Abstract: Intelligent manufacturing, characterized by capabilities such as self-awareness, self-learning, decision-making, and adaptability, is being progressively integrated into various manufacturing processes including design, production, management, and services. Merging new information and communication technologies with advanced manufacturing methods, it establishes a new production paradigm. Given its definition and the requirements of large-scale equipment manufacturing, intelligent manufacturing is distinguished by four key characteristics: dynamic perception, real-time analysis, autonomous decision-making, and precise execution. Scholars globally have dissected its five-layer architecture encompassing enterprise alliance, enterprise management, production management, control execution, and intelligent equipment layers. Within these, the intelligent equipment layer, which includes processing, assembly, and measurement and testing equipment, is directly linked to metrological assurance. Ensuring real-time online accuracy and reliability of measurement data from intelligent equipment is essential for effective intelligent manufacturing. This paper systematically analyzes the metrological needs of intelligent manufacturing and delves into the elements of processing equipment, assembly equipment, testing equipment, and modeling algorithms, with the objective of constructing a key common metrological technology system.