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O presente trabalho traz um estudo para a obtenção da flexibilização das linhas de montagem na planta Anchieta da Volkswagen do Brasil. Para a implantação da flexibilização foram utilizadas interfaces inteligentes para controlar restrições e distribuições do mesmo modelo de automóvel em duas linhas produtivas. Foram aplicadas quatro interfaces inteligentes em duas linhas de produção automotivas distintas, onde o modelo Gol precisava ser feito nas duas linhas, obedecendo as restrições técnicas para alguns acabamentos específicos e visando atingir a meta de produção nestas duas linhas. Estas interfaces eram responsáveis em fazer a identificação do produto, analisar as restrições técnicas, assegurar que não existe ordem de produção duplicada e calcular a quantidade no circulante pelo volume entre o ponto de início de montagem até o ponto de escolha de linha. A automação implantada mudou de forma concreta o modo como as pessoas trabalham no dia a dia. Essa implementação foi fundamental para que a empresa conseguisse utilizar as duas linhas de processo de montagem, fazendo o modelo Gol básico, para atender a sua meta de produção diária otimizando seu curso no processo produtivo.

This paper presents a computational method based on non-classical logic dedicated to routing management and information stream control in communication networks. Paraconsistent logic (PL) was used to create an algorithmic structure whose main property is to accept contradiction. Moreover, a computational structure, the denominated paraconsistent data analyzer (PDAPAL2v), was constructed to perform routing management in communication networks. Direct comparisons of PDAPAL2v with a classical logic system that simulates routing conditions were made in the laboratory. In the conventional system, the paraconsistent algorithms were considered as binary logic gates, and in the tests, the same adjustment limits of PDAPAL2v were applied. Using a database with controlled insertion of noise, we obtained an efficacy of 97% in the detection of deteriorated packets with PDAPAL2v and 72% with the conventional simulation system. Functional tests were carried out, showing that PDAPAL2v is able to assess the conditions and degradation of links and perform the analysis and correlation of various inputs and variables, even if the signals have contradictory values. From practical tests in the laboratory, the proposed method represents a new way of managing and controlling communication network routes with good performance.

In this paper, we present an application of the Paraconsistent Artificial Neural Network (PANnet) in a Statistical Process Control to trigger alarms in an electrical power System. The PANnet is based on Paraconsistent Annotated Logic (PAL) which is a non-classical logic with properties of accepting contradictions in their fundamentals. In this work, we make a joint application technique of Paraconsistent Annotated logic, in the form of PANnet, with the concepts of Statistical Process Control (SPC). The Statistical Process Control Paraconsistent (SCP-PAL) is used in this paper to make a dynamic monitoring of the conditions of the electrical voltage in an electrical power system. To test and validate the functioning of SPC-PAL Controller we use data obtained by random computational processes and we also use a database with actual values generated by a power electrical System of a company installed in Brazil. The SPC-PAL Controller, due to the use of the algorithms of PAL in its construction, has some features that does afford optimized electrical voltage monitoring. The result of the analysis made with the SPC-PAL Controller provides three types of alarms: 1) rapid Variation in the voltage; 2) Imbalance of Mean in the Voltage data; 3) High dispersion index in the voltage data. Based on these three types of alarms we can obtain a better understanding about the operating state of the electrical power system. In the various tests performed, the SPC-PAL Controller presented a good performance and detected changes in Mean and in the variation of tension, as well as sudden changes in voltage data.

This paper shows the results of the sensing system which was designed for the autonomous mobile robot Emmy III. The proposed Sensing System has as its mean part the Paraconsistent Neural Network. This artificial neural network is based on the Paraconsistent Evidential Logics — Et. The objective of the Sensing System is to inform the other robot components about the obstacle position. The reached results have been satisfactory.

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic Eτ. A discussion on navigation system is presented.

This paper shows a controller based on the evidential annotated paraconsistent logic E - Paracontrol. The Paracontrol is a variation of the logic analyzer. This work also shows an autonomous mobile robot, which is named Emmy II, in order to demonstrate the Paracontrol's new properties. As an innovation, the Paracontrol presents besides the characteristics of the previous controller (manipulation of uncertainties, contradiction and paracompleteness information), the speed control in the various robot's actions

This paper shows the results of a sensing system for an autonomous mobile robot. The sensing system is based on the paraconsistent neural network. The type of artificial neural network used in this work is based on the paraconsistent evidential logic (Eτ). The objective of the sensing system is to inform the other robot components the obstacle position. The reached results have been satisfactory.