The panel furniture industry is experiencing rapid development, with a growing focus on intelligent manufacturing and efficient production. However, in the process of upgrading the drilling process for panel furniture towards intelligentization, still lacks standard optimization methods. To address this issue, we conducted an analysis of the cabinet structure in panel furniture and propose a novel approach that utilizes matrices and sets to represent panel and drilling information, enabling efficient data analysis and subsequent optimization. Moreover, we introduce a comprehensive optimization method comprising the COING (a hierarchical clustering analysis method adapted for panel furniture based on the STING grid method) and AR (Association Rule) techniques, uncovering potential associations and relationships within datasets. To validate the efficacy of the proposed method, we implemented it in the production workshop of Company W. Experimental results demonstrate a 14.01% reduction in drilling frequency and a 3.869% improvement in drilling efficiency compared to traditional design methods. Our findings emphasize the practical significance of the proposed standard drilling optimization method in the panel furniture industry, effectively enhancing drilling efficiency and promoting the transition to intelligent manufacturing.