Prediction of flow length in injection molding for engineering plastics by fuzzy logic under different processing conditions

Salimi A., SUBAŞI M. , Buldu L., KARATAŞ Ç.

IRANIAN POLYMER JOURNAL, vol.22, no.1, pp.33-41, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 1
  • Publication Date: 2013
  • Doi Number: 10.1007/s13726-012-0103-5
  • Title of Journal : IRANIAN POLYMER JOURNAL
  • Page Numbers: pp.33-41
  • Keywords: Flow length, Injection molding, Fuzzy logic, Engineering plastics, Prediction, PROCESS PARAMETERS, NEURAL-NETWORKS, YIELD


Flow length determination is one of the most important tasks in injection mold design. In order to achieve the perfect filling of the mold, proper designs for the channel depth and other injection parameters (such as melt temperature, injection pressure and etc.) should be conducted. In this research, melt temperature and injection pressure were considered as input parameters to investigate the flow length, in the most commonly used plastics including acrylonitrile butadiene styrene (ABS), polycarbonate (PC), polyamide 6.6 (PA 6.6), polyoxymethylene (POM). This study was carried out, based on various channel depths, according to ASTM D 3123. A new method based on a fuzzy logic method was developed to predict the amount of flow length in relation to the input parameters such as pressure, channel depth, and temperature. When the present method is used, the problem of finding the optimum mold design can be solved faster compared to the traditional modeling programs. The largest estimated amounts of flow lengths by the fuzzy logic model were 1215, 596, 963 and 1040 mm for POM, PC, PA 6.6 and ABS, respectively. The maximum measured values were 1235, 579, 948 and 1050 mm for the same material. Experimental tests have been conducted to justify the accuracy of the developed method. It was confirmed by regression analysis that the amount of R-2 for the measured and estimated values was 0.920529. The results of this research show that the fuzzy logic system is a reliable method to predict the short shots in an injection process.