42 resultados para intelligent manufacturing systems


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Studies show the positive effects that video games can have on student performance and attitude towards learning. In the past few years, strategies have been generated to optimize the use of technological resources with the aim of facilitating widespread adoption of technology in the classroom. Given its low acquisition and maintenance costs, the interpersonal computer allows individual interaction and simultaneous learning with large groups of students. The purpose of this work was to compare arithmetical knowledge acquired by third-grade students through the use of game-based activities and non-game-based activities using an interpersonal computer, with knowledge acquired through the use of traditional paper-and-pencil activities, and to analyze their impact in various socio-cultural contexts. To do this, a quasi-experimental study was conducted with 271 students in three different countries (Brazil, Chile, and Costa Rica), in both rural and urban schools. A set of educational games for practising arithmetic was developed and tested in six schools within these three countries. Results show that there were no significant differences (ANCOVA) in the learning acquired from game-based vs. non-game-based activities. However, both showed a significant difference when compared with the traditional method. Additionally, both groups using the interpersonal computer showed higher levels of student interest than the traditional method group, and these technological methods were seen to be especially effective in increasing learning among weaker students.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Purpose – The purpose of this paper is to investigate how company size and the type of production system affect the adoption of supply chain management (SCM) practices in companies in the electro‐electronics sector in Brazil. Design/methodology/approach – An e‐mail survey of 107 companies associated with the Brazilian Electrical and Electronics Industry Association (ABINEE) was conducted. Statistical techniques were employed to verify the adoption of SCM practices according to the size of the company and its production system. Findings – The major results indicate that the larger the size of the company, the higher the level of adoption of SCM practices, and that the choice of SCM practices depends upon the type of production system implemented. Practical implications – The implications of this study are useful to top management leaders of small and medium‐sized enterprises since the findings enable them to identify the most common practices adopted by either large‐, medium‐ or small‐sized companies in order to benchmark the level of adoption of SCM practices. Production managers can also benefit from this study by identifying the SCM practices that may support certain production systems.

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Automated Production Systems Development involves aspects concerning the integration of technological components that exist on the market, such as: Programmable Logic Controllers (PLC), robot manipulators, various sensors and actuators, image processing systems, communication networks and collaborative supervisory systems; all integrated into a single application. This paper proposes an automated platform for experimentation, implemented through typical architecture for Automated Production Systems, which integrates the technological components described above, in order to allow researchers and students to carry out practical laboratory activities. These activities will complement the theoretical knowledge acquired by the students in the classroom, thus improving their training and professional skills. A platform designed using this generic structure will allow users to work within an educational environment that reflects most aspects found in Industrial Automated Manufacturing Systems, such as technology integration, communication networks, process control and production management. In addition, this platform offers the possibility complete automated process of control and supervision via remote connection through the internet (WebLab), enabling knowledge sharing between different teaching and research groups.

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The advantages offered by the electronic component light emitting diode ( LED) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data. (C) 2005 Elsevier B.V. All rights reserved.

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This paper deals with the design of a network-on-chip reconfigurable pseudorandom number generation unit that can map and execute meta-heuristic algorithms in hardware. The unit can be configured to implement one of the following five linear generator algorithms: a multiplicative congruential, a mixed congruential, a standard multiple recursive, a mixed multiple recursive, and a multiply-with-carry. The generation unit can be used both as a pseudorandom and a message passing-based server, which is able to produce pseudorandom numbers on demand, sending them to the network-on-chip blocks that originate the service request. The generator architecture has been mapped to a field programmable gate array, and showed that millions of numbers in 32-, 64-, 96-, or 128-bit formats can be produced in tens of milliseconds. (C) 2011 Elsevier B.V. All rights reserved.

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The advantages offered by the electronic component LED (Light Emitting Diode) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data.

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Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

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An intelligent system that emulates human decision behaviour based on visual data acquisition is proposed. The approach is useful in applications where images are used to supply information to specialists who will choose suitable actions. An artificial neural classifier aids a fuzzy decision support system to deal with uncertainty and imprecision present in available information. Advantages of both techniques are exploited complementarily. As an example, this method was applied in automatic focus checking and adjustment in video monitor manufacturing. Copyright © 2005 IFAC.

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The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.