Reliability Engineering - Reliability Modelling

Reliability Modelling

Reliability modelling is the process of predicting or understanding the reliability of a component or system prior to its implementation. Two types of analysis that are often used to model a complete system availability (including effects from logistics issues like spare part provisioning, transport and manpower) behavior are Fault Tree Analysis and Reliability Block diagrams. On component level the same type of analysis can be used together with others. The input for the models can come from many sources: Testing, Earlier operational experience field data or Data Handbooks from the same or mixed industries can be used. In all cases, the data must be used with great caution as predictions are only valid in case the same product in the same context is used. Often predictions are only made to compare alternatives.

For part level predictions, two separate fields of investigation are common:

• The physics of failure approach uses an understanding of physical failure mechanisms involved, such as mechanical crack propagation or chemical corrosion degradation or failure;
• The parts stress modelling approach is an empirical method for prediction based on counting the number and type of components of the system, and the stress they undergo during operation.

Software reliability is a more challenging area that must be considered when it is a considerable component to system functionality.

It is a general praxis to model the early (hardware) failure rate with an exponential distribution. This less complex model for the failure distribution has only one parameter: the constant failure rate. In such cases, the Chi-squared distribution can be used to find the goodness of fit for the estimated failure rate. Compared to a model with a decreasing failure rate, this is quite pessimistic (important remark: this is not the case if less hours / load cycles are tested than service life in a wear-out type of test, in this case the opposite is true and assuming a more constant failure rate than there is in reality can be dangerous). Sensitivity analysis should be conducted in this case.