Determination of effecting process parameters with artificial neural network
Journal Title: Scholars Journal of Engineering and Technology - Year 2017, Vol 5, Issue 9
Abstract
Abstract:The injection of PVC polimers with a molded has been studied. Experimentally, parameters were measured for different processing conditions. Injection molding is the most widely used process in manufacturing plastic products. An empirical model to decide the shrinkages of thermoplastic polymers in the injection process. Polyvnyl chloride was used in this study to test the effectiveness of the model. Comparing the calculated results, it was found that the shrinkage ratio obtained with the present model are in agreement with those obtained by using inline processes. ANN method, a Levenberg Marquardt algorithm neural network model is developed to map the complex non linear relationship between process conditions of the injection molded parts an ANN model. This method is used in the process optimization for an industrial part in order to improve the volumetric shrinkage variation in the part. The results show that the this method is an effective tool for the process optimization of injection molding. The simulations and calculations of the algorithms are done in MATLAB Packaged Program Environment. MPC is especially suitable for controlling these types of systems. MATLAB Packaged Program is utilized in all these studies. Keywords:Plastic injection molding; Simulation; Optimization; Artificial neural network
Authors and Affiliations
Bekir Cirak
Keywords
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