Abstract: As key components of machine tools, spindles, tools and ball screws directly affect the quality and efficiency of machine tool processing. Traditional methods of assessing the condition of critical components based on manual experience have limitations in terms of efficiency and accuracy. In view of the above problems, this paper focuses on the condition monitoring process and hot technologies of key components of machine tools in the context of intelligent manufacturing. Firstly, according to the types of key components, the deployment types and application frequencies of sensors in different research questions were counted. Secondly, the core technologies are summarized into two aspects, namely state feature extraction and state intelligent recognition, and the latest research results of time-domain analysis, frequency-domain analysis, time-frequency domain analysis, mechanism-driven, data-driven, and mechanism-data fusion-driven methods are reviewed in detail. Finally, the technical challenges faced by the intelligent monitoring of the status of key components of machine tools are summarized, and the future development trend is prospected from the aspects of application scenario expansion, monitoring accuracy improvement, and monitoring method innovation.