Competing Risks Analysis of Reliability, Survivability, and Prognostics and Health Management (PHM)

Competing risks analysis is a field of applied statistics with research dating back to the eighteenth century. Starting in the 1980s, the interaction with survival analysis has lead to significant advances in competing risks analysis, especially in dealing with the dependency and identifiability issues, both of which are often intermingled with each other and have been the focus of the controversy surrounding classical competing risks analysis. The usefulness of competing risks analysis in engineering reliability has been recognized since the 1960s, and several important models in competing risks analysis were developed in the context of reliability modeling [e.g., Marshall-Olkin (1967) model]. However, the interaction between competing risks analysis and reliability has gradually withered during the period when significant advances were made in competing risks analysis. Consequently, it seems that the application of competing risks analysis in engineering reliability has fallen behind the theory of competing risks analysis. In particular, the advances in dependence and identifiability research are of extremely important significance in reliability field. We hope that this review article will contribute to the reestablishment of the connections between competing risks analysis and engineering reliability. In perspective, we suggest that the competing risks analysis has great potential in other fields of computer science and engineering, besides engineering reliability. In particular, network reliability and survivability, software reliability and test measurements, prognostics and health management, stand out as fields with very compelling reasons for further exploring.