On the monitoring of multi-attributes high-quality production processes

Over the last decade, there have been an increasing interest in the techniques of process monitoring of high-quality processes. Based upon the cumulative counts of conforming (CCC) items, Geometric distribution is particularly useful in these cases. Nonetheless, in some processes the number of one or more types of defects on a nonconforming observation is also of great importance and must be monitored simultaneously. However, there usually exist some correlations between these two measures, which obligate the use of multi-attribute process monitoring. In the literature, by assuming independence between the two measures and for the cases in which there is only one type of defect in nonconforming items, the generalized Poisson distribution is proposed to model such a problem and the simultaneous use of two separate control charts (CCC & C chats) is recommended. In this paper, we propose a new methodology to monitor multi-attribute high-quality processes in which not only there exist more than one type of defects on the observed nonconforming item but also there is a dependence structure between the two measures. To do this, first we transform multi-attribute data in a way that their marginal probability distributions have almost zero skewnesses. Then, we estimate the transformed mean vector and covariance matrix and apply the well-known χ² control chart. In order to illustrate the proposed method and evaluate its performance, we use two numerical examples by simulation and compare the results. The results of the simulation studies are encouraging.     

Problems in the estimation and interpretation of the reliability of survey data

In this paper I discuss several of the difficulties involved in estimating the reliability of survey measurement. Reliability is defined on the basis of classical true-score theory, as the correlational consistency of multiple measures of the same construct, net of true change. This concept is presented within the framework of a theoretical discussion of the sources of error in survey data and the design requirements for separating response variation into components representing such response consistency and measurement errors. Discussion focuses on the potential sources of random and nonrandom errors, including “invalidity” of measurement, the term frequently used to refer to components of method variance. Problems with the estimation of these components are enumerated and discussed with respect to both cross-sectional and panel designs. Empirical examples are given of the estimation of the quantities of interest, which are the basis of a discussion of the interpretational difficulties encountered in reliability estimation. Data are drawn from the ISR's Quality of Life surveys, the National Election Studies and the NORC's General Social Surveys. The general conclusion is that both cross-sectional and panel estimates of measurement reliability are desirable, but for the purposes of isolating the random component of error, panel designs are probably the most advantageous.     

巧用Excel检查断面观测数据的可靠性

文章通过Excel和Excel合并工具的运用阐明了如何快速检查观测数据的可靠性。     

企业日常管理中环境监测数据的应用

环境监测数据在为环境管理提供重要科学依据的同时,它在企业生产管理中发挥着举足轻重的作用。根据污染物排放监测数据可分析企业生产运行状态是否正常,污染治理设施运行是否正常,从而便于协助其搞好生产管理,达到促进环境保护与经济建设协调发展的目的。     

Performance of cumulative sum schemes for monitoring low count-level processes

In many instances attributes data must be used to monitor a manufacturing (or other) process that, in normal conditions, should operate at very low count levels for defects. Lucas (1989) has directed attention to this problem, and has investigated a new control scheme for low count-level processes. An alternative scheme is proposed, based on a Cumulative Sum (CUSUM) of the number (termed Run-Length) of successive samples having zero count-levels between samples having at least one count. Using the criterion of Average Run Length (the average number of samples until a signal is generated) comparisons of the Lucas scheme and the Run-Length CUSUM scheme indicate that ARL values for the Run-Length CUSUM can be up to 50% lower.     

采煤工作面瓦斯浓度监测数据时间序列分析

采煤工作面瓦斯浓度超限是引起瓦斯灾害的重要原因,通过对瓦斯监测数据进行分析,可以揭示瓦斯浓度变化规律,进而避免瓦斯浓度超限事故.本文以古汉山矿为例,依据采煤工作面瓦斯浓度监测数据,通过时间序列分析和曲线拟合,确定了采煤工作面不同工序和不同时段瓦斯浓度趋势性和周期性变化特征,揭示了采煤工作面特定工序和时段的瓦斯浓度变化规律,为在煤矿生产中预测瓦斯浓度变化趋势,预防瓦斯超限提供科学依据.     

Expectation-based scan statistics for monitoring spatial time series data

We consider the simultaneous monitoring of a large number of spatially localized time series in order to detect emerging spatial patterns. For example, in disease surveillance, we detect emerging outbreaks by monitoring electronically available public health data, e.g. aggregate daily counts of Emergency Department visits. We propose a two-step approach based on the expectation-based scan statistic: we first compute the expected count for each recent day for each spatial location, then find spatial regions (groups of nearby locations) where the recent counts are significantly higher than expected. By aggregating information across multiple time series rather than monitoring each series separately, we can improve the timeliness, accuracy, and spatial resolution of detection. We evaluate several variants of the expectation-based scan statistic on the disease surveillance task (using synthetic outbreaks injected into real-world hospital Emergency Department data), and draw conclusions about which models and methods are most appropriate for which surveillance tasks.     

Comparisons of control schemes for monitoring the means of processes subject to drifts

Although statistical process control (SPC) techniques have been focused mostly on detecting step (constant) mean shift, drift which is a time-varying change frequently occurs in industrial applications. In this research, for monitoring drift change, the following five control schemes are compared: the exponentially weighted moving average (EWMA) chart and the cumulative sum (CUSUM) charts which are recommended detecting drift change in the literature; the generalized EWMA (GEWMA) chart proposed by Han and Tsung (2004) and two generalized likelihood ratio based schemes, GLR-S and GLR-L charts which are respectively under the assumption of step and linear trend shifts. Both the asymptotic estimation and the numerical simulation of the average run length (ARL) are presented. We show that when the in-control (IC) ARL is large (goes to infinity), the GLR-L chart has the best overall performance among the considered charts in detecting linear trend shift. From the viewpoint of practical IC ARL, based on the simulation results, we show that besides the GLR-L chart, the GEWMA chart offers a good balanced protection against drifts of different size. Some computational issues are also addressed.     

Extending monitoring methods to textual data: a research agenda

Textual data has become increasingly common in business analytic data sets. While concept-based text mining offers a method of extracting meaningful information from text data, methods for monitoring of customer perceptions of business processes and products that are discussed in customer-generated documents are not immediately available. We explore the results of two text-mining algorithms and review issues observed in the data that affect uploading the results onto a newly proposed methodological monitoring platform analogous to statistical process control charts. Finally, we discuss several topics for future research in text mining.     

A two-stage realized volatility approach to estimation of diffusion processes with discrete data

This paper motivates and introduces a two-stage method of estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as developed in [Jacod, J., 1994. Limit of random measures associated with the increments of a Brownian semiartingal. Working paper, Laboratoire de Probabilities, Universite Pierre et Marie Curie, Paris] and [Barndorff-Nielsen, O., Shephard, N., 2002. Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society. Series B, 64, 253–280], to provide a regression model for estimating the parameters in the diffusion function. In the second stage, the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite sample performance of the proposed method is compared with that of the approximate maximum likelihood method of [Aït-Sahalia, Y., 2002. Maximum likelihood estimation of discretely sampled diffusion: A closed-form approximation approach. Econometrica. 70, 223–262].     

A review of statistical methods in the analysis of data arising from observer reliability studies (Part I)*

Summary This paper reviews research situations in medicine, epidemiology and psychiatry, in psychological measurement and testing, and in sample surveys in which the observer(rater or interviewer) can be an important source of measurement error. Moreover, most of the statistical literature in observer variability is surveyed with attention given to a notational unification of the various models proposed. In the continuous data case, the usual analysis of variance (ANOVA) components of variance models are presented with an emphasis on the intraclass correlation coefficient as a measure of reliability. Other modified ANOVA models, response error models in sample surveys, and related multivariate extensions are also discussed. For the categorical data case, special attention is given to measures of agreement and tests of hypotheses when the data consist of dichotomous responses. In addition, similarities between the dichotomous and continous cases are illustrated in terms of intraclass correlation coefficients. Finally, measures of agreement, such as kappa and weighted-kappa, are discussed in the context of nominal and ordinal data. A proposed unifying framework for the categorical data case is given in the form of concluding remarks.     

提高电厂PlantScape系统运行的可靠性

文章针对PlantScape系统在实际生产过程中出现的一些问题进行探讨,分析原因,制定对策,取得了良好的使用效果。     

Some ideas and models in reliability theory

Summary Some questions about the meaning of reliability for the design of complex systems are discussed. Should the ideas of reliability be put in a broader framework, becoming applicable also to nontechnical systems, like a government organisation? In the mnd chapter some rather new failure models are reviewed and an interesting derivation of the Weibull distribution is discussed.     

Structural estimation of jump-diffusion processes in macroeconomics

This paper shows how to solve and estimate a continuous-time dynamic stochastic general equilibrium (DSGE) model with jumps. It also shows that a continuous-time formulation can make it simpler (relative to its discrete-time version) to compute and estimate the deep parameters using the likelihood function when non-linearities and/or non-normalities are considered. We illustrate our approach by solving and estimating the stochastic AK and the neoclassical growth models. Our Monte Carlo experiments demonstrate that non-normalities can be detected for this class of models. Moreover, we provide strong empirical evidence for jumps in aggregate US data.     

TSI系统运行的可靠性探讨

由于TSI系统在汽轮机中有着重要的保护作用,引起了人们的广泛关注,TSI系统运行的可靠性成为广大学者研究的新课题。文章分析了TSI系统可靠性运行中存在的问题,并针对这些问题,提出了相应的改进措施。     

Models of stratification processes

Quality &; Quantity - This paper presents certain mathematical models of the stratification process. These models are explicity concerned with the dynamics of stratification systems, and through...     

Stable processes of exchange

In this paper we address a long standing gap in economic theory—the gap between claims for the dynamic efficiency of trading in markets, and the findings of formal economic theory, which justify those claims only under restrictive assumptions. We use agent-based methods to study the dynamics of exchange with trading agents who are characterized by several different preference relations. We see that outcomes converge with high probability to Pareto optima in the cases studied, including the well-known example due to Scarf.     

On the reliability of the chi-square test

Summary The classical ₂ test of goodness of fit depends on the partition chosen to calculate it. In this work the covariance structure of the family of all ₂ tests obtained by translation (modulo 1) of a uniform partition of the interval [0, 1) it is determined, under the hypothesis of uniform distribution on [0, 1). This is used to define and compute an index which measure the indeterminacy of the ₂ test due to the arbitrary choice of the partition to compute it.     

Random monitoring in financing relationships

This paper examines a financier’s optimal monitoring intensity in a multi-period financing relationship. We identify conditions under which the financier should sometimes misidentify the quality of an entrepreneur. Such an imperfect evaluation technology affects action choices by bad entrepreneurs. We first characterize the optimal monitoring intensity and show that it is one in which the investor monitors entrepreneurs randomly. Random monitoring in the first stage of a relationship induces bad entrepreneurs to reveal their intrinsic types. Second, because random monitoring reduces the share of bad entrepreneurs in the subsequent periods, we show that the financier can therefore realize substantial gains.