Orientador: Ronei Jesus Poppi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Quimica / Made available in DSpace on 2018-08-13T19:01:55Z (GMT). No. of bitstreams: 1 Oliveira_IngridKomorizonode_M.pdf: 6898312 bytes, checksum: 2d635a3b5378ed641231dd6d196d33f9 (MD5) Previous issue date: 2008 / Resumo: Cartas de controle multivariadas em conjunto com espectroscopia no infravermelho próximo foram desenvolvidas para avaliar a qualidade de misturas diesel/biodiesel (98% de diesel e 2% de biodiesel). Três cartas foram desenvolvidas baseadas no sinal analítico líquido (NAS): a cartas NAS que corresponde ao analito de interesse (biodiesel nesse caso), a carta de interferente que corresponde a contribuição de outros compostos na amostra (diesel nesse caso) e a carta de resíduos que corresponde a variação não-sistemática. Para cada carta, limites estatísticos foram desenvolvidos utilizando amostras dentro das especificações de qualidade. Foi possível identificar amostras de misturas diesel/biodiesel que estavam fora das especificações relativas à quantidade de biodiesel, biodiesel contaminado com óleo vegetal e diesel contaminado com gasolina. No presente trabalho também foi desenvolvido um modelo de calibração multivariada para a determinação do valor de acidez de biodiesel degradado a partir de espectros na região do infravermelho próximo. O valor de acidez, um dos parâmetros de qualidade do biodiesel, está relacionado com o grau de degradação do biodiesel. O modelo desenvolvido foi baseado no método dos mínimos quadrados parciais (PLS) e validado baseando-se nos cálculos de figuras de mérito. Resultados bastante satisfatórios foram obtidos com erros abaixo de 3,4% e limites de detecção e quantificação de 0,018 e 0,059 mg KOH/g, respectivamente / Abstract: Multivariate control charts in jointly with near infrared spectroscopy were developed to verify the quality of biodiesel blends (2% of biodiesel and 98% of diesel). The control charts were built using the net analyte signal, generating three charts: the NAS chart that corresponds to the analyte of interest (biodiesel in this case), the interference chart that corresponds to the contribution of other compounds in the sample (diesel in this case) and the residual chart that corresponds to nonsystematic variations. For each chart, statistical limits were developed using samples inside the quality specifications. It was possible to identify biodiesel blend samples that were out of specifications relative to biodiesel content, biodiesel contaminated with vegetable oil and diesel contaminated with naphtha. In the present work it was also developed a model of multivariate calibration for the acid value determination of degraded biodiesel using the spectra in the near infrared region. The acid value, one biodiesel quality parameter, is related with the degree of biodiesel degradation. The developed model was based on the partial least squares method (PLS) and it was validated by figures of merit calculation. Feasible results were obtained with errors below to 3.4% and detection and quantification limits of 0.018 and 0.059 mg KOH/g, respectively / Mestrado / Quimica Analitica / Mestre em Química

Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2018-09-10T16:56:04Z No. of bitstreams: 2 Thiago_Nunes2018.pdf: 2241164 bytes, checksum: f455055e715541d1d8b45a0358484420 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-09-10T16:56:04Z (GMT). No. of bitstreams: 2 Thiago_Nunes2018.pdf: 2241164 bytes, checksum: f455055e715541d1d8b45a0358484420 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The drip irrigation system stands out among other irrigation methods because of its high efficiency and uniformity. One of the advantages of the drip system is that pressurizing the system can be performed by gravity, avoiding costs with energy and equipment. In urban gardens, one should expect small irrigation systems and little technology involved; still, however simple it may be, the system must have a good uniformity of application. Thus, the objective of this work was to verify the uniformity of the system under different hydraulic loads using quality control tools. The experiment was carried out in an urban garden of the municipality of Cascavel, PR. The dripping tube used was of the brand Siplast, model P1. The uniformity of the system was evaluated by the method of Keller & Karmeli (1975), using irrigation and fertigation under hydraulic loads of 1.20, 1.40, 1.60, and 1.80 mca. The CUD, CUC, CUE, and CV were calculated and classified to verify uniformity. The quality control tools used were the Shewhart Individual, MMEP, and CUSUM control charts, as well as the process capability index. Regression analyzes were also performed, to know the effect of the change of hydraulic load on the flow and the uniformity of the system. In all regression analyzes, the fittest model was the exponential, and the higher the hydraulic load, the higher the system flow and uniformity. In all the cases studied, the different coefficients of uniformity were classified as excellent, and the coefficient of variation as low. The excellent uniformity of application was further confirmed by the control charts and process capability indices, which in all cases classified the uniformity of the system as adequate. The individual Shewhart control chart was less sensitive to possible changes, while the MMEP and CUSUM charts were more accurate, the latter being more sensitive to variation. / O sistema de irrigação por gotejamento destaca-se entre os demais métodos de irrigação por sua alta eficiência e uniformidade. Uma das vantagens do sistema de gotejamento é que a pressurização do sistema pode ser feita por gravidade, economizando energia e equipamentos. Referindo-se a hortas urbanas, deve-se esperar por sistemas de irrigação de pequeno porte e pouca tecnologia envolvida; porém, por mais simples que seja, o sistema deve apresentar uma boa uniformidade de aplicação. Assim, o objetivo deste trabalho foi verificar a uniformidade do sistema sob diferentes cargas hidráulicas utilizando ferramentas de controle de qualidade. O experimento foi realizado em horta urbana do município de Cascavel, PR. O tubo gotejador utilizado foi da marca Siplast, modelo P1. A uniformidade do sistema foi avaliada pelo método de Keller e Karmeli (1975), utilizando-se irrigação e fertirrigação sob as cargas hidráulicas de 1,20, 1,40, 1,60 e 1,80 mca. Foram calculados e classificados o CUD, CUC, CUE e CV para a verificação da uniformidade. As ferramentas de controle de qualidade utilizadas foram os gráficos de controle de Shewhart Individual, MMEP e CUSUM, além do índice de capacidade de processo. Ainda, foram realizadas análises de regressão, para saber o efeito da mudança de carga hidráulica sobre a vazão e a uniformidade do sistema. Em todas as análises de regressão, o modelo de melhor ajuste foi o exponencial, sendo que quanto maior a carga hidráulica, maior a vazão e a uniformidade do sistema. Em todos os casos estudados, os diferentes coeficientes de uniformidade foram classificados como excelentes e o coeficiente de variação como baixo. A excelente uniformidade de aplicação ainda foi confirmada pelos gráficos de controle e pelos índices de capacidade de processo, que em todos os casos classificou a uniformidade do sistema como adequada. O gráfico de controle de Shewhart individual mostrou-se menos sensível a possíveis alterações, enquanto os gráficos de MMEP e CUSUM se mostraram mais rigorosos, sendo este último o que apresentou mais sensibilidade a variações.

Please read the abstract in the section front of this document / Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2009. / Statistics / unrestricted

The substantial growth in the use of automated in-process sensing technologies creates great opportunities for manufacturers to detect abnormal manufacturing processes and identify the root causes quickly. It is critical to locate and distinguish two types of faults - process faults and sensor faults. The procedures to monitor and diagnose process and sensor mean shift faults are presented with the assumption that the manufacturing processes can be modeled by a linear fault-quality model. A W control chart is developed to monitor the manufacturing process and quickly detect the occurrence of the sensor faults. Since the W chart is insensitive to process faults, when it is combined with U chart, both process faults and sensor faults can be detected and distinguished. A unit-free index referred to as the sensitivity ratio (SR) is defined to measure the sensitivity of the W chart. It shows that the sensitivity of the W chart is affected by the potential influence of the sensor measurement. A Bayesian variable selection based fault diagnosis approach is presented to locate the root causes of the abnormal processes. A Minimal Coupled Pattern (MCP) and its degree are defined to denote the coupled structure of a system. When less than half of the faults within an MCP occur, which is defined as sparse faults, the proposed fault diagnosis procedure can identify the correct root causes with high probability. Guidelines are provided for the hyperparameters selection in the Bayesian hierarchical model. An alternative CML method for hyperparameters selection is also discussed. With the large number of potential process faults and sensor faults, an MCMC method, e.g. Metropolis-Hastings algorithm can be applied to approximate the posterior probabilities of candidate models. The monitor and diagnosis procedures are demonstrated and evaluate through an autobody assembly example.

Our objective is to monitor the changes in a proportion with correlated binary observations. All of the published work on this subject used the first-order Markov chain model for the data. Increasing the order of dependence above one by extending a standard Markov chain model entails an exponential increase of both the number of parameters and the dimension of the transition probability matrix. In this dissertation, we develop a particular Markov chain structure, the Multilevel Model (MLM), to model the correlation between binary data. The basic idea is to assign a lower probability to observing a 1 when all previous correlated observations are 0's, and a higher probability to observing a 1 as the last observed 1 gets closer to the current observation. We refer to each of the distinct situations of observing a 1 as a "level". For a given order of dependence, , at most different values of conditional probabilities of observing a 1 can be assigned. So the number of levels is always less than or equal to . Compared to a direct extension of the first-order Markov model to higher orders, our model is considerably parsimonious. The number of parameters for the MLM is only one plus the number of levels, and the transition probability matrix is . We construct a CUSUM control chart for monitoring a proportion with correlated binary observations. First, we use the probability structure of a first-order Markov chain to derive a log-likelihood ratio based CUSUM control statistic. Then, we model this CUSUM statistic itself as a Markov chain, which in turn allows for designing a control chart with specified statistical properties: the Markov Binary CUSUM (MBCUSUM) chart. We generalize the MBCUSUM to account for any order of dependence between binary observations through implying MLM to the data and to our CUSUM control statistic. We verify that the MBCUSUM has a better performance than a curtailed Shewhart chart. Also, we show that except for extremely large changes in the proportion (of interest) the MBCUSUM control chart detects the changes faster than the Bernoulli CUSUM control chart, which is designed for independent observations. / Ph. D.

We consider two applications of control charts in health care. The first involves the comparison of four methods designed to detect an increase in the incidence rate of a rare health event, such as a congenital malformation. A number of methods have been proposed: among these are the Sets method, two modifications of the Sets method, and the CUSUM method based on the Poisson distribution. Many of the previously published comparisons of these methods used unrealistic assumptions or ignored implicit assumptions which led to misleading conclusions. We consider the situation where data are observed as a sequence of Bernoulli trials and propose the Bernoulli CUSUM chart as a desirable method for the surveillance of rare health events. We compare the steady-state average run length performance of the Sets methods and its modifications to the Bernoulli CUSUM chart under a wide variety of circumstances. Except in a very few instances we find that the Bernoulli CUSUM chart performs better than the Sets method and its modifications for the extensive number of cases considered. The second application area involves monitoring clinical outcomes, which requires accounting for the fact that each patient has a different risk of death prior to undergoing a health care procedure. We propose a risk-adjusted survival time CUSUM chart (RAST CUSUM) for monitoring clinical outcomes where the primary endpoint is a continuous, time-to-event variable that is right censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart to the risk-adjusted Bernoulli CUSUM chart, using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is more efficient at detecting deterioration in the quality of a clinical procedure than the risk-adjusted Bernoulli CUSUM chart, especially when the fraction of censored observations is not too high. We address details regarding the implementation of a prospective monitoring scheme using the RAST CUSUM chart. / Ph. D.

No description available.

This study examines three applications of control charts used for monitoring syndromic data with different characteristics. The first part develops a seasonal autoregressive integrated moving average (SARIMA) based surveillance chart, and compares it with the CDC Early Aberration Reporting System (EARS) W2c method using both authentic and simulated data. After successfully removing the long-term trend and the seasonality involved in syndromic data, the performance of the SARIMA approach is shown to be better than the performance of the EARS method in terms of two key surveillance characteristics, the false alarm rate and the average time to detect the outbreaks. In the second part, we propose a generalized likelihood ratio (GLR) control chart to detect a wide range of shifts in the mean of Poisson distributed biosurveillance data. The application of a sign function on the original GLR chart statistics leads to downward-sided, upward-sided, and two-sided GLR chart statistics in an unified framework. To facilitate the use of such charts in practice, we provide detailed guidance on developing and implementing the GLR chart. Under the steady-state framework, this study indicates that the overall GLR chart performance in detecting a range of shifts of interest is superior to the performance of traditional control charts including the EARS method, Shewhart charts, EWMA charts, and CUSUM charts. There is often an excessive number of zeros involved in health care related data. Zero-inflated Poisson (ZIP) models are more appropriate than Poisson models to describe such data. The last part of the dissertation considers the GLR chart for ZIP data under a research framework similar to the second part. Because small sample sizes may influence the estimation of ZIP parameters, the efficiency of MLEs is investigated in depth, followed by suggestions for improvement. Numerical approaches to solving for the MLEs are discussed as well. Statistics for a set of GLR charts are derived, followed by modifications changing them from two-sided statistics to one-sided statistics. Although not a complete study of GLR charts for ZIP processes, due to limited time and resources, suggestions for future work are proposed at the end of this dissertation. / Ph. D.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-05-22T13:46:14Z No. of bitstreams: 1 Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5) / Made available in DSpace on 2017-05-22T13:46:14Z (GMT). No. of bitstreams: 1 Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5) Previous issue date: 2017-03-07 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Devido à dificuldade em se estimar os custos de operação associados ao monitoramento estatístico do processo nos trabalhos identificados na literatura, este trabalho tem por objetivo propor um modelo de otimização econômico para a carta de controle _X que considere as incertezas em relação aos custos variáveis e dependentes do desvio em relação à média do processo. O levantamento bibliográfico efetuado auxiliou no entendimento de como a incerteza em relação aos custos na utilização das cartas de controle são tratados. Percebeu-se o tratamento dos custos bem como do parâmetro de desvio do processo em relação a média _ como variáveis discretas e que impactavam na carta. A proposta aqui apresentada consiste em tratar não apenas o desvio em relação a média mas também dois dos custos associados à operação da carta de controle _X como variáveis aleatórias de distribuição contínua, inserindo assim um componente de incerteza na sua estimação. Desenvolveu-se assim uma nova formulação para o problema de otimização. Foram escolhidas instâncias para a otimização e comparados os resultados com os obtidos por autores da literatura. Os resultados foram obtidos por meio da metaheurística simulated annealing. Como resultados, o método mostrou-se eficiente, mostrando que o nível de dependência entre o parâmetro de mudança de processo e o custo e, da incerteza que se tem quanto aos valores definidos de custo de operação impactam nos custos totais de operação do CEP. A principal contribuição deste trabalho de pesquisa está na apresentação de uma formulação matemática de otimização da carta de controle _X que trata não somente o desvio em relação à média do processo mas também os custos de operação do CEP como variáveis aleatórias. A originalidade da formulação está em considerar os custos linearmente dependentes do tamanho do desvio do processo em relação a sua média. / Due to the difficulty in estimating the operating costs associated to the statistical monitoring of the process described in the literature, this paper aims to propose a model of economic optimization for the _X control chart that considers the uncertainties in relation to the variable costs and dependent on the deviation in relation to the average of the process. The literature review performed supported the understanding of how the uncertainty in relation to costs in the use of control charts is treated. The treatment of the costs as well as the parameter of deviation of the process in relation to the _ average were indicated as discrete variables and that impacted on the chart. The proposal presented here consists of treating not only the deviation from the mean but also two costs associated with the operation of the _X control chart as random variables of continuous distribution, thus inserting a component of uncertainty in its estimation. A new formulation for the optimization problem was developed. Instances for optimization were chosen and the results were compared with those obtained by authors described in the literature. The results were obtained through simulated annealing metaheuristics. As a result, the method proved to be efficient, showing that the level of dependence between the process change parameter and the cost, as well as the uncertainty regarding the defined operating cost values impact on the total cost of operation of the SPC. The main contribution of this research work is the presentation of a mathematical formulation of optimization of the _X control chart that treats not only the deviation in relation to the average of the process but also the operating costs of the SPC as random variables. The originality of the formulation is to consider costs linearly dependent on the size of the process deviation in relation to its mean.

The aims of this dissertation are to analyze the current state of process control, to identify the product range in selected organization and to design the process planning methodology to ensure an optimal implementation. Optimization is understood as costs minimization while keeping an acceptable continuity of supply. The dissertation contains a description of technological and non-manufacturing processes of brick products, as well as the summary and description of the basic tools of quality management.