【摘要】 针对模板清洗机存在的质量冗余问题，以关键承载结构件——电缸架为研究对象，提出一种结合熵权TOPSIS方法和响应面模型的优化设计策略。研究设计了6个尺寸变量参数，选定最大变形量、最大等效应力及总质量作为响应参数。通过正交试验设计，运用熵权TOPSIS方法计算各变量参数的综合贡献值，剔除对响应参数影响较小的变量，有效降低优化计算成本。采用拉丁超立方抽样方法，成功获取25组样本点，基于这些样本点构建了kriging响应面模型。通过多目标遗传算法(MOGA)与kriging响应面模型结合，对电缸架进行多目标优化求解，得到Pareto最优解集。优化结果表明，在确保结构强度的前提下，电缸架的总质量减少39%。更多还原

【Abstract】 To address the quality redundancy in the template cleaning machine, this paper proposes an optimized design strategy, focusing on the critical load-bearing component and the electric cylinder frame.The strategy integrates the entropy weight TOPSIS method with response surface modeling. First, six dimensional variable parameters are designed with maximum deformation, maximum equivalent stressand total mass selected as response parameters. Orthogonal experimental design is employed and the entropy weight TOPSIS method is utilized to calculate the comprehensive contribution values of each variable parameter, thus eliminating variables with minor impacts on response parameters, markedly reducing optimization calculation costs. Furthermore, by employing Latin hypercube sampling, 25 sample points are successfully obtained. Based on these sample points, a kriging response surface model is built. By integrating multi-objective genetic algorithm(MOGA) with the kriging response surface model, multi-objective optimization of the electric cylinder frame is achieved, resulting in Pareto optimal solution sets.Optimization results demonstrate a reduction of 39% in total mass of the electric cylinder frame while structural strength is ensured.更多还原