Vortices often arise in fluid processes when abrupt changes in the flow occur. Such vortices can induce unexpected flow behavior and hinder the intended operation of the process. They may lead to flow instabilities or even cause degradation of the fluid itself. Therefore, to achieve an ideal process, it is essential to predict flow behavior during process design and to prevent undesirable phenomena such as vortex formation in advance. This study focuses particularly on the prediction of vortices. Vortices in flows can occur at various locations and are generally classified into boundary vortices and internal vortices. Among these, boundary vortices frequently appear in many fluid processes due to complex equipment geometries that induce sudden changes in flow near boundaries. In this work, we propose a method for identifying boundary vortices based on the concept of the streamfunction. The proposed technique is applied to various flow cases to detect boundary vortices, demonstrating its applicability and effectiveness. Among these cases, special emphasis is placed on identifying vortices that occur in the slot-die coating process, in which battery slurry is coated onto a substrate to fabricate electrodes. Battery slurry must be well dispersed to ensure high electrode performance. However, when vortices form during the coating process, flow stagnation within the vortical regions promotes particle aggregation and agglomeration, causing the slurry behavior to deviate from the intended flow. Consequently, suppressing vortex formation in the slot-die coating process is of critical importance, and naturally, identifying such vortices is equally essential. In this regard, the results obtained by applying the proposed streamfunction-based identification method to the slot-die coating process are analyzed and discussed.