Availability analysis for a multi-component system with different k-out-of-n:G warm standby subsystems subject to suspended animation

Abstract

Industrial equipment or systems are usually constructed as a multi-component series system with k-out-of-n:G subsystems to fulfill a specified function. As a common type of standby, warm standby is considered in the multi-component series system with k-outof-n:G standby subsystems. When a subsystem fails, the non-failed subsystems are shut off and cannot fail, which is defined as suspended animation (SA). If the SA is ignored the non-failed subsystems are assumed to keep working in the SA time, which will cause inaccuracy in the availability analysis for the system. In this paper, we focus on the SA to construct an availability model for a multi-component series system with k-out-of-n:G warm standby subsystems. Multiple continuous time Markov chains are constructed to model the system availability. A Monte Carlo simulation has been carried out to verify our method. Several interesting findings are obtained. 1) The failure rates of subsystems with SA and their limits are derived. 2) The closed-form expressions for the stationary availability of the system and subsystems, mean time to failure, mean time to repair and stationary failure frequency are obtained considering SA. 3) The system stationary availability is a monotone function for its parameters. 4) The SA effect on the stationary availability should be emphasized in two cases, one is both the value of n/k and the failure rate of active components in a k-out-of-n subsystem are relatively large or small, the other is both the value of n/k and the repair rate are relatively small.

Defensive strategy optimization of consecutive-k-out-of-n systems under deterministic external risks

“…Defensive strategies (redundancy and assignment of components) are essential to prevent severe catastrophic events, decreasing economic losses from many other disasters. Some scholars have studied the negative effect of risk on the system performance, and the reported research work verified that effective defensive strategy can resist the degradation of system performance [8,9,33,37]. So, risk events may cause enormous losses for the government when the defensive strategy is not appropriate.…”

Modelling of the Military Helicopter Operation Process in Terms of Readiness

“…A separate area of application of Markov processes is the modelling of technical objects exploitation processes [21][22][23][24][25] , as well as their implementation in the analysis and evaluation of both availability 5,[26][27][28] and readiness [29][30][31][32][33] .…”

“…In studies on modelling exploitation processes, the reliability of the vehicle fleet defined as a function of the damage stream 21,29 , assessment of the degree and level of usability 30 , readiness 22,25,32 of an object or system of exploitation 27,28 , or population renewal including replacement according to age 23,34 often become the subject of tests.…”