Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. Joseph J. Pignatiello, Jr., Florida State University, College of Engineering, Department of Industrial Engineering. Title and description from dissertation home page (viewed June 17, 2004). Includes bibliographical references (p 53-55).

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains ix, 94 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 91-94).

Statistical quality control charts originated in the late 1920’s by Shewhart (1926, 1931 and 1939). Their applications in various disciplines have been ever-increasing. Although most control charts are distribution-based, recent literature witnessed the development of a considerable number of distribution-free or nonparametric control charts. The purpose of this thesis is to present the concepts and introduce the researcher to the essentials of univariate nonparametric control charts. Various properties of nonparametric control charts are comprehensively discussed and concepts are clearly explained. Proofs and detailed calculations have been given to help the reader to study and understand the subject more thoroughly. This text contains a wide variety of illustrative examples to give an overall picture of how nonparametric control charts are used. Both simulated and real data examples have been integrated throughout the text. Since most practical problems are too large to be solved using hand calculations, some type of statistical software package is required to solve these problems. There are several excellent statistical packages available and in this thesis we make use of Microsoft Excel, SAS, Minitab, Mathcad and Mathematica to construct (almost all) the tables in this thesis. We point out that a number of Mathematica programs are provided by Chakraborti and Van de Wiel (2003) by means of the website www.win.tue.nl/~markvdw. The aim throughout is to convey the concepts of univariate nonparametric control charts in a way that readers will find attractive and interesting. Since the majority of nonparametric procedures, to be distribution-free, require a continuous population, only variables control charts are covered. We only consider control charts for monitoring the location of a process, since very few nonparametric charts are available for monitoring the spread. In this thesis we consider the three main classes of control charts: the Shewhart, CUSUM and EWMA control charts and their refinements. The text is divided into several chapters. An introduction to nonparametric control charts is presented in Chapter 1. A discussion of some of the advantages of nonparametric control charts is included while pointing out some of the disadvantages. In Chapter 2 we describe the Shewhart-, CUSUMand EWMA-type sign control charts with (and without) warning limits. In Chapter 3 we describe the Shewhart-, CUSUM- and EWMA-type signed-rank control charts with (and without) runs-type signalling rules. The Shewhart-type sign-like control chart with (and without) signalling rules is considered in Chapter 4. In Chapter 5 we consider the Shewharttype signed-rank-like control chart. Finally, in Chapter 6 we consider the Shewhart- and CUSUM-type Mann-Whitney-Wilcoxon control charts. We considered decision problems under both Phase I and Phase II (see Section 1.5 for a distinction between the two phases). In all the sections of this thesis we considered Phase II process monitoring, except in Section 6.2 where a CUSUM-type control chart for the preliminary Phase I analysis of individual observations based on the Mann-Whitney two-sample test is proposed. In the last chapter we have some concluding remarks along with some ideas for future research. / Dissertation (MSc)--University of Pretoria, 2011. / Statistics / unrestricted

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.

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.

Made available in DSpace on 2015-04-22T22:10:48Z (GMT). No. of bitstreams: 1 tsuyoshi.pdf: 2918778 bytes, checksum: 0582f83031f201cf5c9075263e1fe8c4 (MD5) Previous issue date: 2009-12-14 / Manufacturing electronic mobile communication products requires high quality control, achieved through measurements and tunings of each unit produced. The goal of this publication is the evaluation of statistical process control (SPC) to monitor the quality of products and the process capability index Cpk. In other words, this study compares the sensitivity of control charts to detect variations in process mean and standard deviation. In this sense, Shewhart control charts and cumulative sum (CUSUM) control charts were comparatively analyzed to select the best SPC in order to guarantee more accurate measurements and devices tuned with lower deviations. Shewhart, in this case, uses the mean and the standard deviation of samples measured during a defined period of time. CUSUM control charts, based on cumulative sums, are statistical tools successfully used to evaluate processes in different industries. The Shewhart control chart was optimized to monitor the capability index Cpk. According to results obtained under the conditions of this experience, CUSUM control chart has higher sensibility when the process has small shifts. It was not observed efficacy of optimized Shewhart control chart to monitor Cpk. / A manufatura de produtos eletrônicos de comunicação móvel demanda um controle de qualidade apurado que é atingido através de medições e de sintonias de cada unidade produzida. O objetivo deste trabalho é avaliar o uso de controle estatístico de processo (CEP) para monitorar a qualidade dos produtos e o índice Cpk de capacidade do processo. Em outras palavras, este estudo compara a sensibilidade do gráfico de controle para detectar variações na média e no desvio padrão do processo. Nesse sentido, foi usada a medição de um parâmetro crítico do dispositivo produzido, a potência irradiada. Neste estudo, gráficos de controle de Shewhart e de soma cumulativa (CUSUM) foram analisados comparativamente para encontrar o melhor CEP para garantir medições mais exatas e dispositivos sintonizados com menores desvios. Shewhart, neste caso, usa a média e o desvio padrão de amostras observadas num período de tempo definido. Os gráficos de controle CUSUM, baseado em somas cumulativas, são ferramentas estatísticas usadas com sucesso para avaliar processos de diferentes indústrias. O gráfico de Shewhart foi otimizado para monitorar o índice de capacidade Cpk. De acordo com os resultados obtidos nas condições do experimento, o gráfico de controle CUSUM mostrou maior sensibilidade para pequenos desvios no processo. Não foi obsevada a eficácia do gráfico de Shewhart otimizado para monitorar o índice de capacidade Cpk.

Στην παρούσα εργασία παρουσιάζονται οι έλεγχοι για διαρθρωτικές μεταβολές στις αποδόσεις χρηματοοικονομικών χρονοσειρών που διερευνώνται στην διεθνή βιβλιογραφία. Έλεγχοι τύπου σωρευτικών αθροισμάτων (CUSUM) όπως των Kokoszka και Leipus, ο LM και ο LR έλεγχος του Andrews και των Bai και Perron αντίστοιχα και ο έλεγχος τύπου ελαχίστων τετραγώνων των Lavielle και Moullines. Τέλος εφαρμόζουμε τον έλεγχο των Kokoszka και Leipus για την εύρεση διαρθρωτικών μεταβολών στους δείκτες NASDAQ και S&P500. / --

NIALM (Non-Intrusive Load Monitoring) est une technologie innovante qui permet de suivre la consommation individuelle en énergie des différents appareils électriques dans un réseau électrique grâce à un seul point de mesure. Ainsi, l’installation et la maintenance du système est très simple. Cependant, le logiciel NIALM nécessite le développement d’algorithmes sophistiqués pour identifier la consommation de chaque appareil avec une bonne précision. Par conséquent, ces algorithmes complexes nécessitent une plate-forme d’exécution puissante et coûteuse. En réponse à ce problème, cette thèse propose un système NIALM innovant fonctionnant en temps réel et à faible coût. Ce système permet de dépasser certaines limites actuelles du NIALM grâce à une extraction d’informations supplémentaires sur les signatures électriques, une détection des transitions lentes et des appareils à multi-états grâce à deux nouvelles fonctions : un algorithme de détection d'événements CUSUM et une ventilation des sommes cumulées en se basant sur un algorithme génétique. La deuxième contribution importante est de proposer une méthodologie utilisant le modèle RPN (Reactive Process Network) pour développer le système NIALM dans un SoC (System on Chip) avec une accélération matérielle de type FPGA. Ce SoC permet ainsi l'exécution en parallèle dans le FPGA de processus de traitement de données avec des algorithmes complexes tout en satisfaisant les contraintes de temps. Les avantages de notre méthode sont : la capacité de développer une spécification exécutable, d’effectuer une exploration d'architecture, et d’obtenir rapidement un prototype du système NIALM à partir d’un même modèle applicatif. / In comparison to conventional smart meters, NIALM (Non-Intrusive Load Monitoring) is an innovative technology because it can monitor power usage on individual appliances in an electrical network using only one sensing node. Thus, setting up and maintaining the system is very simple because of the few of hardware elements. In contrast, the software of NIALM is often very complex and there is still the need in developing more complex algorithms to classify appliances more accurately. These complex algorithms of NIALM require to run on a powerful and expensive hardware platform. In order to overcome this problem, the first contribution of this thesis is to propose a low cost real-time innovative NIALM system to solve some limits of NIALM design by extracting more electrical signatures, detecting slow transition and multi-state appliances, and energy disaggregation in real-time. This is possible by using two new algorithms: CUSUM event detection algorithm and disaggregation based on Genetic Algorithm. Similar to complex DSP systems, a NIALM system contains both event control processes and data streaming processes. The second important contribution of this research is to propose a methodology based on RPN model (Reactive Process Network) to develop a complex NIALM system in SoC with FPGA acceleration. Such SoC allows running data streaming processes with complex algorithms and hard timing constraints in parallel in FPGA while other processes can run in processors. The advantages of our methodology are the ability to develop an executable specification to proceed to architecture exploration, and prototype the NIALM system quickly using the same application model.

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In this study, neural networks are developed under conditions of nonnormality as alternatives to standard control charts, and their performance is compared with those of standard ‾x and CUSUM control charts.