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     

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.     

一类伴随型非线性系统的快速变结构控制

基于反馈线性化、时间次优控制及变结构控制理论,针对一类伴随型不确定非线性系统,提出了一种快速鲁棒变结构控制方案。这种控制方案在控制有约束的条件下,其中一部分用来把非线性系统反馈校正成线性系统,另一部分则用来为线性系统实现时间次优控制。仿真结果表明：这种控制器不仅动态响应快,而且从初始时刻开始就可产生滑模运动,从而增强了系统鲁棒性。     

非标准气象条件弹道自动修正的研究

针对某强击机瞄准具轰炸性能改进装置,介绍非标准气象条件下弹道修正原理工作式的建立、修正电路的设计及其与瞄准具的交联关系     

火场中A3钢的晶粒度与燃烧时间和温度关系的研究

本文模拟典型火灾温度－时间曲线,对热轧成的Ａ３钢进行受热处理,测定在不同燃烧时间和温度下Ａ３钢的晶粒度,给出了Ａ３钢的晶粒度与燃烧时问和温度之间的定量关系,提出了通过测定Ａ３钢晶粒度的大小来鉴定火场中不同部位的燃烧时间和温度的科学方法     

广州市邮件业务量对确定运能需求的研究

为了合理利用车辆资源,为决策提供理论依据,本文采用多元统计回归分析法与模糊数学优化法,为广州市邮政局车辆运能研究,建立了数学模型,并附有项目软件,计算结果与实际情况吻合较好。这样,对合理利用邮政车辆资源,提高运营效率,具有一定的意义。     

一类折扣型投资模型的最优停止

本文对一类折扣型投资模型进行研究，给出了一个明确的停止规则。     

机动车辆自动识别系统

基于视觉的机动车辆自动识别方法工程量小、检测范围大、系统安装相对灵活，是一种很有前途的方法。目前已开发的商业系统大都用在日间辅助交通管理上。为改善视觉交通检测系统的实用性和增强系统的功能，本文作者对模型系统进行了深入的理论研究，提出了２．５维图像的新思路，提取车辆外形的综和特征更为准确，自适应识别方案使车型识别准确灵活，车头颜色特征的利用使识别的准确性进一步提高。实验证明，系统对光线的适应能力也明显增强，系统的稳定性得到改善，有望扩大系统的使用范围。     

DEC UNIX 操作系统的实时特性及评测

实时操作系统是复杂实时系统的一个重要组成部分，它必须是可预测的。本文首先简要阐述了 Ｄ Ｅ Ｃ Ｕ Ｎ Ｉ Ｘ ４．０ 操作系统的实时特性；然后开发了一种简单有效的实时操作系统性能评测方法，并给出了我们在 Ｄ Ｅ Ｃ Ａｌｐｈａ 系列机上对 Ｄ Ｅ Ｃ Ｕ Ｎ Ｉ Ｘ ４．０ Ｂ进行评测的过程和结果。