As a core component of Industry 4.0, intelligent manufacturing systems are gradually becoming a key driving force for the transformation and upgrading of the manufacturing industry. This research aims to optimize the performance of intelligent manufacturing systems by integrating intelligent control algorithms and big data analysis technology. First, this article introduces the basic principles of intelligent control algorithms and their application scenarios in intelligent manufacturing. Subsequently, this article explores the key role of big data analytics in manufacturing data processing and how to improve production efficiency and quality through a data-driven approach. The research focus is on how to combine intelligent control algorithms with big data analysis to form a collaborative optimization framework to achieve optimization of resource allocation, automation of the production process and continuous improvement of product quality. Through the application verification of multiple actual manufacturing scenarios, the results show that the four satisfaction levels of the intelligent manufacturing system based on intelligent control algorithms and big data analysis increased from 52.21 to 85.12% in the initial system effect improvement satisfaction, efficiency improvement satisfaction, user satisfaction, and revenue improvement. It can be seen that this system can effectively improve the intelligence level of the manufacturing system and provide strong technical support for the digital transformation of the manufacturing industry.