6 resultados para Computer software - 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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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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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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This work presents the research carried through in the industrial segment of confection of clothes of the Great Natal whose objective is to show the profile, enterprise and technological management as also the use of simultaneous engineering in the development of products. The research approaches two studies. The first one presents the current picture of the companies, synthesized through twelve variable. As, through fifteen variable it shows to the level of use of Simultaneous Engineering in the Development of Products and its amplitude in relation to the Integrated Management using tools CAD, PDM and ERP (Computer Aided Design, Product Management Date, Enterprise Resource Planning). The integration of these systems acts aiming the reduction of the cost and the development time of products. The reached results indicate that simultaneous engineering is a competitive advantage and becomes possible: to reduce the life cycle of the product, to rationalize the resources, to incorporate one high standard of the quality to the process and product as well as to personalize the product to take care of the global market. It is important to note that this work also is considered to contribute for the better understanding of the real companies situation of confection located at the Great Natal and its role in the economy of the State of the Rio Grande do Norte

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Currently there is still a high demand for quality control in manufacturing processes of mechanical parts. This keeps alive the need for the inspection activity of final products ranging from dimensional analysis to chemical composition of products. Usually this task may be done through various nondestructive and destructive methods that ensure the integrity of the parts. The result generated by these modern inspection tools ends up not being able to geometrically define the real damage and, therefore, cannot be properly displayed on a computing environment screen. Virtual 3D visualization may help identify damage that would hardly be detected by any other methods. One may find some commercial softwares that seek to address the stages of a design and simulation of mechanical parts in order to predict possible damages trying to diminish potential undesirable events. However, the challenge of developing softwares capable of integrating the various design activities, product inspection, results of non-destructive testing as well as the simulation of damage still needs the attention of researchers. This was the motivation to conduct a methodological study for implementation of a versatile CAD/CAE computer kernel capable of helping programmers in developing softwares applied to the activities of design and simulation of mechanics parts under stress. In this research it is presented interesting results obtained from the use of the developed kernel showing that it was successfully applied to case studies of design including parts presenting specific geometries, namely: mechanical prostheses, heat exchangers and piping of oil and gas. Finally, the conclusions regarding the experience of merging CAD and CAE theories to develop the kernel, so as to result in a tool adaptable to various applications of the metalworking industry are presented

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Formal methods and software testing are tools to obtain and control software quality. When used together, they provide mechanisms for software specification, verification and error detection. Even though formal methods allow software to be mathematically verified, they are not enough to assure that a system is free of faults, thus, software testing techniques are necessary to complement the process of verification and validation of a system. Model Based Testing techniques allow tests to be generated from other software artifacts such as specifications and abstract models. Using formal specifications as basis for test creation, we can generate better quality tests, because these specifications are usually precise and free of ambiguity. Fernanda Souza (2009) proposed a method to define test cases from B Method specifications. This method used information from the machine s invariant and the operation s precondition to define positive and negative test cases for an operation, using equivalent class partitioning and boundary value analysis based techniques. However, the method proposed in 2009 was not automated and had conceptual deficiencies like, for instance, it did not fit in a well defined coverage criteria classification. We started our work with a case study that applied the method in an example of B specification from the industry. Based in this case study we ve obtained subsidies to improve it. In our work we evolved the proposed method, rewriting it and adding characteristics to make it compatible with a test classification used by the community. We also improved the method to support specifications structured in different components, to use information from the operation s behavior on the test case generation process and to use new coverage criterias. Besides, we have implemented a tool to automate the method and we have submitted it to more complex case studies