Status Analysis of Quality Prediction for Automotive Injection Molded Parts

Abstract:

Injection molding is a very complex multi-factor coupling effect and a nonlinear dynamic process. Therefore, under the influence of nonlinear and multi-factor, injection molding goal is to effectively predict and guarantee the quality of injection molded parts. In this paper, the common methods used to predict the quality of injection molded parts are introduced, including: Taguchi method, artificial neural network, response surface method, radial basis function method and Kriging model method. Research progresses as well as application examples of forecasting methods at home and abroad is summarized. Besides, the development trend of the injection molding quality prediction is discussed.

• Periodical: Advanced Materials Research (Volumes 998-999)
• Pages: 534-537
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.998-999.534
• Online since: July 2014
• Authors: Chun Neng Wang, Xi Ying Fan*
• Keywords: Injection Molding, Parameter Optimization, Predict Method, Quality Prediction

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