A general repair, proportional-hazards, framework to model complex repairable systems

A system (machine) is observed to operate in 1 of 2 modes. The most common mode is loaded (or regular) operation. Occasionally the system is placed in an unloaded state, wherein while the system is mechanically still operating, it is assumed that the failure intensity is lower due to this reduction in operating intensity. A proportional hazards framework is used to capture this potential reduction in failure intensity due to switching of operating modes. In either operating condition, analyzed maintenance-records indicate that the system was occasionally shut down, and either a minor or a major repair was undertaken. Furthermore, despite such repairs, it is observed that both modes of operation (loaded or unloaded) resulted in random failures. On failure, 1 of 3 actions are taken: (1) failures were minimally repaired, (2) given a minor repair, or (3) given a major repair. Both minor and major repairs are assumed to impact the intensity following a virtual age process of the general form proposed by Kijima. This research develops a statistical model of such an operating/maintenance environment. Its purpose is to quantify the impacts of performing these repair actions on the failure intensities. Field data from an industrial-setting demonstrate that appropriate parameter estimates for such multiple phenomena can be obtained. Providing a richer, more detailed, modeling of the failure intensity of a system incorporating both operating conditions and repair effects has important ramifications for maintenance planning. This paper refers to related research, in which optimal timing of maintenance repairs depends fundamentally on the failure rate of the system.