State-dependent age replacement policy for a system subject to cascading failures

Abstract

A cascading failure is a failure in a system of interconnected parts in which the failure of a part triggers the failure of successive parts. Although some initial and empirical studies for probabilistic modeling and analysis of the cascading failures have been performed in the literature, general modeling frameworks and relevant maintenance policies have been barely reported yet. However, in this article, based on a general framework for modeling cascading failures, we study the optimal preventive maintenance problem for the system. A new state-dependent age replacement policy is developed. The comparison with the ordinary age replacement policy is also discussed.

A resilient network recovery framework against cascading failures with deep graph learning

“…16,17 Because failures are inevitable and resources to restore the system when failures occur are limited and subject to budgets, optimal maintenance methods or strategies to improve system resilience and mitigate the influences of cascading failures are of great significance and interests in both academia and practice. [18][19][20] Di Muro et al proposed a maintenance strategy for interdependent network systems by repairing the network nodes that belong to the largest connected component of each constituent network. 21 Almoghathawi et al developed an optimization method, which decides the maintenance priority of failed components in interdependent networks, to achieve a balance between resilience and investment cost.…”

Comparison of the replacement policy in k-out-of-n systems having dependent components

“…Nakagawa and Zhao 2 and Eryilmaz 3 also studied the same optimization problems for a parallel system, a particular case of a k -out-of- n system when k = 1 . Some works on replacement policy are in Yang et al, 4 Lee, 5 Wang and Wang, 6 and Levitin and Finkelstein. 7…”