Abstract: In recent years, driven by advancements in artificial intelligence (AI) technology and the urgent need for intelligent transformation in the mining industry, data has emerged as a critical production factor, with data acquisition serving as the cornerstone for building intelligent mines. Mineral processing constitutes a vital stage in mineral resource development, wherein intelligent sorting functions as a key component of intelligent mines. The optimization and control of critical processes—such as grinding and classification, flotation, and gravity separation—rely heavily on the acquisition of production data. Consequently, the mineral processing industry demands data acquisition methods that are easy to implement, cost−effective, highly stable, and cause minimal interference. By establishing a communication link between industrial personal computer (IPC) and the target Siemens S7 series programmable logic controller (PLC), production data can be directly acquired from the PLC using the open−source Snap7 library implemented in C#, thereby enabling efficient data acquisition for mineral processing operations. In a specific engineering project, a data acquisition system developed using this approach operated stably for two years, collecting over one million data records without any interference to the existing S7 series PLC control system, and successfully supported the establishment of a database for the intelligent sorting process.