Recently, in the health surveillance area, control charts have been proposed to decide if the morbidity or mortality of a specific disease reached an epidemic level. This thesis is composed by 3 papers. In the first two papers, CUSUM and EWMA control charts were proposed to monitor count time series with seasonal and trend effects using the Generalized Autoregressive and Moving Average models (GARMA), instead of the independent Generalized Linear Model (GLM) as it is usually used in practice. Different statistics based on transformations, for variables that follow a Negative Binomial distribution, were used in these control charts. In the second paper, two new statistics were proposed based on the ratio of log-likelihood function. Different scenarios describing disease profiles were considered to evaluate the effect of omission of serial correlation in EWMA and CUSUM control charts. The performance of CUSUM and EWMA charts when the serial correlation is neglected in the regression model was measure in terms of average run length (ARL). In summary, when the autocorrelation is neglected, fitting a pure GLM instead of a GARMA model will lead to an increase of false alarms. However, no statistics among the tested ones seem to be robust, in a sense to produce the smallest increase of false alarms in all scenarios. In general, all monitored statistics presented a smaller ARL_0 for higher values of autocorrelation. \\\\ In the last paper, the GARMA models (p, q) with p and q simultaneously different from zero were studied since that two features were observed in practice. One is the multicollinearity, which may lead to a non-convergence of the maximum likelihood, using iteratively reweighted least squares. The second is the inclusion of the same lagged observations into the autoregressive and moving average components confounding the interpretation of the parameters. In a general sense, simulation studies show that the modified model provide estimators closer to the parameters and offer confidence intervals with higher coverage percentage than obtained with the GARMA model, but some restrictions in the parametric space are imposed to guarantee the stationarity of the process. Also, a real data analysis illustrate the GARMA-M fit for daily hospilatization rates of elderly people due to respiratory diseases from October 2012 to April 2015 in São Paulo city, Brazil. / Recentemente, no campo da saúde, gráficos de controle têm sido propostos para monitorar a morbidade ou a mortalidade decorrentes de doenças. Este trabalho está composto por três artigos. Nos dois primeiros artigos, gráficos de controle CUSUM e EWMA foram propostos para monitorar séries temporais de contagens com efeitos sazonais e de tendência usando os modelos Generalized autoregressive and moving average models (GARMA), em vez dos modelos lineares generalizados (GLM), como usualmente são utilizados na prática. Diferentes estatísticas baseadas em transformações, para variávies que seguem uma distribuição Binomial Negativa, foram usadas nestes gráficos de controle. No segundo artigo foram propostas duas novas estatísticas baseadas na razão da função de log-verossimilhança. Diferentes cenários que descrevem perfis de doenças foram considerados para avaliar o efeito da omissão da correlação serial nesses gráficos de controle. Este impacto foi medido em termos do Average Run Lenght (ARL). Notou-se que a negligência da correlação serial induz um aumento de falsos alarmes. Em geral, todas as estatísticas monitoradas apresentaram menores valores de ARL_0 para maiores valores de autocorrelação. No entanto, nenhuma estatística entre as consideradas mostrou ser mais robusta, no sentido de produzir o menor aumento de falsos alarmes nos cenários considerados. No último artigo, foram estudados os modelos GARMA (p, q) com p e q simultaneamente diferentes de zero, uma vez que duas características foram observadas na prática. A primeira é a presença de multicolinearidade, que induz à não-convergência do método de máxima verossimilhança usando mínimos quadrados ponderados reiterados. A segunda é a inclusão dos mesmos termos defasados nos componentes autorregressivos e de médias móveis. Um modelo modificado, GARMA-M, foi apresentado para lidar com a multicolinearidade e melhorar a interpretação dos parâmetros. Em sentido geral, estudos de simulação mostraram que o modelo modificado fornece estimativas mais próximas dos parâmetros e intervalos de confiança com uma cobertura percentual maior do que a obtida nos modelos GARMA. No entanto, algumas restrições no espaço paramétrico são impostas para garantir a estacionariedade do processo. Por último, uma análise de dados reais ilustra o ajuste do modelo GARMA-M para o número de internações diárias de idosos devido a doenças respiratórias de outubro de 2012 a abril de 2015 na cidade de São Paulo, Brasil.

The determination of economic control charts and the determination of specification limits with minimum cost are two different research topics. In this study, we first combine the design of economic control charts and the determination of specification limits to maximize the expected profit per unit time for the smaller the better quality variable following the gamma distribution. Because of the asymmetric distribution, we design the EWMA control chart with asymmetric control limits. We simultaneously determine the economic EWMA control chart and upper specification limit with maximum expected profit per unit time. Then, extend the approach to determine the economic variable sampling interval EWMA control chart and upper specification limit with maximum expected profit per unit time. In all our numerical examples of the two profit models, the optimum expected profit per unit time under inspection is higher than that of no inspection. The detection ability of the EWMA chart with an appropriate weight is always better than the X-bar probability chart. The detection ability of the VSI EWMA chart is also superior to that of the fixed sampling interval EWMA chart. Sensitivity analyses are provided to determine the significant parameters for the optimal design parameters and the optimal expected profit per unit time.

When flying a fighter aircraft such as the JAS 39 Gripen, the pilot is exposed to high g-loads. In order to prevent the draining of blood from the brain during this stress an anti-g protection system is used. The system consists of a pair of trousers, called the anti-g trousers, with inflatable bladders. The bladders are filled with air, pressing tightly on to the legs in order to prevent the blood from leaving the upper part of the body. The purpose of this thesis is to detect if the pressure of the anti-g trousers is deviating from the desired value. This is done by developing a detection algorithm which gives two kinds of alarm. One is given during minor deviations using a CUSUM test, and one is given at grave deviations, based on different conditions including residual, derivative and time. The thresholds, in which between the pressure should lie in a faultless system, are calculated from the g-load value. The thresholds are based upon given static guidelines for the pressure tolerance area and are modified in order to adapt to the estimated dynamics of the system. The values of the input signals, pressure and g-load, were taken from real flight sessions. The validation has been performed using both faultless and faulty flight sequences, with low false alarm rate and no missed detections. All together the detection system is considered to work well.

Control performance assessment (CPA) is an important tool to realize high performance control systems in manufacturing plants. CPA of both continuous and batch processes have attracted much attention from researchers, but only a few results about semiconductor processes have been proposed previously. This work provides methods for performance assessment and diagnosis of the run-to-run control system used in high-mix semiconductor manufacturing processes. First, the output error source of the processes with a run-to-run EWMA controller is analyzed and a CPA method (namely CPA I) is proposed based on closed-loop parameter estimation. In CPA I, ARMAX regression is directly applied to the process output error, and the performance index is defined based on the variance of the regression results. The influence of plant model mismatch in the process gain and disturbance model parameter to the control performance in the cases with or without set point change is studied. CPA I method is applied to diagnose the plant model mismatch in the case with set point change. Second, an advanced CPA method (namely CPA II) is developed to assess the control performance degradation in the case without set point change. An estimated disturbance is generated by a filter, and ARMAX regression method is applied to the estimated disturbance to assess the control performance. The influence of plant model mismatch, improper controller tuning, metrology delay, and high-mix process parameters is studied and the results showed that CPA II method can quickly identify, diagnose and correct the control performance degradation. The CPA II method is applied to industrial data from a high-mix photolithography process in Texas Instruments and the influence of metrology delay and plant model mismatch is discussed. A control performance optimization (CPO) method based on analysis of estimated disturbance is proposed, and optimal EWMA controller tuning factor is suggested. Finally, the CPA II method is applied to non-threaded run-to-run controller which is developed based on state estimation and Kalman filter. Overall process control performance and state estimation behavior are assessed. The influence of plant model mismatch and improper selection of different controller variables is studied. / text

In the recent years threaded run-to-run (RtR) control algorithms have experienced drawbacks under certain circumstances, one such trait is when applied to high-mix of products such as in Application Specific Integrated Circuits (ASIC) foundries. The variations in the process are a function of the product being manufactured as well as the tool being used. The presence of semiconductor layers increases the number of times the lithography process must be repeated. Successive layers having different patterns must be exposed using different reticles/masks in order to maximize tool utilizations. The objectives of this research are to develop a set of methodologies for evaluation and extension of threaded control applied to overlay. This project defines methods to quantify the efficacy of threaded controls, finds the drawbacks of threaded control under production of high mix of semiconductors and suggests extensions and alternatives to improve threaded control. To evaluate the performance of threaded control, extensive simulations were performed in MATLAB. The effects of noise, disturbances, sampling and delays on the control and estimation performance of threaded controller were studied through these simulations. Based on the results obtained, several ideas to extend threaded control by reducing overall number of threads, by improving thread definitions and combination have been introduced. A unique idea of sampling the measurements dynamically based on the estimation accuracy is also presented. Future work includes implementing the extensions to threaded control suggested in this work in real production data and comparing the results without the use of those methods. Future work also includes building new alternatives to threaded control. / text

abstract: Mobile ad hoc networks (MANETs) have attracted attention for mission critical applications. This dissertation investigates techniques of statistical monitoring and control for overhead reduction in a proactive MANET routing protocol. Proactive protocols transmit overhead periodically. Instead, we propose that the local conditions of a node should determine this transmission decision. While the goal is to minimize overhead, a balance in the amount of overhead transmitted and the performance achieved is required. Statistical monitoring consists of techniques to determine if a characteristic has shifted away from an in-control state. A basic tool for monitoring is a control chart, a time-oriented representation of the characteristic. When a sample deviates outside control limits, a significant change has occurred and corrective actions are required to return to the in-control state. We investigate the use of statistical monitoring of local conditions in the Optimized Link State Routing (OLSR) protocol. Three versions are developed. In A-OLSR, each node uses a Shewhart chart to monitor betweenness of its two-hop neighbourhood. Betweenness is a social network metric that measures a node's influence; betweenness is larger when a node has more influence. Changes in topology are associated with changes in betweenness. We incorporate additional local node conditions including speed, density, packet arrival rate, and number of flows it forwards in A+-OLSR. Response Surface Methodology (RSM) is used to optimize timer values. As well, the Shewhart chart is replaced by an Exponentially Weighted Moving Average (EWMA) chart, which is more sensitive to small changes in the characteristic. It is known that control charts do not work as well in the presence of correlation. Hence, in A*-OLSR the autocorrelation in the time series is removed and an Auto-Regressive Integrated Moving Average (ARIMA) model found; this removes the dependence on node speed. A*-OLSR also extends monitoring to two characteristics concurrently using multivariate cumulative sum (MCUSUM) charts. The protocols are evaluated in simulation, and compared to OLSR and its variants. The techniques for statistical monitoring and control are general and have great potential to be applied to the adaptive control of many network protocols. / Dissertation/Thesis / Ph.D. Computer Science 2012

En algunos casos, cuando el número de defectos de un proceso de producción tiene que ser controlada, la distribución de Poisson se emplea para modelar la frecuencia de estos defectos y para desarrollar un gráfico de control. En este trabajo se analiza el control de características de calidad p> 1 de Poisson . Cuando este control se necesita, hay dos enfoques principales: 1 - Un gráfico para cada variable de Poisson, el esquema múltiple.. 2 -. Sólo una gráfico para todas las variables, el sistema multivariable. En este trabajo se desarrolla un nuevo gráfico de control multivariable basado en la combinación lineal de las variables de Poisson, donde esta combinación lineal es optimizada con el fin de mantener un ARL bajo control deseado y de minimizar el ARL fuera de control. Esta optimización se lleva a cabo utilizando un software bajo Windows ©, que también hace una comparación de rendimiento entre este gráfico y otros sistemas para monitorear una serie de variables Poisson. En los otros sistemas se incluye la suma de las variables (gráfico MP) y un conjunto optimizado de gráficos univariados Poisson (esquema múltiple). / García Bustos, SL. (2014). Control Multivariante Estadístico de Variables Discretas tipo Poisson [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/40592 / TESIS

[ES] En el Control Estadístico de Procesos, los gráficos de control por variables suelen ser la herramienta empleada para vigilar el comportamiento de una característica cuantitativa de calidad. Para implementar estos gráficos se requiere de la medición periódica de una muestra de unidades del proceso. En algunos procesos, obtener una medición exacta de la variable de calidad es una tarea compleja, que demanda gran cantidad de recursos (costos, tiempo, mano de obra), o que deteriora/destruye la pieza inspeccionada. En estos casos, una alternativa más ágil y económica consiste en realizar el control basado en la verificación de piezas con una galga. Dado que la verificación con una galga suele ser tan sencilla como la verificación de un atributo, el control basado en galgas es mucho más ágil y económico que el control basado en mediciones exactas. En la literatura del Control Estadístico de Procesos se encuentran múltiples propuestas de esquemas de control basado en inspección por galgas. En esta Tesis doctoral realizamos una detallada revisión de estas propuestas y proponemos un nuevo esquema de control basado en galgas, cuyo desempeño estadístico es siempre igual o mejor que el de cualquiera de las propuestas previas. Este esquema es diseñado para el control de la media/varianza de una variable de calidad con distribución normal y posteriormente es extendido para el control de estos parámetros en distribuciones asimétricas (log-normal, skew-normal y Weibull). Adicionalmente, sobre el nuevo esquema de control basado en galgas, se realiza una adaptación de las estrategias de tamaño de muestra adaptativo, Doble muestreo y Tamaño de Muestra Variable, e incorporamos memoria al estadístico de control a través de un esquema de pesos exponencialmente ponderados EWMA. Como resultado se obtienen nuevos esquemas de control, cuya operación e implementación es tan sencilla como la de los gráficos de control por atributos, pero con mejor desempeño estadístico que los gráficos de control por variables. / [CAT] En el Control Estadístic de Processos, els gràfics de control per variables solen ser la ferramenta empleada per a vigilar el comportament d'una característica quantitativa de qualitat. Per a implementar estos gràfics es requerix del mesurament periòdic d'una mostra d'unitats del procés. En alguns processos, obtindre un mesurament exacte de la variable de qualitat és una tasca complexa, que demanda gran quantitat de recursos (costos, temps, mà d'obra) , o que deteriora/ destruïx la peça inspeccionada. En estos casos, una alternativa més àgil i econòmica consistix a realitzar el control basat en la verificació de peces amb una llebrera. Atés que la verificació amb una llebrera sol ser tan senzilla com la verificació d'un atribut, el control basat en llebreres és molt més àgil i econòmic que el control basat en mesuraments exactes. En la literatura del Control Estadístic de Processos es troben múltiples propostes d'esquemes de control basat en inspecció per llebreres. En esta Tesi doctoral realitzem una detallada revisió d'estes propostes i proposem un nou esquema de control basat en llebreres, l'exercici estadístic del qual és sempre igual o millor que el de qualsevol de les propostes prèvies. Este esquema és dissenyat per al control de la media/varianza d'una variable de qualitat amb distribució normal i posteriorment és estés per al control d'estos paràmetres en distribucions asimètriques (log-normal, skew-normal i Weibull). Addicionalment, sobre el nou esquema de control basat en llebreres, es realitza una adaptació de les estratègies de grandària de mostra adaptatiu, Doble mostratge i Grandària de Mostra Variable, i incorporem memòria a l'estadístic de control a través d'un esquema de pesos exponencialment ponderats EWMA. Com resultat s'obtenen nous esquemes de control, l'operació i implementació és tan senzilla com la dels gràfics de control per atributs, però amb millor exercici estadístic que els gràfics de control per variables. / [EN] In Statistical Process Control, control charts by variables are usually the tool used to monitor a quantitative quality characteristic. To implement these charts, periodic measurement of a sample of process units is required. In some processes, obtaining an accurate measurement of the quality variable is a complex task, which demands a large amount of resources (costs, time, labor), or that deteriorates / destroys the inspected unit. In these cases, a more agile and economical alternative is to perform the control based on the verificatión of units with a gauge. Since the verificatión with a gauge is usually as simple as checking an attribute, the control based on gauges is much more agile and economical than the control based on exact measurements. Several proposals of control schemes based on inspectión by gauges are found in the Statistical Process Control literature. In this PhD thesis we review these proposals and propose a new control scheme based on gauges, whose statistical performance is always the same or better than that of any of the previous proposals. This scheme is designed for the control of the means / variance of a quality variable with normal distributión and is subsequently extended for the control of these parameters in asymmetric distributións (log-normal, skew-normal and Weibull). In additión, on the new gauge-based control scheme, an adaptatión of the adaptive sample size: double sampling and variable sample size strategies, is carried out, and incorporates memory to the control statistic through an exponentially weighted EWMA weights scheme. As a result, new control schemes were obtained, whose operatión and implementatión is as simple as that of the control charts by attributes, but with a best statistical performance than the control charts by variables. / Inicialmente quiero agradecer a la Universidad del Valle, Cali – Colombia, por el soporte económico que me brindaron para garantizar mi estancia en la ciudad de Valencia y para el desarrollo de esta tesis doctoral. / Mosquera Restrepo, J. (2019). Control estadístico de variables cuantitativas mediante inspección por atributos apoyada en el diseño de galgas con dimensiones óptimas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/133059 / TESIS

In many applications, the quality of process outputs is described by more than one characteristic variable. These quality variables usually follow a multivariate normal (MN) distribution. This dissertation discusses the monitoring of the mean vector and the covariance matrix of MN processes. The first part of this dissertation develops a statistical process control (SPC) chart based on a generalized likelihood ratio (GLR) statistic to monitor the mean vector. The performance of the GLR chart is compared to the performance of the Hotelling Χ² chart, the multivariate exponentially weighted moving average (MEWMA) chart, and a multi-MEWMA combination. Results show that the Hotelling Χ² chart and the MEWMA chart are only effective for a small range of shift sizes in the mean vector, while the GLR chart and some carefully designed multi-MEWMA combinations can give similarly better overall performance in detecting a wide range of shift magnitudes. Unlike most of these other options, the GLR chart does not require specification of tuning parameter values by the user. The GLR chart also has the advantage in process diagnostics: at the time of a signal, estimates of change-point and out-of-control mean vector are immediately available to the user. All these advantages of the GLR chart make it a favorable option for practitioners. For the design of the GLR chart, a series of easy to use equations are provided to users for calculating the control limit to achieve the desired in-control performance. The use of this GLR chart with a variable sampling interval (VSI) scheme has also been evaluated and discussed. The rest of the dissertation considers the problem of monitoring the covariance matrix. Three GLR charts with different covariance matrix estimators have been discussed. Results show that the GLR chart with a multivariate exponentially weighted moving covariance (MEWMC) matrix estimator is slightly better than the existing method for detecting any general changes in the covariance matrix, and the GLR chart with a constrained maximum likelihood estimator (CMLE) gives much better overall performance for detecting a wide range of shift sizes than the best available options for detecting only variance increases. / Ph. D.

With the recent increase in the threat of biological terrorism as well as the continual risk of other diseases, the research in public health surveillance and disease monitoring has grown tremendously. There is an abundance of data available in all sorts of forms. Hospitals, federal and local governments, and industries are all collecting data and developing new methods to be used in the detection of anomalies. Many of these methods are developed, applied to a real data set, and incorporated into software. This research, however, takes a different view of the evaluation of these methods. We feel that there needs to be solid statistical evaluation of proposed methods no matter the intended area of application. Using proof-by-example does not seem reasonable as the sole evaluation criteria especially concerning methods that have the potential to have a great impact in our lives. For this reason, this research focuses on determining the properties of some of the most common anomaly detection methods. A distinction is made between metrics used for retrospective historical monitoring and those used for prospective on-going monitoring with the focus on the latter situation. Metrics such as the recurrence interval and time-to-signal measures are therefore the most applicable. These metrics, in conjunction with control charts such as exponentially weighted moving average (EWMA) charts and cumulative sum (CUSUM) charts, are examined. Two new time-to-signal measures, the average time-between-signal events and the average signal event length, are introduced to better compare the recurrence interval with the time-to-signal properties of surveillance schemes. The relationship commonly thought to exist between the recurrence interval and the average time to signal is shown to not exist once autocorrelation is present in the statistics used for monitoring. This means that closer consideration needs to be paid to the selection of which of these metrics to report. The properties of a commonly applied scan method are also studied carefully in the strictly temporal setting. The counts of incidences are assumed to occur independently over time and follow a Poisson distribution. Simulations are used to evaluate the method under changes in various parameters. In addition, there are two methods proposed in the literature for the calculation of the p-value, an adjustment based on the tests for previous time periods and the use of the recurrence interval with no adjustment for previous tests. The difference in these two methods is also considered. The quickness of the scan method in detecting an increase in the incidence rate as well as the number of false alarm events that occur and how long the method signals after the increase threat has passed are all of interest. These estimates from the scan method are compared to other attribute monitoring methods, mainly the Poisson CUSUM chart. It is shown that the Poisson CUSUM chart is typically faster in the detection of the increased incidence rate. / Ph. D.