Optimal design of heating system for electrical rapid heat cycle mold based on multi-objective optimization, multiple-attribute decision-making, and conformal design theory. (August 2018)

• Record Type: Journal Article
• Authors: Li, Jiquan; Li, Taidong; Peng, Xiang; Liu, Feng; Zhou, Hangchao; Jiang, Shaofei
• Is Part Of: Advances in mechanical engineering. Volume 10:Number 8(2018)
• Publication Date: 2018-08
• Subjects: Electrical rapid heat cycle molding -- heating cell unit -- back propagation neural network -- non-dominated sorting genetic algorithm-II -- technique for order preference by similarity to ideal solution; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814018789504
• Languages: English
• ISSNs: 1687-8132

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.