Prediction of power equipment failures based on chronological failure records

When power utility asset managers are facing the task of resource planning for future deployment, often times, only partial information is available: installation dates and amounts, as well as failure and replacement rates. By combining records on yearly populations of the components, estimation of failure model parameters may be possible. Parametric models may then be used for forecasting of the system's short term future failure rates and for formulation of replacement strategies. We employ the Weibull distribution and show how we estimate its parameters from past failure data. With the obtained estimates, we forecast future failures and keep on improving the estimates as new data become available