Abstract
To improve the heating efficiency and cavity surface temperature uniformity, an optimal design method was developed for the heating system in electrical rapid heat cycle molding mold. First, an electrical rapid heat cycle molding mold was simplified as a single heating cell unit for thermal response analysis based on conformal design theory. Second, a response surface using back propagation neural network was constructed on the ground of initial finite element experiments. Then, a non-dominated sorting genetic algorithm-II combined with the polynomial back propagation neural network model was proposed to capture the Pareto-optimal solutions. Subsequently, the technique for order preference by similarity to ideal solution based on entropy-based weight was adopted as a multi-attribute decision-making method to choose the trade-off optimal design point from the Pareto-optimal set. To gain the optimal design of heating system, the optimized heating cell unit for electrical rapid heat cycle molding mold was calculated and finally mapped into the entire mold. Cavity surface temperature uniformity increased by 17.1%, and heating efficiency increased by 26%. The results show that the temperature distribution uniformity on the mold cavity surface was obviously improved and using this optimization strategy ensured high heating efficiency.
Highlights
IntroductionInjection molding technology is widely used to manufacture plastics parts because of its low cost and high productivity.[1,2,3] In conventional injection molding (CIM), the mold temperature is constant, potentially resulting in poor part surface quality, such as welding line, flowing mark, and sink mark on the surface of molded parts.[4,5]
Optimization objectives t (s) to the optimum value of 7.61 s and the cavity surface temperature difference is reduced by 17.1% from the original value of 7.47°C to the optimum value of 6.19°C, which indicates an improvement in both heating efficiency and cavity surface temperature uniformity by optimization
Based on the assumption of single heating cell unit, an optimal result of a uniform temperature field was obtained by combining various methods (BPNN, non-dominated sorting genetic algorithm-II (NSGA-II), and TOPSIS)
Summary
Injection molding technology is widely used to manufacture plastics parts because of its low cost and high productivity.[1,2,3] In conventional injection molding (CIM), the mold temperature is constant, potentially resulting in poor part surface quality, such as welding line, flowing mark, and sink mark on the surface of molded parts.[4,5]. An optimal design method is proposed for the heating system of electrical rapid heat cycle injection molding (ERHCM) to improve both heating efficiency and temperature uniformity of cavity surface. A multi-objective optimization model of heating cell unit was established, in which the specifications and layout of the electrical heating element are the design parameters, while the required heating time and cavity surface temperature difference are the thermal response index. The input layer has four neurons which are design parameters of the heating cell unit (d, q, h, and p), the hidden layer has nine neurons, and the output layer has two neurons which are the required heating time t and maximum cavity surface temperature difference DT.
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