Parametric vs. neural network models for the estimation of production costs: A case study in the automotive industry [An article from: International Journal of Production Economics]

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Description:
This paper aims at illustrating the compared results of the application of two different approaches-respectively parametric and artificial neural network techniques-for the estimation of the unitary manufacturing costs of a new type of brake disks produced by an Italian manufacturing firm. The results seem to confirm the validity of the neural network theory in this application field, but not a clear superiority with respect to the more ''traditional'' parametric approach: in particular, the ANN seems to be characterised by a better trade-off between precision and cost of development, while a critical point-especially in the specific application context-is represented by the reduced possibility of interpreting output data (which is critical for the ''optimisation'' of design solutions during the new product development process).