Statistics for Maintenance Modelling: Proportional Hazards and Accelerated Life Models

# Summary¤

In this session, we have discussed the analysis of reliability data using the proportional hazards and accelerated life models. The merit of the proportional hazard and accelerated life models is the ability to incorporate covariates into the reliability or maintenance model where the time to failure is not only dependent upon the time the item has survived but also upon the levels of covariates. Also, the vast majority of reported cases of using the PH or accelerated life models have been in the analysis of survival data in health care, though the semi-parametric hazard-based model is beginning to have more of an impact in the reliability and maintenance modelling field.

The full PH or accelerated life model has a role to play in condition based maintenance modelling since the observed condition monitoring information may be regarded as the covariates. However, care must be taken when fitting the model to data since you must distinguish the covariates which may influence the state of the item monitored and the covariates which may be a function of the underlying state. The former can be modelled by the PH model such as speed, stress, loading, or temperature, and the latter should be modelled through a different mechanism such as the filtering model introduced in Condition Based Maintenance sessions of the Maintenance Modelling module.