Allocation and activation of resource constrained shock-exposed components in heterogeneous 1-out-of-n standby system

Gregory Levitin, Liudong Xing and Yuanshun Dai

Reliability Engineering and System Safety, 2024, vol. 241, issue C

Abstract: In real-world mission-critical applications like unmanned aerial vehicles (UAVs), the standby sparing design method is typically applied to enhance the mission success probability (MSP), and standby components may reside in different physical positions exposed to diverse random environments/shocks affecting components’ failure behaviors. Thus, the position allocation of standby components may affect the MSP greatly. Moreover, the MSP varies for different activation sequences of standby components. This paper makes contributions by formulating and solving the optimal position allocation and activation sequence (PAAS) problem to maximize the MSP of a 1-out-of-n standby system with n non-identical components, characterized by different performance speeds, initial resource (determining the maximum amount of mission work that can be completed by each component), and shock resistance levels. The rate of shocks affecting each component is dependent on the component's position and mode (standby, activation, or operation). We put forward a new numerical algorithm for evaluating the MSP, the probability that the considered standby system can compete a specified amount of work before all the system components stop operation due to failures or resource depletion. We further apply the genetic algorithm to solve the PAAS co-optimization problem. A multi-UAV surveillance system is studied to showcase the proposed standby system model and impacts of several component and shock parameters on the mission reliability and PAAS optimization solutions.

Keywords: Standby systems; Limited resource; Shocks; Position allocation; Activation sequence; Unmanned aerial vehicles (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:241:y:2024:i:c:s095183202300604x

DOI: 10.1016/j.ress.2023.109690

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