用于监控过程均值的DMHWMA控制图

在已经存在的多元均匀加权移动平均(Multivariate Homogeneously Weighted Moving Average, MHWMA)控制图的基础上,提出了一种用于监控过程均值的双多元均匀加权移动平均(Double Multivariate Homogeneously Weighted Moving Average,DMHWMA)控制图。并且与现有的控制图一样,DMHWMA控制图的平均运行长度只与偏移系数有关。通过蒙特卡罗模拟实验,比较了在不同程度的过程均值偏移下DMHWMA控制图与MHWMA控制图、多元指数加权移动平均(Multivariate Exponentially Weighted Moving Average,MEWMA)控制图、多元累积和(Multivariate Cumulation Sum, MCUSUM)控制图的平均运行长度特性。结论表明,不论过程均值发生多大程度的偏移,DMHWMA控制图的对过程均值变化的监控敏感度都明显优于其他控制图。并且通过一个实例数据验证了上述模拟实验结论的正确性。     

基于反馈调整的自相关过程质量损失分析

传统的SPC要求过程观测值统计独立,而实际过程大多具有自相关性,不满足统计独立的要求。在SPC与EPC的整合框架下,分析了自相关过程的质量损失。根据模型的自相关系数(ACF)和偏相关系数(PACF)以及选择迭代算法识别模型参数;采用MMSE反馈控制器对自相关过程进行调整,并结合过程能力,对自相关过程的质量损失进行分析。结果表明,在MMSE反馈调整后,自相关过程质量损失才符合实际情况。     

一种面向二阶动态过程的集成控制方法

针对较为复杂的二阶动态过程和稳态干扰ARMA（1,1）组成的系统模拟制造过程,采用SPC与EPC整合的集成过程控制方法,实现对全过程的监控。整合的关键是EPC控制器的设计。将状态空间分析法引入到对EPC控制器的设计中,并通过分析MMSE和PID控制器的状态空间模型,得出EPC控制器的一般设计模型。最后通过仿真实验,比较MMSE、PI控制器和文中设计的控制器的监控性能,验证了该方法的有效性。     

基于离散Hopfield网络的自相关过程控制方法

对于自相关过程的统计控制,传统统计学方法虚发警报的概率较大,而BP人工神经网络方法权值训练困难,灵敏度不高。提出一种基于联想学习与离散Hopfield网络的自相关过程控制方法。不需任何训练样本,通过正交化编码将过程状态以吸引子的形式存储到Hopfield网络中,并利用网络的联想功能来检测自相关过程的阶跃型突变。算例研究表明,与Elman网络和EWMA方法相比,过程正常时,所提方法的平均链长（ARL）分别提高了27.9%和55.0%;过程异常时,所提方法的ARL分别降低了74.1%与81.8%以上。说明了方法的有效性与优越性。     

统计过程监测与反馈控制的整合: 状态空间下的一般方法

将状态空间模型引入统计过程监测,选取状态变量为统计过程控制(SPC)统计量,以解决自相关过程的统计监测问题.在分析常用的最小均方误差(MMSE)和PID控制器的基础上,提出了工业过程控制(EPC)反馈控制器的一般设计方法和基本设计原则.作为演绎示例,给出了两组新型反馈控制器,并与MMSE和PID的反馈调整进行比较,当过程均值发生阶跃扰动时,可进一步提高统计监测效果.     

基于多重相关状态采样的多元EWMA控制图

为提高控制图的监测效率,提出了一种基于多重相关状态采样的多元EWMA控制图,并利用改进后的马尔可夫链方法计算控制图的平均运行长度。根据不同参数下控制图的平均运行长度,分析了控制图在失控和受控状态下的性能表现,并与其它多元EWMA控制图进行比较。模拟结果表明,该控制图具有良好的监测能力。最后用一组模拟数据来说明该方法的使用。     

基于概率神经网络的控制图模式识别

近年来,人工神经网络被广泛应用于复杂过程质量异常的监控中.文献表明人工神经网络方法存在结构选择困难的问题,其解决主要通过研究人员的经验,耗时多且识别率低.本文提出使用概率神经网络来识别六类典型控制图模式,以改进神经网络识别器的设计效率.研究和仿真试验结果表明,概率神经网络不仅拓扑结构设计简单,而且识别率高.     

基于统计过程控制的软件过程管理

真正有效管理软件过程的关键是定量管理。统计过程控制是判断软件过程是否异常,预测过程未来行为的重要工具。把统计过程控制技术融合到软件开发过程中,可以实现对软件过程的定量管理,也有助于组织更快地实现CMMI 4/5目标。     

一种基于SPC的软件过程质量分析方法

一个项目的开发活动是很多软件过程的集合,不同软件过程之间关联性很强,成功地分析特定软件过程质量的关键是确保软件过程分析的独立性,剔除来自于其他过程的影响。传统Shewhart控制图基于统计假设检验理论,能够区分软件过程中的偶然因素和系统因素,但Shewhart控制图是全控图,无法区分过程之间的影响。为解决这种问题,定义软件过程的总质量和分质量,把系统因素细分为外部系统因素和内部系统因素,并总结软件过程质量诊断表,以使用控制图和选控图来帮助诊断导致软件过程质量异常的偏差源。     

统计过程监测中低阶EPC控制器分析与设计

观测值相互独立并服从正态分布是应用统计过程控制(SPC)的基本前提,然而由于某些不可消除因素,实际过程的输出观测值常常是自相关的。采用SPC与EPC整合,消除过程自相关,实现对自相关过程的监控。将状态空间分析法引入到EPC控制器的设计中,通过极点配置方法来分析EPC控制器的性能,研究平均运行链长(ARL)与极点配置的关系。最后对均值发生阶跃型故障的自相关ARMA(1,1)过程进行仿真实验,得到EPC控制器极点的较优配置范围。仿真结果亦证明了该方法的可行性和有效性。     

A hybrid fuzzy adaptive sampling - Run rules for Shewhart control charts

In crisp run control rules, usually it is stated that a process moves very sharply from in-control condition to out-of-control act. This causes an increase in both false-alarm rate and control chart sensitivity. Moreover, the classical run control rules are not implemented on an intelligent sampling strategy that changes control charts’ parameters to reduce error probability when the process appears to have a shift in parameter values. This paper presents a new hybrid method based on a combination of fuzzified sensitivity criteria and fuzzy adaptive sampling rules, which make the control charts more sensitive and proactive while keeping false alarms rate acceptably low. The procedure is based on a simple strategy that includes varying control chart parameters (sample size and sample interval) based on current fuzzified state of the process and makes inference about the state of process based on fuzzified run rules. Furthermore, in this paper, the performance of the proposed method is examined and compared with both conventional run rules and adaptive sampling schemes.     

Non-parametric confidence bounds for process performance monitoring charts

Statistical Process Control (SPC) provides a tool for achieving and maintaining product quality. In today's climate of major data monitoring campaigns there has been an increase in interest in the multivariate statistical projection techniques of principal components analysis and projection to latent structures for process performance monitoring. Within univariate SPC, techniques for identifying when a process is moving out of control are well established. Similar guidelines are required for multivariate statistical process control (MSPC). Two approaches will be discussed - Hotelling's T² statistic and a new approach, the M² statistic. Both approaches will be illustrated by application to a high pressure low density polyethylene tubular reactor and to a batch methyl methacrylate polymerisation reactor.     

New EWMA control charts for monitoring process dispersion

There exist two EWMA-type dispersion charts for monitoring dispersion increases in the literature. One resets the EWMA statistic to zero whenever it is below zero. The other one truncates negative normalized observations to zero in the EWMA statistic. This paper proposes two one-sided EWMA charts for detecting dispersion increases and decreases, respectively, and one two-sided EWMA chart for monitoring dispersion increases or decreases simultaneously. Simulation studies show that the proposed upper-sided EWMA chart performs better than the two existing counterparts for detecting increases in dispersion, and that the proposed lower-sided EWMA chart significantly outperforms the two lower-sided EWMA charts developed similar to their two existing upper-sided EWMA charts for detecting decreases in dispersion. Moreover, the proposed two-sided EWMA chart provides much better sensitivity than the two two-sided EWMA charts generalized from the two existing upper-sided EWMA charts for detecting overall changes in dispersion.     

Performance evaluation methodologies for abstract data type implementation techniques

The runtime management system for a programming language must allow the efficient manipulation of complex objects, such as instances of abstract data types (ADTs). We describe an implementation model for ADTs based on coroutine objects (i.e. as an alternative to ad hoc modifications of the runtime stack). We evaluate the performances of variants of our implementation model using two different approaches: a benchmarking technique which monitors actual costs for test programs and a “pseudo-execution” technique which estimates costs based on idealized instruction timings. The results of our comparison indicate that the two forms of evaluation give very similar cost estimates, supporting the use of the (cheaper) pseudo-execution technique. The overall performance results identify applications in which our coroutine implementation model has definite strengths and weaknesses. Finally, our implementation approach is compared with modified stack implementations used in other ADT systems.     

A variable parameter Shewhart control scheme for joint monitoring of process mean and variance

This paper presents a new Statistical Process Control model for the economic optimization of a variable-parameter control chart monitoring a process operation where two assignable causes may occur, one affecting the mean and the other the variance of the process. Therefore, it is possible for the process to operate in statistical control, when none of the two assignable causes has occurred, or under the effect of one or both the assignable causes. By making the assumption that the occurrence rate of each assignable cause is exponential, a Markov chain approach is utilized to determine the probabilities that the process operates at any of the above possible states. The model uses an economic (or an economic/statistical) optimization criterion for the time to the next sampling instance, the size of the next sample, as well as the control limits of the inspection. That is, all design parameters of the control scheme are selected so as to minimize the total expected quality-related costs. The superiority of the proposed model is estimated by comparing its expected quality control cost vs. the outcome of the Fp (Fixed-parameter) Shewhart control chart, the Variable Sample Size (VSS) control chart, the Variable Sampling Interval (VSI) and the Variable Sample Size and Sampling Interval (VSSI) control chart, for a benchmark of examples. The numerical investigation indicates that the economic improvement of the proposed model may be significant.     

A variable parameter Shewhart control scheme for joint monitoring of process mean and variance

This paper presents a new Statistical Process Control model for the economic optimization of a variable-parameter control chart monitoring a process operation where two assignable causes may occur, one affecting the mean and the other the variance of the process. Therefore, it is possible for the process to operate in statistical control, when none of the two assignable causes has occurred, or under the effect of one or both the assignable causes. By making the assumption that the occurrence rate of each assignable cause is exponential, a Markov chain approach is utilized to determine the probabilities that the process operates at any of the above possible states. The model uses an economic (or an economic/statistical) optimization criterion for the time to the next sampling instance, the size of the next sample, as well as the control limits of the inspection. That is, all design parameters of the control scheme are selected so as to minimize the total expected quality-related costs. The superiority of the proposed model is estimated by comparing its expected quality control cost vs. the outcome of the Fp (Fixed-parameter) Shewhart control chart, the Variable Sample Size (VSS) control chart, the Variable Sampling Interval (VSI) and the Variable Sample Size and Sampling Interval (VSSI) control chart, for a benchmark of examples. The numerical investigation indicates that the economic improvement of the proposed model may be significant.     

Behavior of EWMA type control charts for small smoothing parameters

A general family of EWMA charts is considered for monitoring an arbitrary parameter of the target process. The distribution of the run length is analysed for the case when the smoothing parameter tends to zero. The key impact on the results from the use of the exact variance of the control statistics vs. the asymptotic one and the presence of a head start. For fixed head start, the run lengths for both the exact and asymptotic monitoring procedures degenerate to a binary quantity. To guarantee a feasible monitoring procedure, the head start has to be chosen proportional to the smoothing parameter and the control statistics have to be modified when used with the asymptotic variance. This result underlines the weakness of schemes with a fixed head start and of schemes based on the asymptotic variance if the smoothing parameter is small. The assumptions on the target process are very weak, and are usually satisfied for stationary processes. In addition, the asymptotic equivalence of the EWMA schemes and of repeated significance tests is shown.     

Box Car过程数据压缩算法性能分析

Box Car过程数据压缩算法在现场总线控制系统中得到广泛采用。其压缩效果受记录限和压缩区间的影响。本文基于对典型仿真数据的大量计算，分析了Box Car过程数据压缩算法记录限和压缩区间对趋势平稳的过程数据的压缩比、计算时间和压缩系数的影响。本文还分析了过程数据趋势特片和波动特性对Box Car算法压缩比和逼近系数的影响。本文的计算结果对于在实际应用中根据过程数据不同的趋势和噪声特征调整Box Car压缩算法参数以获得理想的压缩效果具有指导意义。     

Box Car过程数据压缩算法性能分析

Box Car过程数据压缩算法在现场总线控制系统中得到广泛采用。其压缩效果受记录限和压缩区间的影响。本文基于对典型仿真数据的大量计算,分析了Box Car过程数据压缩算法记录限和压缩区间对趋势平稳的过程数据的压缩比、计算时间和压缩系数的影响。本文还分析了过程数据趋势特征和波动特性对Box Car算法压缩比和逼近系数的影响。本文的计算结果对于在实际应用中根据过程数据不同的趋势和噪声特征调整Box Car压缩算法参数以获得理想的压缩效果具有指导意义。     

Performance evaluation of compromised synchronization control mechanism for distributed virtual environment (DVE)

Synchronization in a distributed virtual environment (DVE) involves mechanisms to ensure a consistent view of a virtual world for all participants. Most applications in the DVE are related to collaborative activities that include non-contention and contention cases. Using transmission of update messages is suitable enough to support synchronization for only non-contention activity. The contention activity requires an additional mechanism to control accessing a common object for synchronization. In this paper, we present the compromised synchronization control mechanism to support both non-contention and contention activities. The mechanism employs frequent update event and multiple-lock checking to control the synchronization. Frequent update event is used to support a dynamic virtual world for non-contention activity. Multiple-lock checking is embedded to ensure consistency when accessing the common object is required simultaneously for the contention event. Performance measurement of the compromised synchronization is provided by simulation in terms of locking time, sampling event, number of logical processes, and traffic tolerance. Prototype application is also implemented to compare the result in a small scale level. Based on the simulation and experimental results, the compromised sychronization control mechanism is capable to support up to 100 participants for the non-contention activity. It provides a good performance of supporting the contention activity in a small scale. The mechanism is considered suitable for collaborative application where contention is considered a critical event.