2009 | OriginalPaper | Chapter
Time Estimation in Injection Molding Production for Automotive Industry Based on SVR and RBF
Authors : M. Reboreda, M. Fernández-Delgado, S. Barro
Published in: Bioinspired Applications in Artificial and Natural Computation
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.