A transformation-based multivariate chart to monitor process dispersion

Multivariate monitoring techniques such as multivariate control charts are used to control the processes that contain more than one correlated characteristic. Although the majority of previous researches are focused on controlling only the mean vector of multivariate processes, little work has been performed to monitor the covariance matrix. In this research, a new method is presented to detect possible shifts in the covariance matrix of multivariate processes. The basis of the proposed method is to eliminate the correlation structure between the quality characteristics by transformation technique and then use an S chart for each variable. The performance of the proposed method is then compared to the ones from other existing methods and a real case is presented.     

基于模糊阈值的质量控制图模糊诊断系统

针对质量控制及诊断过程中出现的不确定、模糊性问题,提出了一种基于模糊逻辑的推理系统。该系统由六个模糊推理子模块及一个聚合模块组成。每个子模块以控制图异常模式数据作为输入,通过模糊化确定异常模式发生的程度,用重心法解模糊后的输出,作为相应异因对输入异常模式的贡献度。不同子模块的输出结果采用模糊算子进行聚合,根据给定阈值对聚合结果排序,形成过程失控情况下异因查找的一个优先序列,并以优先级最高的异因作为排查对象,缩小查找范围,加速异常排除。最后,通过实例表明,该系统可以发现Minitab软件无法预警的质量异常,并可给出相应的排查方案。     

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.     

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.     

面向中小批量生产的CUSUM管理图工序过程在线监控

CUSUM管理图(累计和管理图)是面向中小批量生产的最主要的管理图,CUSUM管理图的工序过程在线监控是加工过程工序监控的一种先进技术.本研究首先概括了面向中小批量生产的CUSUM管理图的技术优势和计算模型,然后讨论了JAVA代码CUSUM管理图工序过程在线监控软件的设计,其中详细讨论了时序图和程序框图描述,然后用机床加工的原始数据作了仿真实验.仿真实验结果表明面向中小批量生产的JAVA代码CUSUM管理图的计算模型和工序过程在线监控软件是正确的、有效的和可用的.     

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。     

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.     

Control chart system with independent quality characteristics

This article proposes an algorithm to design a control chart system consisting of several individual control charts, each of which monitors one of s critical quality characteristics (dimensions) x_i of a product. All of the characteristics x_i are assumed to be independent of each other. The algorithm designs all the charts within a system in an integrative and optimal manner. Consequently, the performance characteristics of the overall system as a whole can be considerably improved and the product quality will be further enhanced. Such improvement is achieved with minimum additional cost and effort. Furthermore, the floor operators can utilize and understand the optimal control chart system as easily as the conventional system. Some useful guidelines have also been brought forth to aid the users in adjusting the control limits of the control charts in a system.     

用VC实现质量控制图的绘制与分析

介绍了利用Microsoft Visual C 6.0开发工具,在Windows平台上进行质量控制图的绘制和分析的方法。通过质量控制图,可以作出正确的判断,有效地监控生产过程中的质量变化情况。     

基于模糊数的不确定质量控制图及选型

为了利用常规控制图对产品质量特性或制造过程质量参数进行监控,提出模糊质量控制图,分析了模糊控制图的基本形式、描点数据的来源及其处理方法,设计了控制图判异准则。针对打点数据常用的四种模糊数类型,从控制图形态上分析了各自的控制宽严度。分析结果可以为不同控制要求下模糊控制图的选型提供决策依据。     

基于标准化变换的质量控制图研究

基于标准化变换的质量控制图一般应用在小批量环境下,对生产过程进行控制。分析标准化变换的准则,指出工序分析起到关键作用及能否对工序进行控制,不在于统计,而在于管理;通过对不同数据变换方式有效性的研究表明,各种标准化变换控制图的复杂性及灵敏性是不同的,因此要依工序分析的结果灵活采用各种标准化控制图。     

预控图在TS16949质量管理体系标准中的应用

介绍了预控图在企业贯彻TS16949质量管理标准中的具体应用,并举出应用实例,实现了生产作业准备的验证活动,满足了TS16949标准7．5．1．3条款的要求,达到过程预先控制的目的,使加工的产品符合要求。     

Estimating the change point of the parameter vector of multivariate Poisson processes monitored by a multi-attribute T 2 control chart

When a control chart signals an out-of-control condition, knowing when the process has really changed (the change point) accelerates the identification of the source of special causes and makes the corrective measures to be taken sooner. In this paper, a new multi-attribute T ² control chart based on two transformation methods is initially proposed to monitor the parameter vector of multi-attribute Poisson processes. Then, the maximum likelihood estimators (MLE) of the process change point designed for both linear trend and step change disturbances are derived. Next, using Monte Carlo simulation, we show the performances of the proposed estimators are satisfactory. Finally, through performance comparisons, we conclude the MLE of the change point designed for linear trends outperforms the MLE designed for step changes when a linear trend disturbance is present and conversely, the MLE of the change point designed for step changes outperforms the MLE designed for linear trend disturbances when the real change type is step change.     

A new EWMA monitoring design for multivariate quality control problem

In this paper, a new approach is proposed to detect shifts of a multivariate quality control system. To do this, first, the decomposition method in multivariate normal distribution is introduced. Then, a control statistics is defined, and its properties are explained. In order to understand the proposed methodology and to evaluate its performance, a numerical example is provided by simulation. Moreover, the in- and out-of-control average run length of the proposed method are compared with the ones from the well-known multivariate cumulative sum and multivariate exponential weighted moving average in different scenarios of shifts. The results of the simulation study show that the proposed methodology performs better than the other methods in detecting the shifts of the standard deviation and correlation.     

The optimal control limit of a G�CEWMAG control chart

The control chart is a widely used statistical process control tool that detects any process change and plays an important role in high-quality processes. In this paper, we design G?CEWMAG control chart which is sensitive to both small and large shifts. G?CEWMAG control chart combines G control chart with EWMAG control chart. The G control chart is based on a plot of the G statistic designed for quality control using attribute data. There is a drawback in G control chart. When it is applied to high-quality processes, it performs poorly in detecting small shifts. On the other hand, EWAMG control chart which apply the EWMA technique with attribute data to G statistics can quickly detect small shifts. G?CEWMAG control chart have the ?? ratio which represent the combination ratio of G control chart and G?CEWMAG control chart. A large ?? ratio makes the G?CEWMAG control chart sensitive to detecting large shifts. On the other hand, a small ?? ratio makes it sensitive to detecting small shifts. But problems arise when the G?CEWMAG control chart has an ?? ratio of 1. In this case, a slight numerical difference in average run-length between EWMAG and G?CEWMAG appears to exist when detecting small shifts. We suggest optimal control limits for designing the G?CEWMAG control chart which is sensitive both large and small shift for use in high-quality processes.     

智能自校正模糊控制在电厂再热汽温调节中的应用

再热汽温控制系统因其对象具有非线性、大惯性、大迟延等特点,成为火电厂较难控制的系统之一。文中设计了一种采用解析法描述控制规则的智能自校正模糊控制器来应用于再热汽温的调节系统。仿真结果表明在响应速度、鲁棒性能和控制精度等方面都具有相当大的优越性。