6 resultados para Statistical Quality Control

em Universidade Federal do Rio Grande do Norte(UFRN)


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LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

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The present work is grounded basically on the use of the Basic Tools for the Statistic Process Control SPC, with the intent to detect non-conformities on a given productive process. It consists on a case study accomplished at a Hemocenter in Natal (Rio Grande do Norte). In this study it is shown that, the Statistic Process Control Technique, which was used as a tool, is useful to identify on-conformities on the volume of hemocomponents. The gathering of the used data was performed by means of document analysis, direct observations and database queries. The results achieved from the study show that the analyzed products, even though when they have presented, in some cases, points out of control, they satisfied the ANVISA standards. Finally, suggestions for further improvement of the final product and guidance for future employment of CEP, also extended to other lines of production, are presented

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This Master Thesis presents a case study on the use of Statistical Process Control (SPC) at the Núcleo de Pesquisas em Alimentos e Medicamentos (NUPLAM). The SPC basic tools have been applied in the process of the tuberculostáticos drugs encapsulation, primarily concerning the objective to choose, between two speeds, which one is the best one to perform the tuberculostatics encapsulation. Later on, with the company effectively operating, the SPC was applied intending to know the variability of the process and, through the tracking of the process itself, to arrive at an estimated limit for the control of future lots of tuberculostatics of equal dosage. As special causes were detected acting in the process, a cause-and-effect diagram was built in order to try to discover, in each factor that composes the productive process, the possible causes of variation of the capsules average weight. The hypotheses raised will be able to serve as a base for deepened the study to eliminate or reduce these interferences in the process. Also a study on the capacity of the process to attend the specifications was carried out, and this study has shown the process´s inaptitude to take care of them. However, on the side of NUPLAM exists a real yearning to implant the SPC and consequently to improve the existing quality already present on its medicines

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This work presents a study in quality of health care, with focus on consulting appointment. The main purpose is to define a statistical model and propose a quality grade of the consulting appointment time. The time considered is that from the day the patient get the appointment done to the day the consulting is realized. It is used reliability techniques and functions that has as main characteristic the analysis of data regarding the time of occurrence certain event. It is gathered a random sample of 1743 patients in the appointment system of a University Hospital - the Hospital Universitário Onofre Lopes - of the Federal University of Rio Grande do Norte, Brazil. The sample is randomly stratified in terms on clinical specialty. The data were analyzed against the parametric methods of the reliability statistics and the adjustment of the regression model resulted in the Weibull distribution being best fit to data. The quality grade proposed is based in the PAHO criteria for a consulting appointment and result that no clinic got the PAHO quality grade. The quality grade proposed could be used to define priority for improvement and as criteria to quality control

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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study

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LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007