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The paper presents a method based on the neural networks to study of working conditions, for the workstations from the manufacture industry. The neural networks were chosen because they excel in gathering difficult non-linear relationships between the inputs and outputs of a system. The neural network was simulated with Matlab. In this paper, we considered as relevant for the study of working conditions, 6 input parameters: temperature, humidity, noise, luminosity, load and frequency. The neural network designed for the study presented in this paper has 6 input neurons and 3 neurons in the output layer. Some experimental results obtained through simulations, are presented in the final part of the paper.

Today, for the enterprises, the competition is more and more intense and more competitor try to satisfy their customers. In the field of automotive industry, the demands for the product increase and the company need to satisfy the demand. As the demands increases, the company should produce more product than usual. In the same time the comfort and health of the workers should be consider. Some factors such as workstation design should take into consideration in order to increase the productivity and at the same time protect workers from accidents and health problem. Therefore, the workstations need to be redesign by applying the ergonomics principles. This paper presents the combined application of Artificial Neural Networks and the Rapid Upper Limb Assessment (RULA) Analysis in the process of redesign ergonomic workstations. Artificial Neural Networks excel in gathering difficult non-linear relationships between the inputs and outputs of a system. We used, in this work, a feed forward neural network in order to ranking a workstation. The neural network is simulated with MATLAB. The experiment presented in this paper was realized at University of Piteşti, Faculty of Mechanics and Technology, Department of Manufacturing and Industrial Management, using CATIA V5 software.

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Abstract. This paper presents a method for locating the operators, equipment and parts using radio communications systems. Specifically there will be radio transceiver arranged in a network of active and passive radio receivers placed on personnel, equipment or parts. Based on a radio triangulation method, it is determined the location of the all resources and parts involved in manufacturing process. The transceivers communicate with each other via "routers" -also components of the network. Such a structure may extend over large distances even in indoor spaces where there are obstacles (walls between rooms). The location is done by determining the power of transmission signal for at least three end points. The receiver position is then transmitted over the network through routers, to a central server where all positions of the resources are centralized. Our solution is a non-invasive and low cost method for determining resource position in the factory. The system can be used for both resource planning production for current process more efficient and for further analysis of the movement of resources during previous processes with possible adjustments to the workspace and re-planning of resources for future processes.