Design and Comparative Analysis of Mathematical and Simulation Models in Injection Molding Decision System


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Abstract


Injection molding is a very challenging process for many manufacturers and researchers to produce the products meeting requirements at lower cost. Many algorithms and techniques have been developed with simulation and mathematical models for the injection molding design and development process. Some mathematical or simulation techniques improve the production capacity, while some other improve the quality of knowledge base. But, it is uncertain that all these mathematical or simulation model based techniques provide high production capacity at all times. Thus, analysis is necessary for the techniques that are utilized in the injection molding process. Hence, in this study, a mathematical model for the injection molding decision system is proposed. The injection molding decision system with efficient parameters is developed by means of both simulation and mathematical models. In both models, the product quality value is computed by utilizing parameter values in different experiments and the decision is taken by using the environment parameters and the computed quality values. The performance of both analytical models in the injection molding decision system is analyzed with more experimental parameter values. Moreover, the performances of both models are compared to find the model having high score performance in product quality as well as in molding decision.
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Keywords


Injection Molding Design; Feed Forward Back Propagation Neural Network (FFBNN); Fuzzy Inference System (FIS); Fuzzy Rules; Process Parameters; Simulation Based Model; Mathematical Based Model and Polynomial Coefficients

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