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A neural network model, trained by a genetic algorithm, has been developed to study the
thickened ends of the pipes rolled by means of two stretch-reducing mills. The forecasting
of the model showed a good performance that avoids other complicated developments based
on precise structural approaches that generally take a great amount of elaboration time.
The neural network can be applied to build an automatic procedure for the definition of
the production parameters to minimize the discarded material of the pipe that is not
in the limits imposed by the geometrical specifications.
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