<p>This study investigated the risk distribution of an intelligent production mode for meat products by taking a cooked sausage smart factory as a representative case. This study analyzed the key smart equipment, systems, and microbial contamination across the whole production process to identify critical risk points and propose adaptive risk management strategies. Results of microbial analysis of processed samples and environmental air demonstrated that the highly automated and intelligent production scenario significantly reduced the likelihood of microbial contamination in products. However, it concurrently imposed more stringent requirements on workshop environmental control and the performance stability of relevant production equipment and systems. Based on these findings, this study systematically applied Hazard Analysis and Critical Control Point (HACCP) principles to delineate risk factors that diverged from traditional production paradigms, establishing specific monitoring targets including automated guided vehicles (AGVs), intelligent temperature monitoring devices, and distributed control systems, etc. Thus, five critical control points (CCPs) and one operational prerequisite program (OPRP) were determined: ingredient receiving inspection, adjunct ingredient addition, cooking and sterilization, metal detection, workshop environment (CCPs), along with equipment and systems (OPRP). Ultimately, a data-driven risk control logic centered on the stability and reliability of equipment and systems was established. This study proposed an exploratory framework designed to optimize critical control processes in the meat industry, thereby enhancing the assurance of food safety through systematic and data-driven process management.</p>