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Availability evaluation and design optimization of multi-state weighted k-out-of-n systems

机译:多状态加权K-Out-N个系统的可用性评估和设计优化

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The multi-state weighted k-out-of-n system model can illustrate the performance and reliability/availability relationship between components and system so that attracted more and more attentions in recent years. Under the condition that the state probabilities of components are dynamically changing with time, this paper presents a generalized instantaneous availability model for multi-state weighted k-out-of-n systems and an efficient Genetic Algorithm (GA) is proposed to compute optimal reliability and performance design values for components. Firstly, a Universal Generating Function (UGF) approach is developed to efficiently determine the availability of system assuming the state probability distributions of multi-state components follow the non-homogeneous continuous time Markov process. And then, taking into consideration of availability and cost constraints respectively, two design optimization models are set up to obtain the optimal design solutions for component via improved GA. Finally, an example analysis of transportation systems in a naval shipyard is shown to demonstrate effectiveness of the proposed model. Our results show that the improved GA can enhance the applicability of design results and conclusions of our paper can provide clear policy recommendations for design optimization of multi-state weighted k-out-of-n system.
机译:多态加权K-Out-N个系统模型可以说明组件和系统之间的性能和可靠性/可用性,以便近年来吸引了越来越多的注意。在部件的状态概率随时间动态变化的情况下,本文提出了一种用于多态加权K-OUT-N系统的广义瞬时可用性模型,提出了一种有效的遗传算法(GA)来计算最佳可靠性和组件的性能设计值。首先,开发了通用生成功能(UGF)方法以有效地确定假设多状态分量的状态概率分布遵循非均匀连续时间马尔可夫过程的系统的可用性。然后,考虑到可用性和成本约束,设置了两个设计优化模型,以通过改进的GA获得组件的最佳设计解决方案。最后,显示了海军造船厂的运输系统的示例分析,显示了拟议模型的有效性。我们的研究结果表明,改进的GA可以提高设计结果的适用性,我们的论文的结论可以为多州加权K-Out-N系统的设计优化提供明确的政策建议。

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