【摘要】 针对船板冷加工过程中碳排放严重、成形质量差等问题，以实现低碳制造与成形质量协同优化为目标，提出一种工艺参数多目标优化方法。通过系统分析船板冷加工工艺碳排放特性，构建涵盖设备能耗与材料损耗的加工过程碳排放量化模型；结合成形质量要求，建立以残余应力、回弹量和碳排放为优化目标的多目标工艺参数优化模型，并基于正交试验设计与有限元仿真技术获取工艺参数样本数据，建立设计变量与响应目标的非线性映射关系。为提升模型求解效率，提出融合旋转模拟二元交叉策略的多目标进化算法，通过收敛性分析与多样性测试验证其相较于传统算法的优越性。实验结果表明，经优化后的工艺参数组合可使加工过程碳排放降低2.945%,同时将残余应力与回弹量分别控制在220.557 MPa和8.003 mm以内。更多还原

【Abstract】 To address the severe carbon emissions and poor forming quality in ship plate cold forming processes, a multi-objective optimization method was proposed for process parameters aimed at achieving the synergistic optimization of low-carbon manufacturing and forming quality. A carbon emission quantification model for the cold forming process was established by systematically analyzing the carbon emission characteristics, incorporating equipment energy consumption and material loss. A multi-objective optimization model was constructed with residual stress, spring-back and carbon emissions as optimization targets, supported by orthogonal experimental design and finite element simulation to acquire parameter samples and establish nonlinear mapping relationships between design variables and response objectives. To enhance solving efficiency, a multi-objective evolutionary algorithm integrated with a rotational simulated binary crossover strategy was proposed, whose superiority in convergence and diversity is validated through comparative analyses with conventional algorithms. Experimental results demonstrated that the optimized process parameters reduce carbon emissions by 2.945% while controlling residual stress and spring-back within 220.557 MPa and 8.003 mm respectively.更多还原