On-line SPC with consideration of learning curve

This work identifies a link between on-line statistical process control (SPC) and the learning effect for the process standard deviation (PSD) caused by the quality improvement (QI) program. The learning curve (LC) is used to describe and forecast, and the exponentially weighted root mean square control chart is used to monitor the progress in reducing PSD. A modification of the quality control chart (QCC) that considers LC of PSD is proposed. The reduction rate of PSD may be large during the initial stage of the QI program, and influences QCC construction. Simulation is used to compare the shift-detecting ability of the Shewhart- control chart and EWMA- control chart, without- and with- consideration of LC. The EWMA- chart with consideration of LC performs best. In comparison, the Shewhart- chart without LC consideration has almost no shift-detecting ability when the shift magnitude of the process mean is small, leading to rendering quality control ineffective.     

Analytic network process decision-making to assess slicing machine in terms of precision and control wafer quality

We discuss and develop a manufacturing quality yield model to forecast the 12 in silicon wafer slicing based on an analytic network process (ANP) framework. The ANP is a general theory of relative measurement used to derive composite-priority-ratio scales from individual-ratio scales that represent the relative influence of factors that interact with respect to the control criteria. Through its supermatrix, which is composed of matrices of column priorities, the ANP framework captures the outcome of dependence and feedback within and between clusters of factors. Additionally, the proposed algorithm can select the evaluation outcomes to identify the optimal machine of precision. Finally, results of the EWMA control chart and Process Capability Indices demonstrate the feasibility of the proposed ANP-based algorithm in effectively selecting the evaluation outcomes and in evaluating the precision of the optimal performing machines. We illustrate how the ANP model implemented for helping the engineer can find out the manufacturing process yield quickly and effectively.     

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。     

基于统计过程控制技术的钢卷质量控制

统计过程控制（Statistical Process Control, SPC）是生产过程质量控制的重要工具,包括过程监控、过程诊断与改进等一系列活动。详细阐述了此技术在钢卷质量控制方面的应用流程,并通过实例重点介绍了控制图在钢卷质量分析与控制中的应用。系统采集钢卷工艺数据,选择控制图对工艺参数进行监控,计算和分析工序的工序能力指数。发现工序失控时,分析原因并及时采取纠正预防措施,保证工艺的一致性和稳定性,提高工艺成品率。     

基于控制图算法的质量自动控制

对控制图原理进行研究，采用计算机实现统计量的计算和控制状态的判断，并与生产线上的自动检测设备、调节设备连接，实现质量自动控制的目的。避免手工绘制控制图的繁琐。     

基于控制图算法的质量自动控制

对控制图原理进行研究,采用计算机实现统计量的计算和控制状态的判断,并与生产线上的自动检测设备、调节设备连接,实现质量自动控制的目的,避免手工绘制控制图的繁琐。     

自适应EWMA控制图统计经济设计

针对自适应指数加权移动平均(AEWMA) 控制图统计经济设计问题, 给出AEWMA控制图统计经济设计模型, 提出一种在偏移区间上对AEWMA控制图进行设计的多目标优化方法. 针对不同的偏移区间优化了AEWMA控制图, 并将AEWMA控制图统计经济性能与指数加权移动平均(EWMA) 控制图相比较. 结果表明, 所提出方法优化设计的AEWMA控制图仍具有克服EWMA控制图的惯性问题的统计特性, AEWMA控制图的经济性能也优于EWMA控制图.

     

适应智能质量控制的多分类支持向量机

分析了现有控制图识别器在实际应用中存在的缺陷,并提出了一种基于支持向量机(SVM)的新方法．为了克服HAH多分类SVM(HAH SVM)的缺陷,提高识别速度和准确率,设计了一种有针对性的SVM多分类器进行模式识别．仿真实验结果表明,该方法相对现有的BP和HAH SVM方法能得到更高的识别率和识别速度,适合于工序的实时在线控制．     

An experimental evaluation of comprehensibility aspects of knowledge structures derived through induction techniques: A case study of industrial fault diagnosis

Machine induction has been extensively used in order to develop knowledge bases for decision support systems and predictive systems. The extent to which developers and domain experts can comprehend these knowledge structures and gain useful insights into the basis of decision making has become a challenging research issue. This article examines the knowledge structures generated by the C4.5 induction technique in a fault diagnostic task and proposes to use a model of human learning in order to guide the process of making comprehensive the results of machine induction. The model of learning is used to generate hierarchical representations of diagnostic knowledge by adjusting the level of abstraction and varying the goal structures between 'shallow' and 'deep' ones. Comprehensibility is assessed in a global way in an experimental comparison where subjects are required to acquire the knowledge structures and transfer to new tasks. This method of addressing the issue of comprehensibility appears promising especially for machine induction techniques that are rather inflexible with regard to the number and sorts of interventions allowed to system developers.     

基于Intranet的控制图系统

控制图的主要任务就是控制系统性差异造成的质量波动。提出了基于 Intranet的控制图系统设计方案 ,并讨论系统的组成、功能结构及具体的实现方法。现场的数据经控制图系统的统计运算 ,确定样本观测值的均值或加权均值、控制图中心线、控制图上下控制界限等统计量 ,并绘制相应的控制图形     

SPC数据采集与处理系统

SPC数据采集与处理系统实现了SPC数据的计算机采集与处理,大大提高了SPC分析的效率与准确性,对推动目前国内SPC应用,提高产品质量管理水平具有重要的现实意义。本文具体介绍了SPC数据采集与处理系统的结构与组成及软件实现和处理功能。     

Bicharacteristic quality control in manufacturing

In this paper, the importance of bicharacteristic quality control has been discussed, when it is desired to exercise process control on manufacturing products that present two measurable characteristics which can suffer variations and on the other hand are considered significant for the functioning or the acceptance of the product. The verification that the process is in control or not is made by examining periodically the items of the samples drawn and plotting the points representing the mean of the characteristic in analysis on the corresponding charts. Using the computational program developed, a practical application is carried out for a mechanical manufacturing component that presents two critical characteristics. Also, a programmable mathematical model has been developed, aiming to computationally determine the sample size, and the interval between successive samples, which minimize the expected total cost. Idealized numerical application illustrates the use of the cost model that optimizes these parameters.     

Measuring the performance improvement of a double generally weighted moving average control chart

This study extends the sum of squares generally weighted moving average (SS-GWMA) control chart by using the double generally weighted moving average (DGWMA) technique. The proposed expanded chart is called the sum of squares double generally weighted moving average (SS-DGWMA) control chart. Simulations are performed to evaluate the average run length (ARL) and standard deviation of run length (SDRL) of the SS-DGWMA, SS-DEWMA, and SS-GWMA charts. An extensive comparison shows that the optimal SS-DGWMA chart is superior to the optimal SS-GWMA and SS-DEWMA charts in all studied scenarios. The SS-DGWMA chart is also easy to implement and to interpret the abnormal signals.     

基于Labview开发统计过程控制软件

统计过程控制是质量管理的重要内容,介绍了SPC的原理,并用Labview软件实现了SPC软件.这种开发方法应用了Labview软件提供的统计过程控制模块,方便了程序的开发,很容易被质量人员掌握,设备改动或软件应用于别的设备时,只需简单地修改参数,大大方便了统计过程控制的普及,提高企业的质量水平.     

电能质量异常数据在线检测方法

电网电能质量监测数据大多数监测指标具有周期性变化规律、波动性大等特征,现有的异常数据检测方法在针对此类数据做异常值检测时具有适应性差等问题.针对上述问题,将控制图和时间序列数据预测方法有机结合,提出了基于控制图的动态阈值电能质量异常数据在线检测方法.利用电能质量数据的变化趋势数据替代控制图中心线,将控制图的控制线化直为...