Rapid sequence optimization of spot welds for improved geometrical quality using a novel stepwise algorithm

Joining sequence optimization is a combinatorial problem, requiring extensive computational time. The significance of determination of an optimal sequence for improved geometrical quality is substantial. Previously, genetic algorithms have been studied for defining the optimal sequence. However, these algorithms are highly dependent on the internal parameters, requiring additional computational analysis and thereby extended evaluation time. In this article, a novel robust stepwise algorithm is introduced to determine the optimal weld sequence. Application of the proposed algorithm leads to drastic time improvements for defining the optimal weld sequence of each assembly. Three industrial assemblies are evaluated. Comparison with the previously applied population-based optimization algorithms indicates that the optimization time can be reduced drastically with the proposed stepwise algorithm. The stepwise algorithm is intended to be applied in a geometry assurance digital twin, where the assembly parameters are being optimized for each individual assembly.

连接序列优化属于组合优化问题，需耗费大量计算时间。为提升装配几何质量而确定最优序列的意义极为重大。此前已有研究采用遗传算法求解最优连接序列，但这类算法高度依赖内部参数，需开展额外计算分析，进而延长了评估耗时。本文提出一种新型鲁棒逐步算法，用于求解最优焊接序列。将所提算法应用于各装配体的最优焊接序列求解时，可大幅缩减计算耗时。本文针对三个工业装配体开展了验证评估。与此前采用的基于种群的优化算法对比可知，本文提出的逐步算法可显著降低优化所需时间。该逐步算法旨在应用于几何保证数字孪生（Geometry Assurance Digital Twin）系统中，针对单个装配体优化其装配参数。