A synthetic control chart for monitoring process dispersion with sample range

A synthetic control chart for monitoring the changes in the standard deviation of a normally distributed process is proposed in this paper. The synthetic chart consists of the sample range (R) chart and the conforming run-length (CRL) chart. The R chart can be viewed as a special case of the synthetic chart. The operation, design and performance of this chart are described. Average run- length comparisons between other procedures and the synthetic chart are presented. It indicates that the synthetic chart is a good alternative for monitoring process dispersion. The variable sampling interval (VSI) schemes, as an enhancement to the synthetic chart, are discussed to further improve the chart performance. An example is presented to illustrate the application of synthetic chart and its VSI scheme.     

A Max-EWMA approach to monitor and diagnose faults of multivariate quality control processes

A new approach is developed in this paper to detect general mean shifts of multivariate quality control systems and to determine the quality characteristic(s) responsible for the shift. This approach takes advantage of both a decomposition method and an EWMA-based control statistics that are employed for multivariate normal distributions. In order to evaluate the performance of the proposed methodology, simulation studies are provided to estimate the in- and out-of-control average run lengths under different mean and variance shift scenarios. Simulation experiments are also given to compare the performances of the proposed procedure with the ones of the well-known MEWMA and MCUSUM methods. The results of the simulation studies show that while the proposed method is compatible to the other compared methods, it has a good ability of detecting the correct out-of-control characteristic(s) most of the times. At the end, a case study is provided to demonstrate the applicability of the proposed procedure.     

A nonparametric control chart based on the Mood statistic for dispersion

Control charts are used as a statistical process control (SPC) to distinct the presence of an assignable cause of variation in the process. The advantage of the nonparametric control charts is that the nonparametric charts can be useful in statistical process control problems when there is a lack of knowledge about the underlying process distribution. In this paper, the nonparametric control chart is considered based on the rank sum statistic for dispersion. In the case of small sample sizes, the exact control limits are derived. For the large sample sizes, the control limits are evaluated by using the normal and saddlepoint approximations. The nonparametric charting statistic is applied for the real data.     

A modified multivariate process capability vector

Process capability indices have been widely used in industries to assess the performance of the manufacturing processes. Various different multivariate capability indices have been introduced. In this paper, a new multivariate capability vector is proposed under the assumption of multivariate normality, to assess the production capability of the processes that involve multiple product quality characteristics. Also, we investigate the relation between this index and process centering, as well as the relation between this index and the lower and upper bounds of percentage of non-conforming items manufactured. Two real manufacturing data set are used to demonstrate the effectiveness of the proposed index.     

Integrating multivariate engineering process control and multivariate statistical process control

Multivariate engineering process control (MEPC) and multivariate statistical process control (MSPC) are two strategies for quality improvement that have developed independently. MEPC aims to minimize variability by adjusting process variables to keep the process output on target. On the other hand, MSPC aims to reduce variability by monitoring and eliminating assignable causes of variation. In this paper, the use of MEPC alone is compared to using the MEPC coupled with MSPC. We use simulations to evaluate the average run lengths (ARL) and the averages of the performance measure. The simulation results show that the use of both MEPC and MSPC can always outperform the use of either alone. To detect small sustained shifts of the mean vector, combing MEPC with a multivariate generally weighted moving average (MGWMA) chart (MEPC/MGWMA) is more sensitive than the MEPC/multivariate exponentially weighted moving average (MEWMA) chart and MEPC/Hotelling’s χ² chart. An example of the application, based on the proposed method, is also given.     

基于OMAP3530双核处理器的液晶视力测试仪研制

针对传统视力表及视力投影仪在视力测试时存在的问题,以美国德州仪器公司最新的双核处理器OMAP3530为核心,设计新型液晶视力测试仪,并对设计中涉及的一些关键问题进行讨论。由于采用LCD旋光器,使显示偏振图像成为可能,很好地满足视力测试的不同要求。介绍基于TI OMAP3530平台的液晶视力测试仪硬件和软件设计,重点讨论嵌入式Linux红外遥控驱动程序。     

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

In this article, we propose a control chart for detecting shifts in the covariance matrix of a multivariate process. The monitoring statistic is based on the standardized sample variance of p quality characteristics we call the VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these p variances. The reasons to consider the VMAX statistic instead of the generalized variance |S| are faster detection of process changes and better diagnostic features, which mean that the VMAX statistic is better at identifying the out-of-control variable. User’s familiarity with sample variances is another point in favor of the VMAX statistic. An example is presented to illustrate the application of the proposed chart.     

应用CUSUM控制图监控过程变差方法的比较

累积和控制图监控过程均值偏移的应用较多,而用于监控过程变差较少。在机械零、部件的大批量、高精度生产过程中,需要同时监控过程均值和变差。在介绍三种主要的监控变差的CUSUM控制图方法基础上,结合案例给予比较,并指出各自的不足之处。     

A new adaptive control chart for monitoring process mean and variability

Traditionally, an $\bar{X}$ chart is used to control the process mean, and an R chart is used to control the variance. However, these charts are not sensitive to the small shifts in the processes. The adaptive charts might be considered if the aim is to detect process changes quickly. In this paper, we propose a new adaptive single control chart which integrates the exponentially weighted moving average procedure with the generalized likelihood ratio test statistics for jointly monitoring both the process mean and variability. This new chart is effective in detecting the disturbances that shift the process mean, increase or decrease the process variance, or lead to a combination of both effects.     

A review of univariate and multivariate process capability indices

This paper offers a review of univariate and multivariate process capability indices (PCIs). PCIs are statistic indicators widely used in the industry to quantify the capability of production processes by relating the variability of the measures of the product characteristics with the admissible one. Univariate PCIs involve single-product characteristics while multivariate PCIs deal with the multivariate case. When analyzing the capability of processes, decision makers of the industry may choose one PCI among all the PCIs existing in the literature depending on different criteria. In this article, we describe, cluster, and discuss univariate and multivariate PCIs. To cluster the PCIs, we identify three classes of characteristics: in the first class, the characteristics related to the information of the process data input are included; the second class includes characteristics related to the approach used to calculate the PCIs; and in the third class, we find characteristics related to the information that the PCIs give. We discuss the strengths and weaknesses of each PCI using four criteria: calculation complexity, globality of the index, relation to proportion of nonconforming parts, and robustness of the index. Finally, we propose a framework that may help practitioners and decision makers of the industry to select PCIs.     

CAPP中工艺卡片的统计处理

采用Visual Basio6.0和SQLsever开发的CAPP工艺卡片管理系统,是集报表定制和工艺卡片的生成,输出及管理于一体的工艺卡片处理系统软件。     

Interpreting the out-of-control signal in multivariate control chart — a comparative study

Interpretation of the out-of-control signal poses a persistent problem in multivariate control chart owing to the limitations of available general methods like Hotelling T². Many research papers address these problems and present alternative approaches to diagnose faults in out-of-control conditions and to help identify aberrant variables. This work reviews the different methods and attempts to make a comparative study of some of these methods viz. Mason, Tracy and Young method (Journal of Quality Technology 27:99–108, 1995), Murphy method (The Statistician 36:571–583, 1987), Hawkins method (Technometrics 33:61–75, 1991) and Doganaksoy, Faltin and Tucker method (Communications in Statistics — Theory and Methods 20:2775–2790, 1991). A simulation approach was taken to generate data on various out of control situation and to compare the powers of different targeted methods. In control sate was characterised by a multi-variate normal with standardised mean and variance assuming intra-class correlation structure. Data were generated for different values of correlation and various out of control situation with respect to the shift of mean in one, two or more variables. Due to the limitations of using average run length as a performance criterion especially in case of skewed distribution of run length it was decided to use power as a measure of comparison. Situations in which the particular method works satisfactorily were identified with respect to correlation structure and pattern of shift of mean.     

基于波动轨迹图的多工序过程能力量测方法

为解决单工序单质量特性过程评价方法不能直接用于多工序多质量特性过程能力评价的问题,提出了一种基于工序波动轨迹图的多工序过程能力评价方法.首先,把各工序在不同时刻的状态,描绘在由过程偏移度和过程稳定度组成的工序流波动平面上,形成工序波动轨迹图.在此基础上,讨论了不同规范限情形下的过程能力与过程合格率之间的关系,并基于合格率构建了多工序过程的能力指数.依据建立的多工序过程能力指数和波动轨迹图,分析各工序改进的机会和方向.最后,以柴油机连杆加工为例说明了该方法的可行性.     

基于AutoCAD平台的工艺图表模块开发

针对制造企业提高工艺设计效率和质量的要求,提出了基于AutoCAD环境进行辅助工艺设计的解决方案.采用VBA结合Access数据库技术,使工艺数据在数据库、工艺卡片与模型文件之间进行传递,实现了工艺模板的定制、工艺卡片填写、数据库管理等功能,给出了系统的总体结构,并对其中的关键技术进行了论述.该方案的实现,为工具化CAPP的研究提供了新思路.     

质量控制图及其工序质量控制

简要介绍了质量控制图的基本特点,论述了质量控制图的选择方法,对比分析了四种计量值质量控制图的应用特点,以实例详细分析了应用控制图进行工序质量控制的方法.