Dynamic importance measure for the K-out-of-n: G system under repeated random load. (March 2020) - Lyu, Dong; Si, Shubin
Highlights: A dynamic importance measure for k -out-of- n : G systems under repeated random load is proposed. A MC method is developed to validate the dynamic importance measure. Effects of the randomness of load on component importance and importance ranking are studied. The strength distribution parameters of the component affect its importance. Abstract: Importance measures have been widely used in system reliability design and optimization to find out system weaknesses. But the existing importance measures are hard to identify the dynamic weakness effectively for systems subjected to repeated and random load. Based on the stress-strength interference (SSI) model, this paper aims to develop a dynamic importance measure for k -out-of- n : G systems under repeated random load. At first, the importance measure for systems under repeated random load is put forward by using the order statistics theory. Then by describing the loading process with the Poisson process, a time-dependent model of the dynamic importance measure is established. Further, a Monte Carlo (MC) simulation method is proposed to verify the correctness of the dynamic importance measures. Finally, the reliability analysis for a multi-lock cargo door system in the air freighter is implemented to illustrate the practical application of the dynamic importance measure.