A Prognostics-Based Spare Part Ordering And System Replacement Policy For A Deteriorating System Subjected To A Random Lead Time

Prognostics-based spare part ordering and system replacement (PSOSR) policies are at the forefront of the prevalent prognostics and health management discipline. However, almost all of the existing researches in this domain ignore the stochasticity of the lead time. With this in mind, this paper proposes a PSOSR policy based on the real-time health condition of a deteriorating system subjected to a random lead time. In doing so, the degradation path of the interested system is modelled by a Wiener process, and the associated life distributions can be predicted recursively according to the real-time health condition of the system. In turn, the proposed policy can also be updated dynamically based on these real-time obtained life distributions. The policy, which - in addition to incorporating the stochasticity of the lead time - integrates the decision-making issues of both spare part ordering and system replacement - is finally applied to a case study of an inertial navigation system served in a type of aircraft. The experimental results validate the policy's effectiveness and superiority.