On Modeling of Repairable Systems with Multi-Output Gaussian Convolution Process

This paper focuses on the modeling of repairable systems using the multi-output Gaussian convolution process. We propose a statistical model that captures the heterogeneity of recurrent failure time data. We use a Bayesian framework for parameter estimation. A diesel engine system is used to illustrate the application of the model.