包装机混合式自动定量控制系统的设计

简要介绍了混合式自动定量系统的原理,为了提高混合式自动定量系统的定量的速度和定量精度,针对一个具体的包装机设计了一个微机控制系统.该系统以单片微型计算机为核心,与称重传感器相连,具有数据采集的功能,同时具有控制加料、信息显示和主控微机通信的功能.该控制系统在包装机上具有较大的推广价值和一定的实效性.     

四维Qi系统的参数自适应控制

基于Routh-Hrtwitz稳定性理论及Hopf分岔理论分析了四维Qi系统第二类非零平衡点的动力学行为,并通过绘制分岔图及最大Lypunov指数谱验证理论分析结果。给出了基于系统变量为观测量的参数自适应控制器,该控制器能自动调整控制参数,在参数受到较大扰动的情况下保持系统渐近稳定,并利用Lyapunov直接方法证明了受控系统的全局稳定性。通过数值模拟证明了文中所给的控制方法具有较快的收敛速度。关键词：Qi系统 非零平衡点 参数自适应控制 参考模型     

BOPP膜8色凹版印刷自动套色控制系统的研究

介绍了BOPP膜8色凹版印刷自动套色控制系统的组成和原理,分析了利用光电自动检测系统测量Mark线的间距及获取套色误差的方法,并根据套色对象的模型提出套准控制的一种控制算法.该系统功能齐全,套印精度高,并具有较高的可靠性.     

协调加载控制及数据采集系统的自动校准设计

利用标准仪器的通信接口,在VEE Pro软件开发平台上设计出一套针对协调加载控制和数据采集系统的自动校准平台.该系统由仪器信息采集、伺服控制通道校准、数据采集通道校准、打印输出4个主模块组成,可实现实时显示、超差报警、自动处理数据及存档等功能.应用结果表明:自动校准平台高效、准确、可靠,在直升机研发试验中发挥出重要作用,具有广泛的应用前景.     

信号发生器自动计量系统的设计与实现

文章设计了一套适合通用型信号发生器的自动计量系统,该系统通过软件平台进行代码编写,硬件系统通过成熟的控制总线进行控制连接,能实现不同型号信号发生器的自动计量校准,达到降低人力成本、提升工作效率和准确度的目的。其良好的兼容性和实用性,使系统具有很好的推广应用价值。该自动计量系统已经广泛应用于工厂的信号发生器的自动检定。     

超精密定位的模糊神经网络控制

利用激光莫尔技术设计了一种超精密定位装置,系统以工业控制计算机为核心,通过光、机、电的有机结合,可实现高精度位置检测及精密自动定位.针对系统存在非线性,精确控制模型难以建立的缺陷,将模糊神经网络应用于该控制系统中,给出了模糊推理BP网络模型,改造后的模糊控制系统具有了知识自动获取功能,能更好地适应工况环境.实验结果表明使用模糊神经网络控制,控制响应快、稳定性好、鲁棒性强.系统取得了亚微米级的定位精度,对超精密加工具有实用价值.     

G/G/S系统队长的优化控制

制造系统生产流水线由于受随机干扰的影响,经常出现待加工工件积压或短缺的现象.针对这种情况,给出G/G/S系统队长控制图的优化设计方法.该方法对给定的第一类风险,结合工件短缺的惩罚费用和积压的存贮费用,提出合理度量控制图损失的损失函数及控制限确定方法.通过与已有方法的比较分析,证明该方法是有效、可行的.     

钣金CAPP系统的研制

本文介绍了一个适用于箱(壳)体的钣金CAPP系统。该系统采用特征图形法描述零件的几何信息,并应用创成原理,自动生成钣金件的工艺规程,系统还具有生成展开图功能,并能实现板材的半自动排料。     

基于图像处理方法的自动调焦系统的研制

介绍了基于图像处理方法的自动调焦系统的组成、工作原理、硬件电路设计和软件设计.该系统的核心是图像处理部分和控制部分.导出了计算聚焦量的三个快速算法公式,优化了系统的实时性能.详细分析了自动调焦的控制过程,并提出了渐变步长的思想,提高了系统的控制精度.实验结果表明,在较宽范围的光照度条件下,应用该系统均能获得良好的调焦效果.     

微小型零件自动装配的软件设计与实现

针对微小型零件的装配问题,搭建了四轴微装配系统,利用VC++平台开发了微小型零件自动装配软件,实现了可视化人机交互式装配.微装配系统软件设计模式采用分层架构的思想,通过分析类和对象的关系,采用创建类的方式封装了微装配软件系统架构的主要模块.软件模块包括运动控制、气动控制、图像采集与处理、模板数据管理、示教再现以及相机标定.采用面向对象的方式实现了各个模块间的数据交换,创建了机器视觉与示教再现相结合的自动装配控制模式.装配测试表明:该系统运行平稳,装配过程中无需人工干预,可以很好地实现不同尺寸微小型零件的自动装配;软件具有很好的重复性、人机交互性和稳定性.     

一种保证预设质量和过程稳态的SPC方法

提出三种过程质量指数(PQI)的过程质量指数系统,基于过程质量指数的统计公差提供了一个过程质量要求和控制图设计之间的标准化界面.通过基于过程质量指数的统计公差带增加对x--R或x--s控制图中线的约束,建立一种保证预设质量和过程稳态的统计过程控制新方法.这不仅增强了控制图的功能,也为过程质量规划、统计公差和保证预设质量的SPC相关参数的并行设计提供了指导.     

统计过程控制在微电脑控制器生产中的应用:案例研究

以某电子集团生产的某类型控制器的实际生产为例,采用因果分析法对其生产过程中造成质量缺陷的原因从5M1E(人、机、料、法、测、环)方面进行综合分析.通过对其测量系统进行监控,在其稳定可靠的情况下采集数据.运用SPC技术对波峰焊工序进行控制图监控,对失控原因进行分析并在线调整.有效地保证了控制器的质量,为其质量改善指明了方向.     

监控不合格品率的MEWMA-p控制图设计

传统Shewhart-p控制图只对单一属性的不合格品率进行监控,在过程发生偏移时有一定的滞后性。为提高不合格品率控制图的精度,提出一种多元指数加权移动平均不合格品率(multivariate exponentially weighted moving average p, MEWMA-p)控制图。该控制图将多个属性的不合格品率应用于多元指数加权移动平均控制图,可同时对多个属性进行监控,并且对于小范围的偏移更加敏感。对比分析同等偏移程度下指数加权移动平均不合格品率(exponentially weighted moving average p, EWMA-p)控制图与MEWMA-p控制图的平均运行长度(average run length,ARL)结果,并通过模拟仿真说明该方法的有效性。     

A mixed control chart to monitor the process

In this paper, we propose a mixed control chart to monitor the process quality using attribute data combined with variable data. The proposed control chart proceeds like an np control chart based on the number of nonconforming parts but requires variable data only when the decision is indeterminate. The control coefficients are determined by considering the in-control and the out-of-control average run lengths for various specified parameters. The extensive tables are provided for the industrial use. The advantages of the proposed control chart are discussed over the traditional np control chart.     

Integration of SPC and performance maintenance for supply chain system

In this paper, a supply chain system is viewed as a maintainable system, and the economic-statistical design of a likelihood ratio control chart with a maintenance application is considered for this system. The supply chain system is described by a three-state: normal state, warning state and failure state. A likelihood ratio control chart is used to monitor the system given that only categorical observations can be obtained. When the chart signals, a full inspection is performed to determine the actual system state (normal or warning), and preventive maintenance is immediately performed in the warning state. In addition, the supply chain system must be corrected upon failure (i.e. corrective maintenance), and should be maintained in a scheduled time (i.e. planned maintenance). A mathematical model is developed for the joint optimisation of the control chart parameters and planned maintenance time based on renewal theory. An example is presented to illustrate how to determine the optimal design parameters. We also investigate the effect of coefficients and statistical constraints on the decision variables and the expected cost.     

An Economic Approach to the Management of High‐Quality Processes

Modern manufacturing developments have forced researchers to investigate alternative quality control techniques for high‐quality processes. The cumulative count of conforming (CCC) control chart is a powerful alternative approach for monitoring high‐quality processes for which traditional control charts are inadequate. This study develops a mathematical model for the economic design of the CCC control chart and presents an application of the proposed model. On the basis of the results of the application, the economic and classical CCC control chart designs of the CCC control chart are compared. The optimal design parameters for different defective fractions are tabulated, and a sensitivity analysis of the model is presented for the CCC control chart user to determine the optimal economic design parameters and minimum hourly costs for one production run according to different defective fractions, cost, time, and process parameters. Copyright © 2012 John Wiley & Sons, Ltd.     

A multivariate CUSUM control chart for monitoring Gumbel's bivariate exponential data

Exponentially distributed data are commonly encountered in high-quality processes. Control charts dedicated to the univariate exponential distribution have been extensively studied by many researchers. In this paper, we investigate a multivariate cumulative sum (MCUSUM) control chart for monitoring Gumbel's bivariate exponential (GBE) data. Some tables are provided to determine the optimal design parameters of the proposed MCUSUM GBE chart. Furthermore, both zero-state and steady-state properties of the proposed MCUSUM GBE chart for the raw and the transformed GBE data are compared with the multivariate exponentially weighted moving average (MEWMA) chart and the paired individual cumulative sum (CUSUM) chart. The results show that the proposed MCUSUM GBE chart outperforms the other two types of control charts for most shift domains. In addition, an extension to Gumbel's multivariate exponential (GME) distribution is also investigated. Finally, an illustrative example is provided in order to explain how the proposed MCUSUM GBE chart can be implemented in practice.     

多品种小批量生产的SPC应用研究

综述了多品种小批量生产方式的特点以及该生产方式下SPC(统计过程控制)的应用现状,指出常规控制图不适用于多品种小批量生产的问题,提出结合通用控制图、累积和(Cumulative-Sum,CUSUM)控制图和指数加权移动平均(Exponentially Weighted Moving-Averages,EWMA)控制图的解决方法,并总结出该SPC方法用于处理多品种小批量生产中微小偏差的步骤。     

The variable sample size variable dimension T2 control chart

In this paper, we describe the development of the variable dimension and variable sample size T² control chart (VSSVDT²), which is an enhancement of the variable dimension T² chart (VDT²). In the VDT² control chart, the number of variables that are measured to compute the T² statistic is made variable. Some of the variables are easy or inexpensive to measure and are always monitored. The variables that are more difficult or expensive to measure are measured only when the T² value from the previous sample exceeds a specified threshold. The VDT² control chart performs well for moderate and large shifts in the mean vector. However, its performance for small shifts is poor. To improve the chart’s performance in detecting such shifts, we propose the application of the variable sample size technique to the VDT² control chart, resulting in the VSSVDT² control chart. To promote the use of the VSSVDT² chart, a user-friendly software has been developed, which the final user can use to find the best parameters of the VSSVDT² chart for a particular process.     

Cusum of Q chart with variable sampling intervals for monitoring the process mean

Recently, adaptive control charts (that is, with variable sample sizes and/or sampling intervals) for univariate or multivariate quality characteristics have received considerable attention in Phase II analysis in the literature. Due to insufficient samples to obtain good knowledge of the parameters in the start-up process, adding adaptive features to self-starting control charts remains an open problem. In this paper, we propose an adaptive Cusum of Q chart with variable sampling intervals for monitoring the process mean of normally distributed variables. A Fortran program is available to assist in the design of the control chart with different parameters. The effect of the control chart parameters on the performance is studied in detail. The control chart is further enhanced by finding adaptive reference values. Due to the powerful properties of the proposed control chart, the Monte Carlo simulation results show that it provides quite satisfactory performance in various cases. The proposed control chart is applied to a real-life data example to illustrate its implementation.