Optimal allocation of multi-state elements in a sliding window system with phased missions

Abstract

Many real-world engineering systems such as aerospace systems, intelligent transportation systems and high-performance computing systems are designed to complete missions in multiple phases. These types of systems are known as phased-mission systems. Inspired by an industrial heating system, this research proposes a generalized linear sliding window system with phased missions. The proposed system consists of N nodes with M multi-state elements that are subject to degradation. The linear sliding window system fails if the cumulative performance of any r consecutive nodes is less than the pre-determined demand in any phase. The degradation process of each element is modeled by a continuous-time Markov chain. A novel reliability evaluation algorithm is proposed for the linear sliding window system with phased missions by extending the universal generating function technique. Furthermore, the optimal element allocation strategy is determined using the particle swarm optimization. The effectiveness of the proposed algorithm is confirmed by a set of numerical experiments.

A two-stage UAV routing problem with time window considering rescheduling with random delivery reliability

“…For example, the optimal strategy can be obtained to minimize the cost to meet a requirement of reliability, or to maximize the reliability under a constraint of cost. In details, the high reliability is indicated by the low probability of UAVs destruction and few unvisited targets according to the system reliability definition in many complex processes or missions [21][22][23][24][25][26][27][28][29]. The reliability is defined by two metrics: the probability of UAVs being destroyed and the number of unvisited targets; and both of them are negatively related with reliability.…”

Comparing with the joint importance under consideration of consecutive-k-out-of-n system structure changes

“…And it is widely used in specific practical scenarios, such as weighted voting system [5], multi-state windowing system [24], aerospace repeater system [21] etc. Recently, Ma, Wang, Cai, Si, and Zha [13] studied the production monitoring system, that is, when at least k consecutive monitors fail, there will be a blind zone, in which monitors with different reliability can be interchanged in use.…”

Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

“…A system is usually composed of some components with different functions [1]- [3]. Under certain environmental conditions, these components work with different functional intensity to accomplish the expected tasks of the system [4]- [6]. This functional intensity is called system performance [7], [8].…”