Modeling and analysis of a mixed‐model assembly line with stochastic operation times

We consider a mixed‐model assembly line (MMAL) comprised a set of workstations and a conveyor. The workstations are arranged in a serial configuration. The conveyor moves at a constant speed along the workstations. Initial units belonging to different models are successively fed onto the conveyor, and they are moved by the conveyor to pass through the workstations to gradually generate final products. All assembling tasks are manually performed with operation times to be stochastic. An important performance measure of MMALs is overload times that refer to uncompleted operations for operators within their work zones. This paper establishes a method to analyze the expected overload times for MMALs with stochastic operation times. The operation processes of operators form discrete time nonhomogeneous Markov processes with continuous state spaces. For a given daily production schedule, the expected overload times involve in analyzing the Markov processes for finite horizon. Based on some important properties of the performance measure, we propose an efficient approach for calculating the expected overload times. Numerical computations show that the results are very satisfactory. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Combining standardized time series area and Cramér–von Mises variance estimators

We propose three related estimators for the variance parameter arising from a steady‐state simulation process. All are based on combinations of standardized‐time‐series area and Cramér–von Mises (CvM) estimators. The first is a straightforward linear combination of the area and CvM estimators; the second resembles a Durbin–Watson statistic; and the third is related to a jackknifed version of the first. The main derivations yield analytical expressions for the bias and variance of the new estimators. These results show that the new estimators often perform better than the pure area, pure CvM, and benchmark nonoverlapping and overlapping batch means estimators, especially in terms of variance and mean squared error. We also give exact and Monte Carlo examples illustrating our findings.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

虚拟现实与仿真技术在火控系统中的应用

简述了虚拟现实(VR)的概念、基本特征及其系统体系结构,探讨了虚拟现实(VR)与系统仿真的关系,介绍了其在火控系统中的应用.     

航测平台监测系统的开发应用研究

航测平台监测系统是在航测平台系统的调试开发过程中,根据工程的实际需要开发完成的.系统具有硬件实现简单、软件灵活、独立性强、易于扩展等特点.对该系统的组成、设计实现方法做了详细的介绍,对系统进一步的研究进行了探讨,并对系统开发应用中的特点进行了分析.通过实际应用,证明该系统具有一定的工程应用和研究意义.     

系统建模技术初探

为了对系统建模技术有一个总体认识,本文采用归纳和分析的方法,对系统建模技术的体系结构进行了初步探讨。     

外卡式传感器特征参数的提取与分析

基于试验所检测到的压力波形,通过分析燃油喷射过程,提取了压力波形的特征参数,着重给出了特征点识别的新算法,井用MATLAB开发了相应软件。最后,根据识别结果,分析了调整参数对特征参数的影响。     

确定相对体制雷达对不同飞机性能的检飞标准

如何在不同检飞机型的条件下,检验防空导弹武器系统制导雷达的性能,是工程上亟待解决的技术问题。将实践经验和理论分析充分结合,本着经济实用的原则,提出了"对比检飞、等信噪比和等概率"的指标转换方法,确定了不同检飞机型的评定标准。通过实际应用,证明确定的标准切合实际。     

基于多Agent的多传感器仿真系统总体分析

多传感器是实现未来信息化战场"网络中心战"概念的一组必要的装备系统.实施该项目先期概念技术演示,必须设计其仿真系统.采用基于多Agent的仿真方法,结合Agent的通用含义及结构,把多传感器仿真系统的内部组元直接映射成相应的Agent.由此,研究了基于多Agent的信息化战场多传感器仿真过程,前瞻了多传感器运用场景,分析了多传感器仿真系统的整体流程和逻辑结构.设计的多传感器仿真系统,以Agent的表现形式获得了对多传感器战场运用这一客观、复杂过程的深刻认识,从而可实现对这种动态作战环境行为的仿真.     

基于神经网络的离散变结构控制系统

系统研究了基于神经网络的离散变结构控制系统设计方法,提出了几种具体设计方案.神经网络的引入可以使滑模(变结构)控制具备学习与自适应能力,使控制信号得以柔化,从而能够减轻或避免困扰常规滑模控制器的抖振现象,改善控制效果.     

航天试验指挥自动化系统体系结构

随着各种航天试验和航天器进入现代高技术局部战争,逐步形成了一体化的战争格局,提高航天试验指挥效能成为现代天战的迫切需求。体系结构是从顶层设计的角度,对指挥自动化系统进行的一种"统一的和概念的"描述。分析了航天试验指挥自动化系统的概念、结构组成及系统连接关系,研究航天试验指挥自动化系统的体系结构,对航天试验指挥自动化系统进一步发展和完善提供指导。