Redundancy allocation of mixed warm and cold standby components in repairable K-out-of-N systems

Abstract

In system design process, standby redundancy is a widely used technique to improve system reliability and availability. Typical standby techniques involve cold standby, hot standby, and warm standby. In this article, we investigate the repairable K-out-of- N system with mixed standby strategy containing both warm and cold standby. In the proposed system, each component can be in failure, cold, warm, and active states and the components are assumed to be repairable. The systems are modeled by continuous time Markov chain and the system long-run availability is derived. Furthermore, the optimal configuration of standby components in the system is studied considering both system availability and system running cost. Illustrative examples are presented to show the applications of the proposed model.

Reliability analysis of k-out-of-n: G repairable systems considering common cause failure and multi-level maintenance strategy

“…The k-out-of-n: G system consists of n components, and the system works normally if and only if when there are at least k working components at the same time in the system. [1][2][3] As this kind of system has been widely used in various fields, the research on the maintenance problems of the k-out-of-n: G system has become a hot topic in recent years. For instance, preventive maintenance, 4 condition-based maintenance, 5 the optimal maintenance policy which includes preventive maintenance and corrective maintenance, 6 and the maintenance under D-policy.…”

A new dynamic model to optimize the reliability of the series-parallel systems under warm standby components

“…Reliability maximization results in customer satisfaction maximization and gaining a large market share [52,26]. Using RAP to improve the reliability of systems and products will in turn help organizations remain more competitive in the market [20,24]. RAP has been used for vast variety of system's structures, including series [32], parallel series [57,14,47,17,55,2,56,36,58,50,35], and k-out-of-n systems [13,33,20,10], to name a few.…”

“…Using RAP to improve the reliability of systems and products will in turn help organizations remain more competitive in the market [20,24]. RAP has been used for vast variety of system's structures, including series [32], parallel series [57,14,47,17,55,2,56,36,58,50,35], and k-out-of-n systems [13,33,20,10], to name a few. There are generally two classes of RAP: the first class is limited to component selection from a discrete set of subsystems with a priori given characteristics, such as reliability, weight, cost, and volume.…”

“…More specifically, Suprasad et al [46] proposed a static model to calculate system reliability of k-out-of-n systems in which each subsystem can be active or warm standby. Gong et al [20] analyzed the reliability of static systems with warm and cold standby for each subsystem to solve the RAP. They used an algorithm based on the Markov process.…”