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The paper investigates a model of a k-out-of-n system, the residual lifetime of which changes after failures of any of its components. The problem of a Preventive Maintenance (PM) organization as advice to the Decision Maker (DM) for such a system is considered. The purpose of this paper is to propose a mathematical model of the k-out-of-n system to support DM about PM. For most practical applications, it is usually possible to estimate the lifetime distribution parameters of the system components with limited accuracy (only one or two moments), which is why special attention is paid to the sensitivity analysis of the system reliability characteristics and decisions about PM to the shape of system components lifetime distributions. In the numerical examples, we consider the 3-out-of-6 model discussed in our previous works for two real systems. The novelty, significance, and features of this study consist of the following, after the failure of one of the system components, the load on all the others increases, which leads to a decrease in their residual lifetime. We model this situation with order statistics and study the quality of PM strategies with respect to the availability maximization criterion. At the same time, we are focusing on the study of the sensitivity of decision-making to the type of lifetime distribution of system components. [ABSTRACT FROM AUTHOR]

In a previous paper, the problem of how the preventive maintenance organization for the k-out-of-n: F system could be used, in order to maximize system availability, was considered. The current paper continues these investigations using a different optimization criterion. The proposed approach is based on decision making theory for regenerative processes. We propose a general procedure for comparing different preventive maintenance strategies based on the ordered statistics distributions, aiming to choose the best one with respect to cost-type criterion. The lifetime distributions of system units are usually unknown and only one or two of their moments are available. For this reason, we pay special attention to the sensitivity analysis of decision making about preventive maintenance, taking into account the shape of the system unit lifetime distributions. A numerical study of two examples based on a real-world system illustrates the results of the proposed approach. [ABSTRACT FROM AUTHOR]

Environmental safety issues are of particular importance when we design and operate underwater transport systems. To ensure the transport systems function safely, special systems to monitor their condition are being created. Underwater pipeline monitoring systems should continuously operate to detect and prevent emergency and pre-emergency situations in a timely manner. The purpose of this article is to demonstrate the possibility of using a mathematical model of a k-out-of-n system to support decision-making in the preventive maintenance of an unmanned underwater vehicle to monitor the condition of a subsea pipeline. The novelty and feature of this study are that we investigate a strategy of preventive maintenance for a model of a k-out-of-n system, where failures depend not only on the number but also on the location of the failed components in the system. The method to solve this problem, based on the distribution of the members of the variational series of the failing components, is also new. Since the distributions of the system component lifetimes are usually known with an accuracy of only one or two moments, we paid special attention to how sensitive the decision making about preventive maintenance is to the shape of the distributions. Numerical examples are conducted in order to support the theoretical investigations of the paper. The results of the study are applied to specific equipment to monitor the state of the outer surface of the pipeline. [ABSTRACT FROM AUTHOR]