This chapter first highlights the importance of facility location selection in supply chain management. Subsequently, a hot topic in semiconductor supply chain management, supply chain localization, is introduced, in which semiconductor manufacturing capacity originally owned by wafer foundries is to be transferred back to the home countries of chip makers. Facility location selection becomes especially critical and urgent in semiconductor supply chain localization. Artificial intelligence (AI) applications in facility location selection are then reviewed. However, some of these AI applications are not easy to comprehend or communicate. Therefore, explainable artificial intelligence (XAI) techniques and tools are proposed to explain the reasoning process and results of these AI applications, such as hanging gradient bar charts, gradient heatmaps, hanging group gradient bar charts, gradient bidirectional scatterplots, traceable aggregation plot, Shapley value (SHAP) analysis, and local interpretable model-agnostic explanations (LIME).