Gráfico de controle de VMAX para o monitoramento da matriz de covariâncias

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoring the mean vector and the covariance ­matrix of multivariate processes with sample means and sample ranges

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sistema computacional para índices de cárie dentária: banco de dados e análise estatística

Apresenta-se um sistema computacional, denominado ICADPLUS, desenvolvido para elaboração de banco de dados, tabulação de dados, cálculo do índice CPO e análise estatística para estimação de intervalos de confiança e comparação de resultados de duas populações.Tem como objetivo apresentar método simplificado para atender necessidades de serviços de saúde na área de odontologia processando fichas utilizadas por cirurgiões dentistas em levantamentos epidemiológicos de cárie dentária. A característica principal do sistema é a dispensa de profissional especializado na área de odontologia e computação, exigindo o conhecimento mínimo de digitação por parte do usuário, pois apresenta menus simples e claros como também relatórios padronizados, sem possibilidade de erro. Possui opções para fichas de CPO segundo Klein e Palmer, CPO proposto pela OMS, CPOS segundo Klein, Palmer e Knutson, e ceo. A validação do sistema foi feita por comparação com outros métodos, permitindo recomendar sua adoção.

Gráficos de controle X para processos robustos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O uso da estatística de qui-quadrado no controle de processos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Gráfico de controle MCMAX para o monitoramento simultâneo do vetor de médias e da matriz de covariâncias

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

O efeito da autocorrelação no planejamento das cartas de controle de x̄ e EWMA

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Economic design of (X)over-bar and R charts under Weibull shock models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Joint (X)over-bar and R charts with variable sample sizes and sampling intervals

Recent studies have shown that the (X) over bar chart with variable sampling intervals (VSI) and/or with variable sample sizes (VSS) detects process shifts faster than the traditional (X) over bar chart. This article extends these studies for processes that are monitored by both the (X) over bar and R charts. A Markov chain model is used to determine the properties of the joint (X) over bar and R charts with variable sample sizes and sampling intervals (VSSI). The VSSI scheme improves the joint (X) over bar and R control chart performance in terms of the speed with which shifts in the process mean and/or variance are detected.

Systematic consideration of petiole anatomy of species of Echinodorus Richard (Alismataceae) from north-eastern Brazil

Petiole anatomy of the north-eastern Brazilian species Echinodorus glandulosus, E. palaefolius, E. pubescens, E subalatus, E lanceolatus and E paniculatus were examined. All species had petioles with an epidermis composed of tabular cells with thin walls. The chlorenchyma just below the epidermis alternates with collateral vascular bundles. The interior of the petiole is filled by aerenchyma with ample open spaces or lacunas. The lacunas are bridged at intervals by plates, or by diaphragm-like linkages. There are lactiferous ducts and groups of fibres throughout the entire length of the petiole, but more frequently in the chlorenchyma. Important taxonomic characteristics for the genus Echinodorus include the shape and outline of the petiole in transversal section, the presence of winged extensions, and the number of vascular bundle arcs. Exceptions occur in E. lanceolatus and E. paniculatus, whose petioles have similar anatomic patterns. A comparative chart of the petiole anatomic characteristics analyzed is presented. (c) 2007 Elsevier GmbH. All rights reserved.

Periodic orbits for a class of reversible quadratic vector field on R-3

For a class of reversible quadratic vector fields on R-3 we study the periodic orbits that bifurcate from a heteroclinic loop having two singular points at infinity connected by an invariant straight line in the finite part and another straight line at infinity in the local chart U-2. More specifically, we prove that for all n is an element of N, there exists epsilon(n) > 0 such that the reversible quadratic polynomial differential systemx = a(0) + a(1y) + a(3y)(2) + a(4Y)(2) + epsilon(a(2x)(2) + a(3xz)),y = b(1z) + b(3yz) + epsilon b(2xy),z = c(1y) +c(4az)(2) + epsilon c(2xz)in R-3, with a(0) < 0, b(1)c(1) < 0, a(2) < 0, b(2) < a(2), a(4) > 0, c(2) < a(2) and b(3) is not an element of (c(4), 4c(4)), for epsilon is an element of (0, epsilon(n)) has at least n periodic orbits near the heteroclinic loop. (c) 2007 Elsevier B.V. All rights reserved.

(X)over-bar charts with variable parameters

Varying the parameters of the (X) over bar chart has been explored extensively in recent years. In this paper, we extend the study of the (X) over bar chart with variable parameters to include variable action limits. The action limits establish whether the control should be relaxed or not. When the (X) over bar falls near the target, the control is relaxed so that there will be more time before the next sample and/or the next sample will be smaller than usual. When the (X) over bar falls far from the target but not in the action region, the control is tightened so that there is less time before the next sample and/or the next sample will be larger than usual. The goal is to draw the action limits wider than usual when the control is relaxed and narrower than usual when the control is tightened. This new feature then makes the (X) over bar chart more powerful than the CUSUM scheme in detecting shifts in the process mean.

X charts with supplementary samples to control the mean and variance

A standard X chart for controlling a process takes regular individual observations, for instance every half hour. This article proposes a modification of the X chart that allows one to take supplementary samples. The supplementary sample is taken (and the (X) over bar and R values computed) when the current value of X falls outside the control limits. With the supplementary sample, the signal of out-of-control is given by an (X) over bar value outside the (X) over bar chart's control limits or an R value outside the R chart's control limit. The proposed chart is designed to hold the supplementary sample frequency, during the in-control period, as low as 5% or less. In this context, the practitioner might prefer to verify an out-of-control condition by simply comparing the (X) over bar and R values with the control limits. In other words, without plotting the (X) over bar and R points. The X chart with supplementary samples has two major advantages when compared with the standard (X) over bar and A charts: (a) the user will be plotting X values instead of (X) over bar and R values; (b) the shifts in the process mean and/or changes in the process variance are detected faster.

Economic design of two-stage (X)over-bar charts: the Markov chain approach

When the (X) over bar chart is in use, samples are regularly taken from the process, and their means are plotted on the chart. In some cases, it is too expensive to obtain the X values, but not the values of a correlated variable Y. This paper presents a model for the economic design of a two-stage control chart, that is. a control chart based on both performance (X) and surrogate (Y) variables. The process is monitored by the surrogate variable until it signals an out-of-control behavior, and then a switch is made to the (X) over bar chart. The (X) over bar chart is built with central, warning. and action regions. If an X sample mean falls in the central region, the process surveillance returns to the (Y) over bar chart. Otherwise. The process remains under the (X) over bar chart's surveillance until an (X) over bar sample mean falls outside the control limits. The search for an assignable cause is undertaken when the performance variable signals an out-of-control behavior. In this way, the two variables, are used in an alternating fashion. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A study is performed to examine the economic advantages of using performance and surrogate variables. (C) 2003 Elsevier B.V. All rights reserved.

(X)OVER-BAR CHARTS WITH VARIABLE SAMPLE-SIZE

The usual practice in using a control chart to monitor a process is to take samples of size n from the process every h hours This article considers the properties of the XBAR chart when the size of each sample depends on what is observed in the preceding sample. The idea is that the sample should be large if the sample point of the preceding sample is close to but not actually outside the control limits and small if the sample point is close to the target. The properties of the variable sample size (VSS) XBAR chart are obtained using Markov chains. The VSS XBAR chart is substantially quicker than the traditional XBAR chart in detecting moderate shifts in the process.