Control charts applications for multivariate attribute processes

Two procedures were proposed for the construction of control charts to monitor multivariate process based on multi-dimenstional linguistic data. The first is based on probability theory and the second on the fuzzy theory. The performance of resulting control charts and their sensitivity to process shift are presented. These procedures are applied to a real data example. This real data application allow us to illustrate the implementation and the use of the proposed charts. Comparison of these charts is based on the ARL following a predefined process shift. A new procedure for interpreting out-of-control signals is also developed.     

A genetic algorithm approach to determine the sample size for attribute control charts

Determining the sample size for control charts (CCs) is generally an important problem in the literature. In this paper, Kaya and Engin’s [?. Kaya, O. Engin, A new approach to define sample size at attributes control chart in multistage processes: an application in engine piston manufacturing process, Journal of Materials Processing Technology 183 (2007) 38-48] model based on minimum cost and maximum acceptance probability to determine the sample size for attribute control charts (ACCs), and solved by genetic algorithms (GAs) with linear binary representation structure, is handled to solve it by a linear real-valued representation. A new chromosome structure is also suggested to increase the efficiency of GAs. The performance of GAs depends on mutation and crossover operators, and their ratios. To determine the most appropriate operators, five different mutation and crossover operators are used and they are compared with each other. An application in a motor engine factory is illustrated. u-Control charts are constructed with respect to the sample size determined by GA in the model. The piston production stages in this factory are monitorized using the obtained control charts.     

The economic design of control charts with repair cost depending on detection delay

This study extends Duncan's [1] model to two different manufacturing process models in which the processes continue and discontinue in operations during the search for the assignable cause. A more realistic assumption considered in this paper is that the cost of repair and the net hourly out-of-control income are functions of detection delay. In the continuous model, detection delay is defined as the elapsed time from the time when the shift of the process occurs until it is identified by control charts and the assignable cause is eliminated. The discontinuous model defines detection delay as the time interval from the occurrence of the process shift to the completion of testing a set of samples and interpreting the results. An efficient procedure is developed to determine the optimal designs without using any approximation approach. Thus, the proposed procedure can obtain the truly optimal designs rather than those approximate designs determined by Duncan [1] and other subsequent researchers. This paper illustrates several numerical examples and makes some relevant comparisons. The results indicate that this optimal solution procedure is more accurate than that of Panagos et al. [2]. Also, detection delay is sensitive to the economic design of control charts.     

A control point methodology for CUSUM control charts

A control point methodology (CPM) is proposed for implementation of graphical cumulative-sum (CUSUM) control charts on computers. Currently, most computer implementation of CUSUM charts is based on tabular form which loses the distinguished look of CUSUM statistics and V-mask. The more intuitive graphical CUSUM charts are not popular due to the difficulty of computer implementation. CPM removes the need to store all CUSUM points and thus reduces computing time. Examples are given to show that the proposed method can be applied to CUSUM for both means and ranges.     

一种新的分裂属性选择方法

代价敏感决策树通常讨论测试代价和误分类代价,在其分类过程中,最关键的是节点分裂属性的选择。分析了代价敏感决策树分类问题目前常见的选择分裂属性方法的优、缺点,提出了综合信息量和测试代价并且最大程度降低误分类代价的分裂属性选择方法,UCI数据集实验结果显示该方法在各个方面好于已有的方法。     

多级水泵房自动化排水控制系统设计

介绍了一种多级水泵房自动化排水控制系统的设计方案,给出了系统结构及主要功能,从水泵引水方式及多级联动功能两方面阐述了系统的关键问题并给出了相应的解决方案。实践表明,该系统排水效率高,监测数据准确,运行稳定可靠,实现了多级水泵房的无人值守。     

Design for patient safety: a systems-based risk identification framework

Current risk identification practices applied to patient safety in healthcare are insufficient. The situation can be improved, however, by studying systems approaches broadly and successfully utilised in other safety-critical industries, such as aviation and chemical industries. To illustrate this, this paper first investigates current risk identification practices in the healthcare field, and then examines the potential of systems approaches. A systems-based approach, called the Risk Identification Framework (RID Framework), is then developed to enhance improvement in risk identification. Demonstrating the strengths of using multiple inputs and methods, the RID Framework helps to facilitate the proactive identification of new risks. In this study, the potential value of the RID Framework is discussed by examining its application and evaluation, as conducted in a real-world healthcare setting. Both the application and evaluation of the RID Framework indicate positive results, as well as the need for further research.

Practitioner Summary: The findings in this study provide insights into how to make a better amalgamation of risk identification inputs to the safer design and more proactive risk management of healthcare delivery systems, which have been an increasing research interest amongst human factor professionals and ergonomists.     

基于BIM的低成本工程项目进度控制系统设计

针对工程项目中出现的施工进度规划不合理等问题,提出低成本工程项目进度控制系统进行设计。传统的工程项目进度控制方法覆盖面有限,仅可完成某个领域进度的控制,存在成本高,效率低的问题。针对该问题提出基于BIM的低成本工程项目进度控制系统设计方法。该方法首先对控制系统的整体硬件结构进行设计,通过ARM7微处理器以及液晶显示模块、IC总线、以太网模块构建系统硬件组成了整体系统结构。对于所设计的系统软件部分,是基于CSDT-S对TR(传送请求)的处理,结合对TR的处理调度,先实现用户的工程项目进度控制的实时请求,并对其进行响应高效处理,进而利用进度数据信息存储器进行并行分布控制,对获取的控制结果进行进一步整合,按照相关度排序传送到用户的控制界面。为验证所设计系统的有效性,进行一次仿真实验,实验结果表明该系统能够实现人力资源与建筑资源合理分配,并且可以高效控制低成本工程项目管理的具体进度。     

Adaptive tracking control for stochastic uncertain non-linear systems satisfying short- and long-term cost criteria

The tracking control problem for a class of stochastic and uncertain non-linear systems is addressed. The proposed controller uses suitable radial basis function neural network designs for the approximation of the unknown non-linearities while it is arbitrarily regulated in order to effectively penalize the tracking error. This regulation is implemented through a risk-sensitivity parameter. A stability analysis based on Lyapunov functions obtained by the backstepping technique, proves that all the error variables are bounded in probability; simultaneously, for any given risk-sensitivity parameter the system performance is regulated with respect to both a desired small average tracking error and low long-term average cost in accordance to a risk-sensitive cost criterion. Moreover, the larger this parameter is, the mean square tracking error becomes semiglobally uniformly ultimately bounded in a smaller area while a lower level of a long-term average cost is achieved. The effectiveness of the design approach is illustrated by simulation results wherein it becomes clear how one can achieve a tradeoff between good response and control effort.     

Robust control charts for time series data

This article presents a control chart for time series data, based on the one-step-ahead forecast errors of the Holt–Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain the reliability of the control chart after the occurrence of alarm observations. The properties of the new control chart are examined in a simulation study and on a real data example.     

Beta control charts for monitoring fraction data

p-Charts and np-Charts are commonly used in monitoring variables of the fraction type and these charts assume that the monitored variables are binomially distributed. In this paper we propose a new control chart called Beta Charts, for monitoring fraction data (p). The Beta Chart presents the control limits based on the Beta probability distribution. It was applied for monitoring the variables in three real studies, and it was compared to the control limits with three schemes. The comparative analysis showed that: (i) Beta approximation to the Binomial distribution was more appropriate with values confined in the [0, 1]-interval; and (ii) the charts proposed were more sensitive to the average run length (ARL), in both in-control and out-of-control processes monitoring. The Beta Charts outperform the control charts analyzed for monitoring fraction data.     

Q control charts for negative binomial distribution

As we known, Q charts are SPC charts for approximate normal distribution. This paper proposes new kinds of Q charts for negative binomial random variable. First, define two transformations of approximate standard normal distribution for a negative binomial parameter p which it is known or unknown. Then, Q charts are constructed by transformed data, these Q charts are useful for monitoring process in real time from the beginning of sampling, especially, for p unknown in advance. In order to compare the goodness of the Q charts with conventional Shewhart charts with 3-sigma limits, an example is given. The results have shown that these Q charts are more efficient than classical Shewhart charts. Finally, some review are given.     

基于测试代价的三支邻域属性约简算法

针对粗糙集属性约简时很少考虑属性自身的测试代价等问题,提出了一种基于测试代价的三支邻域属性约简算法。算法根据各属性在邻域分辨矩阵中出现的频次和比例来计算属性重要性,并结合属性自身的测试代价来构造性价比指标,以此指导属性的甄选。三支决策方法被用于划分属性集,为属性的约简处理提供数据支撑。在7个UCI公共数据集上进行对比实验,结果表明,该算法可得到比对比算法更小的属性约简集合,在分类精度不降低的情况下,该算法具有更少的运行时间和更小的测试代价。基于财政收入的预测应用实例进一步证明了所提算法的有效性和实用性。     

Control charts for flexible and multi-variety production systems

This study presents two new proposals of self-start statistical process control procedures for implementing quality control charts in mass customized production environments. Mass customization is characterized by high variety and/or low production volumes, or by current production strategies that increase the necessity of flexibility. The proposed approaches consider that the quality characteristic under monitoring is the same among the items, allowing the possibility of different averages and standard deviations for different products into the series. Analysis of the proposed approaches include assumption violations and the comparison of the new approaches to a Phase I–Phase II residual control chart, as benchmark. Simulation results show that one of the proposed approaches ties in performance with the benchmark, and the other can produce faster detection of deviations from the process mean, both without the need of a Phase I – retrospective analysis, thus increasing suitability for application in real environments. Also, the proposed approaches are made to handle with unitary production lots as well. Analysis performed in an extensive simulation procedure presents that normality assumption violation (with higher asymmetry) has the most degenerative effect on all tested control charts. The study also shown decreasing in performance on scenarios that violated the independence of the observations assumption.     

基于属性的内部文档访问控制

采用基于属性的访问控制模型思想,实现了分布式环境下的内部文档访问控制.采用F-Logic语言,描述了访问控制策略,具有良好的结构化知识的描述能力.采用FLORA-2作为逻辑推理引擎,具有更好的通用性.在统一的访问控制框架下,以具体应用为例,描述了基于属性的内部文档访问控制实现过程中的各个要素,包括属性描述、访问控制请求描述、策略描述.     

Comparison of control charts for low defective rate

It is well known that the conventional p control chart constructed by the normal approximation for the binomial distribution suffers a serious inaccuracy in the monitor process when the true rate of nonconforming items is small. A similar problem also arises in the binomial confidence interval estimation. Adjusted confidence intervals are established in the literature to improve the coverage probability when the binomial proportion is small. In this paper, a new p control chart based on an adjusted confidence interval is established, which can substantially improve the existing control charts when the nonconforming rate is small.     

使用控制的可变性研究

在传统的访问控制模型和策略中虽有可变的特性,但属性的可变性是一个全新的概念。作为对传统访问控制的扩展,论述了使用控制模型,分析了其核心组成及特性。运用使用控制的观点,讨论了使用控制的可变性,定义了临时属性和永久属性两个可变属性。可变性是对相关主体和对象访问结果的属性更新处理,发生在授权和认证模型中,是通过在定义模型中加入更新过程实现的,使得基于历史的访问决策更容易实施。在属性可变性的基础上,进一步讨论了可变性的几种变化形式。     

Design and optimization of EWMA control charts for in-control,indifference, and out-of-control regions

The design of quality control charts is normally carried out considering a process shift size that is considered important to be detected. The EWMA control chart is one of the best available options to use when good performance is needed to detect small process shifts. This paper presents a method for design of EWMA charts for control processes, in which the detection of small shifts is not necessary, and at the same time is effective in detecting important shifts. In such cases the EWMA control chart can also be designed successfully to deal with these requirements. A Markov chain approach is also applied to determine the ARL of the modified EWMA control chart. The implementation and interpretations are provided and numerical examples are used to illustrate the application procedure. We also investigate some basic properties of the proposed scheme. Genetic algorithms have been used to carry out this design.     

CUSUM control charts for monitoring optimal portfolio weights

A portfolio investor requires statistical tools for the timely detection of changes in the optimal portfolio composition. Several multivariate cumulative sum (CUSUM) control charts are proposed for the purpose of monitoring optimal portfolio weights. The ability of the CUSUM schemes to detect important types of changes in the optimal portfolio weights is analyzed in an extensive Monte Carlo simulation study. The empirical application of control charts shows that the proposed methodology can provide a significant reduction of the portfolio volatility.     

A novel approach for multistage inference fuzzy control

This paper presents a methodology to the design of a multistage inference fuzzy controller in which the consequence in an inference stage is passed to the next stage as fact, and so forth. A new general method which is based on a performance index of the control system is used to generate fuzzy rule bases for the multistage inference. This proposed method can reduce the design cycle time. In order to reduce the computation time, a method for precomputing the match-degrees of fuzzy values is adopted. Thus, the number of operations that must be carried out at execution time can be significantly reduced. The new method has been applied to two applications, a two-trailer-and-truck system and a three-trailer-and-truck system. The simulation studies showed that the proposed method is feasible.