Contributions to Ranking an Ergonomic Workstation, Considering the Human Effort and the Microclimate Parameters, Using Neural Networks

Daniel Constantin Anghel; Nadia Belu

doi:10.4028/www.scientific.net/AMM.371.812

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Contributions to Ranking an Ergonomic Workstation, Considering the Human Effort and the Microclimate Parameters, Using Neural Networks

Abstract:

The paper presents a method to use a feed forward neural network in order to rank a working place from the manufacture industry. Neural networks excel in gathering difficult non-linear relationships between the inputs and outputs of a system. The neural network is simulated with a simple simulator: SSNN. In this paper, we considered as relevant for a work place ranking, 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, 13 neurons in the hidden layer and 1 neuron in the output layer. We present also some experimental results obtained through simulations.

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Periodical:

Applied Mechanics and Materials (Volume 371)

Pages:

812-816

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.371.812

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Online since:

August 2013

Authors:

Daniel Constantin Anghel, Nadia Belu

Keywords:

Ergonomics, Neural Network (NN), Workplace Ranking

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References

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