A model-driven approach for the failure data analysis of multiple repairable systems without information on individual sequences

This paper proposes a model-driven approach which is able to analyze the failure data of multiple repairable systems when no information on the individual sequences is available, thus overcoming the limitations of the previous models proposed in the literature. The proposed approach can analyze the failure data of systems subject to minimal, imperfect, or worse repairs; and is developed under a general form of the baseline failure intensity. Both failure- and time-truncation are considered, provided that the truncation time is the same for all the systems. Due to its physical interpretation, the proposed approach allows the reliability characteristics of the failure process to be estimated, and it allows the effect of the repairs on the system reliability to be checked via testing procedures. The proposed approach has been applied to a well-known real data set, which inspired the work in this paper, showing its flexibility and great potential.