This study aims to explore the application of embodied intelligence in the field of intelligent manufacturing, providing both theoretical support and practical guidance for its implementation, thereby promoting the high-quality development and upgrading of the manufacturing industry. The evolution of intelligent manufacturing is reviewed across three stages: rule-based automated manufacturing, data-driven digital intelligent manufacturing, and embodied-intelligence-enabled intelligent manufacturing. From the perspectives of interaction models, key technical elements, and architectural frameworks, a technical system for embodied intelligence-driven intelligent manufacturing is constructed, emphasizing core technologies such as multimodal industrial data fusion and perception, embodied-intelligence-enabled intelligent manufacturing powered by foundation models, force control, and robotic motion planning. Embodied intelligence drives the development of intelligent manufacturing from the aspects of production, warehousing and logistics, inspection and maintenance, and human‒robot collaboration. However, it also faces practical challenges, including limitations due to a lack of multimodal data, difficulties in perception and understanding in complex manufacturing environments, application security risks caused by AI hallucinations, bottlenecks in software‒hardware integration, and compliance issues caused by the absence of ethical and legal standards. The study proposes the following recommendations: intensifying technical research to overcome key bottlenecks, improving the industrial ecosystem to promote real-world application, establishing standards to ensure production safety, and expanding application scenarios to unlock new market opportunities.