Reliability Training Advanced Topics

Duration: 3 Days | Lecture

This Reliability Training Course provides an overview of a variety of advanced reliability techniques, such as:

• Reliability assessment of dynamic systems, characterized by their change in functional and physical configuration as a function of time and tightly interacting and interdependent components.

• The Bayesian approach to probability and its application to reliability analysis. This approach is particularly useful for highly reliable components and systems where failures in test and field operation are very rare, requiring the use of all other non-statistical engineering information and generic data to estimate reliability.

• Collection and statistical analysis of reliability data, covering both the engineering and analytical aspects of the development of a reliability database and estimation of reliability parameters, such as failure rates and mean repair times. Both the classical and Bayesian approaches to parameter estimation are covered, while establishing the link between the corresponding tools and techniques.

• Markov Chain Analysis is a powerful modeling and analysis technique with strong applications in time-based reliability and availability analysis. The reliability behavior of a system is represented using a state-transition diagram, which consists of a set of discrete states that the system can be in, and defines the speed at which transitions between those states take place. As such,

• Fault Tree Analysis is one of the core techniques used in reliability, risk and safety analyses. A Fault Tree forms a logical representation of the manner in which combinations of basic events, often made up of failures at the component level, could lead to a hypothesized failure of a system.

Schedule: TBC

Location: TBC

Cost: TBC

Registration

To book a place on this useful and informative Reliability Training workshop, please use the registration link above, or contact us by telephone or email.

Further details are available on request.

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