11 resultados para Spare parts classification

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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This paper presents a proposal of a model to measure the efficiency of outsourced companies in the aeronautical industry applying the methods DEA and AHP. It also proposes an evaluation in the relation between the variables of the process and the value obtained for the effiiency. The criteria of Quality, Time and Cost were considered the outputs of the process, and those criteria were quantified by AHP for DEA matrix.The number of technical documents received by those outsorced companies were considered the input of the process. The other purpose is to separate the companies in groups considered able to receive an investment to improve their process. Copyright © 2008 SAE International.

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Pós-graduação em Engenharia Mecânica - FEG

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

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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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In the current economic scenario of constant changes, industries seek to increase their profitability decreasing inventory levels. Maintenance and maintenance management, combined with the inventory management of spare parts, has assumed a position of competitive advantage in business. Stock only what you need has become a difficult decision for managers, who are faced with the lack of models and criteria to assist this decision-making. This work proposes a method which supports decision making, on a MATLAB modeling, using criteria established by an expert and his maintenance workers team, focusing on no regular demand of spare parts. The proposed model was adequate to the needs of the company and the maintenance manager in the decision on the storage

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Pós-graduação em Engenharia Mecânica - FEG

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

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Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.