This study aims to identify and maintain optimal stencil printer settings in dynamic surface mount technology (SMT) assembly lines to control the solder paste volume transfer efficiency (TE) and increase the yield rates of surface mount assembly (SMA) lines. Stencil printing process (SPP) is a crucial procedure that determines the first pass yields in SMA lines. Stencil printing speed (PS) and printing pressure (PP) are two critical SPP parameters in the manufacturing process; identifying the optimal printer settings in complex fabrication environment is cost efficient but challenging. To search for the global optimal PS and PP values in real time with minimal computational efforts, a dynamic optimization SPP optimization system is proposed based on a novel guided evolutionary search (GES) strategy. The GES algorithm is flexible to adjust the feasible solution region based on real-time optimization results to maximize the probability of finding optimal solutions and minimize the computational burden. As a major extension on the classical evolutionary search, the GES minimizes the possibility to fall in the local optimal due to insufficiencies in the prediction accuracy and guarantees global optimality within the dynamically varying printing environment.

中文翻译：

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实时模版印刷优化的引导式进化搜索方法

这项研究旨在确定并维持动态表面贴装技术（SMT）装配线中的最佳模板印刷机设置，以控制焊膏的体积转移效率（TE）并提高表面贴装装配（SMA）线的合格率。模板印刷工艺（SPP）是决定SMA生产线首过合格率的关键程序。模板印刷速度（PS）和印刷压力（PP）是制造过程中的两个关键SPP参数。在复杂的制造环境中确定最佳打印机设置是具有成本效益的，但具有挑战性。为了以最小的计算量实时搜索全局最优PS和PP值，提出了一种基于新型导引进化搜索（GES）策略的动态优化SPP优化系统。GES算法可灵活地根据实时优化结果来调整可行解区域，以最大程度地找到最优解，并最大程度地减少计算负担。作为经典进化搜索的主要扩展，GES最大限度地降低了由于预测精度不足而导致陷入局部最优的可能性，并保证了在动态变化的打印环境中的全局最优性。