Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

The building evacuation problem with shared information

In this article, the Building Evacuation Problem with Shared Information (BEPSI) is formulated as a mixed integer linear program, where the objective is to determine the set of routes along which to send evacuees (supply) from multiple locations throughout a building (sources) to the exits (sinks) such that the total time until all evacuees reach the exits is minimized. The formulation explicitly incorporates the constraints of shared information in providing online instructions to evacuees, ensuring that evacuees departing from an intermediate or source location at a mutual point in time receive common instructions. Arc travel time and capacity, as well as supply at the nodes, are permitted to vary with time and capacity is assumed to be recaptured over time. The BEPSI is shown to be NP‐hard. An exact technique based on Benders decomposition is proposed for its solution. Computational results from numerical experiments on a real‐world network representing a four‐story building are given. Results of experiments employing Benders cuts generated in solving a given problem instance as initial cuts in addressing an updated problem instance are also provided. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

电子时间引信检测仿真试验研究

为提高电子时间引信的检测能力，介绍了电子时间引信检测仿真试验，分析了仿真试验的原理，给出了检测仿真试验的试验方法。经实际检测表明，该检测仿真试验能够安全可靠地完成电子时间引信的日常检测任务。     

一种新的基于粗糙集的连续属性离散化算法

粗糙集理论作为一种新的处理含糊和不确定性问题的数学工具,已成为国际学术界的一个前沿的研究领域.传统的粗糙集理论只能对数据库中的离散属性进行处理,而绝大多数现实的数据库既包含了离散属性,又包含了连续属性.针对传统粗糙集理论的这一缺陷,提出了一种改进的基于断点重要性的属性离散化方法.最后,通过实例分析说明该方法是有效的.     

使用双水压传感器抗风浪干扰原理

提出了在水雷上使用双水压传感器的设想.传统水雷只使用一个水压传感器,提供的信号信息稍嫌不足,给水压引信抗风浪干扰带来了限制.通过使用两个传感器,利用海浪水压场传播时在两个传感器上的时延信息,使用抵消方法压制海浪水压信号.初步分析表明,使用双传感器可以使水压引信抵抗一定的海浪水压信号的干扰.     

Nonperiodic preventive maintenance for repairable systems

As a complex system with multiple components usually deteriorates with age, preventive maintenance (PM) is often performed to keep the system functioning in a good state to prolong its effective age. In this study, a nonhomogeneous Poisson process with a power law failure intensity is used to describe the deterioration of a repairable system, and the optimal nonperiodic PM schedule can be determined to minimize the expected total cost per unit time. However, since the determination of such optimal PM policies may involve numerous uncertainties, which typically make the analyses difficult to perform because of the scarcity of data, a Bayesian decision model, which utilizes all available information effectively, is also proposed for determining the optimal PM strategies. A numerical example with a real failure data set is used to illustrate the effectiveness of the proposed approach. The results show that the optimal schedules derived by Bayesian approach are relatively more conservative than that for non‐Bayesian approach because of the uncertainty of the intensity function, and if the intensity function are updated using the collected data set, which indicates more severe deterioration than the prior belief, replacing the entire system instead of frequent PM activities before serious deterioration is suggested. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于前景理论的CGF Agent决策建模研究

前景理论(Prospect Theory,PT)描述了个体在不确定条件下的决策规律,较好地刻画了决策者的风险偏好。分析表明,PT在作战决策建模中具有一定的适用性和可行性。提出了一种基于PT的计算机生成兵力(Computer Generated Forces,CGF)Agent决策建模方法,给出了CGF Agent的建模框架,对CGF Agent决策过程中方案选择的具体步骤和算法进行了详细阐述。实验表明,所提出的方法在一定程度上提高了CGF Agent决策行为的真实性,证明了所提出方法的有效性。     

基于无线双工通信系统分组数据传输的探讨

分析了军用无线双工通信系统数据传输资源,指出了存在的问题及改进办法;利用话音、报文、传真、数据电路交换信令的工作模式标示,提出了基于无线双工通信系统的数据传输TCP/IP结构体系及协议栈,并探讨了网络适配和实现与军用公共数据网、地域通信网（电路交换网、分组交换网）、数字化部队单工无线电数据网互联的关键技术。     

Cell structure of microcellular combustible object foamed by supercritical carbon dioxide

In order to solve the issue that the combustible objects for cased telescoped ammunition (CTA) didn't burn completely during the combustion process, the microcellular combustible objects were foamed with numerous cells in the micron order to improve the combustion performance by the supercritical carbon dioxide (SCCO₂) foaming technology. As the cell structure determined the combustion properties of microcellular combustible objects, the solubility of SCCO₂ dissolved into the combustible objects was obtained from the gravimetric method, and scanning electron microscope (SEM) was applied to characterize the cell structure under various process conditions of solubility, foaming temperature and foaming time. SEM images indicate that the cell diameter of microcellular combustible objects is in the level of 1 μm and the cell density is about 10¹¹ cell⋅cm⁻³. The microcellular combustible objects fabricated by the SCCO₂ foaming technology are smooth and uniform, and the high specific surface area of cell structure can lead to the significant combustion performance of microcellular combustible object for CTA in the future.     

Empirical Biases and Some Remedies in Estimating the Effects of Selective Reenlistment Bonuses on Reenlistment Rates

Researchers have, for decades, been attempting to estimate the effects of Selective Reenlistment Bonuses (SRBs) on the probability of reenlistment for the military services. SRBs are targeted to specific military occupations for which reenlistment rates are lower (or expected to be lower) than what is needed. This article first identifies four primary sources of biases affecting these models: reverse causality from supply shifts (a negative bias), the endogeneity of the decision point causing coded SRBs to be higher for reenlisters than leavers (a positive bias), measurement error (a likely negative bias), and excess supply preventing the full effect of an SRB change to materialize (a positive or negative bias). The report proceeds to develop a model that attempts to address the first two biases. With U.S. Navy data from FY2001-FY2008, I examine the extent to which these two biases are affecting the estimated SRB effects. Despite these corrections, the difficulty of addressing the other biases calls into doubt studies that examine the effects of retention bonuses or even the effects of the structure of military pay in general.