Abstract
Resource planning in automotive industry is a very complex process which involves the management of material and human needs and supplies. This paper deals with the production of plastic injection moulds used to make car components in the automotive industry. An efficient planning requires, among other, an accurate estimation of the task execution times in the mould production process. If the relation between task times and mould parts geometry is known, the moulds can be designed with a geometry that allows the shortest production time. We applied two popular regression approaches, Support Vector Regression and Radial Basis Function, to this problem, achieving accurate results which make feasible an automatic estimation of the task execution time.
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© 2009 Springer-Verlag Berlin Heidelberg
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Reboreda, M., Fernández-Delgado, M., Barro, S. (2009). Time Estimation in Injection Molding Production for Automotive Industry Based on SVR and RBF. In: Mira, J., Ferrández, J.M., Álvarez, J.R., de la Paz, F., Toledo, F.J. (eds) Bioinspired Applications in Artificial and Natural Computation. IWINAC 2009. Lecture Notes in Computer Science, vol 5602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02267-8_54
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DOI: https://doi.org/10.1007/978-3-642-02267-8_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02266-1
Online ISBN: 978-3-642-02267-8
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