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首页> 外文期刊>Journal of Applied Polymer Science >Multiobjective Optimization Design of Heating System in Electric Heating Rapid Thermal Cycling Mold for Yielding High Gloss Parts
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Multiobjective Optimization Design of Heating System in Electric Heating Rapid Thermal Cycling Mold for Yielding High Gloss Parts

机译：高光泽零件电加热快速热循环模具加热系统的多目标优化设计

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摘要

An optimization design method is developed for the electric heating system in rapid thermal cycling molding (RTCM) mold. First, a multiobjective optimization model is established, in which the distance between the mold cavity surface and the center of heating elements and the number and power density of heating elements are the design variables, the required heating time t_h and the highest cavity surface temperature T_(max) at time t_h are the objective functions. Then, an optimization strategy consisting of design of experiment, finite element analysis, artificial neural network (ANN) and response surface methodology (RSM) models, and Paretobased genetic algorithm is proposed to solve the multiobjective optimization model. Finally, the optimization strategy is applied for the design of the heating system for an automotive spoiler blow mold. The results show that the temperature distribution uniformity on the blow mold cavity surface is obviously improved and high heating efficiency is also ensured with the optimized design parameters. Moreover, the ANN model exhibits its superiority over the RSM model in terms of modeling and predictive abilities. A RTCM blow mold with the optimized electric heating system is constructed and successfully utilized to mold high gloss automotive spoiler.
机译：针对快速热循环成型（RTCM）模具中的电加热系统，开发了一种优化设计方法。首先，建立一个多目标优化模型，其中模具型腔表面与加热元件中心的距离以及加热元件的数量和功率密度是设计变量，所需加热时间t_h和最高模腔表面温度T_ t_h时刻的（max）是目标函数。然后，提出了一种由实验设计，有限元分析，人工神经网络（ANN）和响应面方法（RSM）模型以及基于帕累托遗传算法组成的优化策略来求解多目标优化模型。最后，将优化策略应用于汽车扰流板吹塑模具的加热系统设计。结果表明，采用优化的设计参数，吹塑模腔表面的温度分布均匀性得到明显改善，并确保了较高的加热效率。此外，在建模和预测能力方面，ANN模型表现出优于RSM模型的优势。构造了具有优化的电加热系统的RTCM吹模，并成功地将其用于成型高光泽度的汽车扰流板。

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