulting in a major reduction in total maintenance and operating costs.

 

This course covers all facets of preventive maintenance and condition monitoring. It is designed to benefit every level of maintenance personnel, providing the most up-to-date facts and techniques on the maintenance technology that is revolutionizing the way our industry operates. It examines the importance of preventive maintenance in a "World Class Maintenance" environment.

 

The course is designed to provide an insight into condition monitoring (CM).  It will cover the various methods of maintenance and it will give the participant an introduction to the techniques utilized in condition monitoring such as noise & vibration measurement, infrared thermography, oil debris analysis, laser alignment and balancing, vibration and engine analyzers, boroscope inspection and lube oil sampling.

 

Participants will understand the place of condition monitoring in the maintenance process and will appreciate the implications for maintenance cost saving and improved machine reliability.  They will be able to assess plant for the most appropriate monitoring parameter, will learn of the various specialist instruments and methods, be able to plan a monitoring programme and set up measurement rounds.  

 

The course will introduce participants to the dynamic behaviour of machines and discuss appropriate fault detection and diagnostic criteria and schemes for various applications.  It will address the more popular techniques which employ dynamic data analysis, including vibration and acoustic emission signals for the recognition of early life failures in machines. Emphasis will be placed on the practical application of tools to identify a wide range of mechanical, electrical and lubrication flaws in machinery and an objective approach to the optimum choice of analysis procedure.