992 resultados para Statistical control
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The oil industry has several segments that can impact the environment. Among these, produced water which has been highlight in the environmental problem because of the great volume generated and its toxic composition. Those waters are the major source of waste in the oil industry. The composition of the produced water is strongly dependent on the production field. A good example is the wastewater produced on a Petrobras operating unit of Rio Grande do Norte and Ceará (UO-RNCE). A single effluent treatment station (ETS) of this unit receives effluent from 48 wells (onshore and offshore), which leads a large fluctuations in the water quality that can become a complicating factor for future treatment processes. The present work aims to realize a diagnosis of a sample of produced water from the OU - RNCE in compliance to certain physical and physico-chemical parameters (chloride concentration, conductivity, dissolved oxygen, pH, TOG (oil & grease), nitrate concentration, turbidity, salinity and temperature). The analysis of the effluent is accomplished by means of a MP TROLL 9500 Multiparameter probe, a TOG/TPH Infracal from Wilks Enterprise Corp. - Model HATR - T (TOG) and a MD-31 condutivimeter of Digimed. Results were analyzed by univariated and multivariated analysis (principal component analysis) associated statistical control charts. The multivariate analysis showed a negative correlation between dissolved oxygen and turbidity (-0.55) and positive correlations between salinity and chloride (1), conductivity, chloride and salinity (0.70). Multivariated analysis showed there are seven principal components which can explain the variability of the parameters. The variables, salinity, conductivity and chloride were the most important variables, with, higher sampling variance. Statistical control charts have helped to establish a general trend between the physical and chemical evaluated parameters
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The chart of control of Hotelling T2 has been the main statistical device used in monitoring multivariate processes. Currently the technological development of control systems and automation enabled a high rate of collection of information of the production systems in very short time intervals, causing a dependency between the results of observations. This phenomenon known as auto correlation causes in the statistical control of the multivariate processes a high rate of false alarms, prejudicing in the chart performance. This entails the violation of the assumption of independence and normality of the distribution. In this thesis we considered not only the correlation between two variables, but also the dependence between observations of the same variable, that is, auto correlation. It was studied by simulation, the bi variate case and the effect of auto correlation on the performance of the T2 chart of Hotelling.
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O conceito de controle de qualidade nas operações inserido na agricultura é viabilizado por incidir diretamente nos principais objetivos do processo produtivo: retorno econômico e aumento da produtividade. A colheita mecanizada normalmente é realizada sem que haja controle efetivo para que a variabilidade das perdas fique dentro de padrões aceitáveis. Esta pesquisa teve o objetivo de determinar e caracterizar as perdas e a distribuição da cobertura vegetal após a colheita mecanizada da soja, por meio de ferramenta de controle estatístico de processo (cartas de controle). A média da perda de grãos total foi próxima do limite superior aceitável para a cultura da soja, apresentando alta variabilidade entre os pontos, tornando o processo fora de controle. A distribuição de cobertura vegetal manteve-se em processo controlado, com maior variabilidade onde o relevo foi mais inclinado. A utilização das cartas de controle foi eficiente na identificação dos pontos fora de controle e na avaliação da qualidade do processo de colheita.
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A colheita mecanizada de café se destaca como um dos principais avanços tecnológicos em benefício dos produtores, porém, problemas com planejamento no plantio e desenvolvimento da cultura, bem como falhas na regulagem da colhedora, podem acarretar em redução na eficiência da operação, tornando-a mais estressante para a cultura que a colheita manual. Diante disso, o presente trabalho foi realizado no município de Patos de Minas, MG, com o objetivo de avaliar os danos na parte vegetativa e a qualidade da colheita mecanizada do café cultivado em plantio circular sob pivô central, com duas frequências de vibração das hastes, sob o controle estatístico do processo. Observou-se que a bienalidade negativa sobre a cultura reduziram a carga inicial de café, eliminando o efeito das condições de insolação. Os índices de qualidade da colheita apresentaram distribuição assimétrica, com grande variabilidade nas amostras, sendo apenas a eficiência de derriça influenciada pelos eixos avaliados, e se mostrando estável pelo controle estatístico. Os danos causados às plantas pela colheita apresentaram valores desejáveis, não variando em função dos fatores analisados, mas sendo considerado sob controle estatístico.
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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 X̄ 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) X̄ chart are obtained using Markov chains. The VSS X̄ chart is substantially quicker than the traditional X̄ chart in detecting moderate shifts in the process.
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Throughout this article, it is assumed that the no-central chi-square chart with two stage samplings (TSS Chisquare chart) is employed to monitor a process where the observations from the quality characteristic of interest X are independent and identically normally distributed with mean μ and variance σ2. The process is considered to start with the mean and the variance on target (μ = μ0; σ2 = σ0 2), but at some random time in the future an assignable cause shifts the mean from μ0 to μ1 = μ0 ± δσ0, δ >0 and/or increases the variance from σ0 2 to σ1 2 = γ2σ0 2, γ > 1. Before the assignable cause occurrence, the process is considered to be in a state of statistical control (defined by the in-control state). Similar to the Shewhart charts, samples of size n 0+ 1 are taken from the process at regular time intervals. The samplings are performed in two stages. At the first stage, the first item of the i-th sample is inspected. If its X value, say Xil, is close to the target value (|Xil-μ0|< w0σ 0, w0>0), then the sampling is interrupted. Otherwise, at the second stage, the remaining n0 items are inspected and the following statistic is computed. Wt = Σj=2n 0+1(Xij - μ0 + ξiσ 0)2 i = 1,2 Let d be a positive constant then ξ, =d if Xil > 0 ; otherwise ξi =-d. A signal is given at sample i if |Xil-μ0| > w0σ 0 and W1 > knia:tl, where kChi is the factor used in determining the upper control limit for the non-central chi-square chart. If devices such as go and no-go gauges can be considered, then measurements are not required except when the sampling goes to the second stage. Let P be the probability of deciding that the process is in control and P 1, i=1,2, be the probability of deciding that the process is in control at stage / of the sampling procedure. Thus P = P1 + P 2 - P1P2, P1 = Pr[μ0 - w0σ0 ≤ X ≤ μ0+ w 0σ0] P2=Pr[W ≤ kChi σ0 2], (3) During the in-control period, W / σ0 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ0 = n0d2, i.e. W / σ0 2 - xn0 22 (λ0) During the out-of-control period, W / σ1 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ1 = n0(δ + ξ)2 / γ2 The effectiveness of a control chart in detecting a process change can be measured by the average run length (ARL), which is the speed with which a control chart detects process shifts. The ARL for the proposed chart is easily determined because in this case, the number of samples before a signal is a geometrically distributed random variable with parameter 1-P, that is, ARL = I /(1-P). It is shown that the performance of the proposed chart is better than the joint X̄ and R charts, Furthermore, if the TSS Chi-square chart is used for monitoring diameters, volumes, weights, etc., then appropriate devices, such as go-no-go gauges can be used to decide if the sampling should go to the second stage or not. When the process is stable, and the joint X̄ and R charts are in use, the monitoring becomes monotonous because rarely an X̄ or R value fall outside the control limits. The natural consequence is the user to pay less and less attention to the steps required to obtain the X̄ and R value. In some cases, this lack of attention can result in serious mistakes. The TSS Chi-square chart has the advantage that most of the samplings are interrupted, consequently, most of the time the user will be working with attributes. Our experience shows that the inspection of one item by attribute is much less monotonous than measuring four or five items at each sampling.
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The sugarcane mechanized planting is becoming increasingly widespread in Brazil due to a higher operability and better working conditions offered to workers compared to other types of planting. Studies related to this topic are insufficient or scarce in Brazil. In this context, the aim of this study was to evaluate the operation quality of sugarcane mechanized planting in two operation shifts, by means of statistical process control. The mechanized planting was held on March 2012 and statistical design was completely randomized with two treatments, totaling 40 replications for the day shift and 40 replications for the night shift. The variables evaluated were: speed, engine rotation, engine oil pressure, water temperature of the engine, effective field capacity and the time consumption hourly and effective fuel. The use of statistical control charts showed that random intrinsic do not cause this process. The tractor alignment error showed outliers in the day and night shifts operations, indicating a possible delay in receiving the signal. The water temperature of the engine and the effective fuel consumption showed lower variability in nighttime operation with average values of 81°C and 22.66 L ha-1, respectively. The hourly fuel consumption had greater variability and consequently lower quality during the night of the operation, with an average consumption of 25.46 L h-1 while the day shift showed 26.86 L h-1.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The mechanical harvesting is an important stage in the production process of soybeans and, in this process; the loss of a significant number of grains is common. Despite the existence of mechanisms to monitor these losses, it is still essential to use sampling methods to quantify them. Assuming that the size of the sample area affects the reliability and variability between samples in quantifying losses, this paper aimed to analyze the variability and feasibility of using different sizes of sample area (1, 2 and 3 m²) in quantifying losses in the mechanical harvesting of soybeans. Were sampled 36 sites and the cutting losses, losses by other mechanisms of the combine and total losses were evaluated, as well as the water content in seeds, straw distribution and crop productivity. Data were subjected to statistical analysis (descriptive statistics and analysis of variance) and Statistical Control Process (SCP). The coefficients of variation were similar for the three frames available. Combine losses showed stable behavior, whereas cutting losses and total losses showed unstable behavior. The frame size did not affect the quantification and variability of losses in the mechanical harvesting of soybeans, thus a frame of 1 m² can be used for determining losses.
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During the sugarcane mechanized harvester process, the wear of base cutting knives is directly correlated to the quality of the cut made by the machines, and the use of quality control tools important in monitoring this process. Thus, the present study in Ribeirão Preto region aimed to assess the knives cut baseline and damage caused to wear brass knuckles in mechanized harvesting of cane raw sugar, from the viewpoint of statistical quality control (SQC). The wear of the knives was quantified by mass loss and its dimensions, while cutting quality was assessed by cutting height and damage to stumps visually classified according to the level of damage caused. The results showed that the wear of the knives was more pronounced in certain periods of use, but still within control standards. The cutting height was not affected by the wear of the knives, keeping within the limits of desirable quality for operation. Eventually damage the stumps ranged among themselves depending on each face of the cutting knives evaluated, and the predominance of certain classes of damage in each cutting face, but always remained in statistical control.
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV