Time Estimation in Injection Molding Production for Automative Industry Based on SVR and RBF

TítuloTime Estimation in Injection Molding Production for Automative Industry Based on SVR and RBF
AutoresM. Reboreda, M. Fernández-Delgado, S. Barro
TipoComunicación para congreso
Fonte 3rd International Work-Conference on the Interplay Between Natural and Artificial Computation, Santiago de Compostela (Spain), Springer, pp. 509-518 , 2009.
AbstractResource 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.
Palabras chaveFunction approximation, Automotive industry, Plastic injection mould, Support Vector Regression, Radial Basis Function