Background The lack of a systematic selection framework for the selection of linear feed mechanisms in precision machine tools results in a mismatch between the performance of the mechanism and the specific application requirements in terms of accuracy, stiffness and load capacity, which restricts the optimization design of high-performance machining systems. Objectives We are committed to establishing a systematic classification system to categorize existing technologies and define their quantified performance boundaries, in order to guide the optimal choices of institutions and future innovation directions. Methods This review establishes a structured classification system, dividing mechanisms into four clear categories: typical linear drive mechanisms, linear linkage mechanisms, high-precision feed mechanisms and novel linear mechanisms. We compared and analyzed their working principles based on key parameters such as positioning accuracy, structural stiffness and load capacity; quantified their performance boundaries; and provided their applications. At the end of each section, a table is listed to summarize the content for easy reference. Discussions The analysis reveals that a typical linear feed mechanism, as the basic unit of machine tool linear motion, is widely used but has low accuracy. A linear linkage mechanism may not have high accuracy, but it can help machine tools complete specific structures. A high-precision linear feed mechanism has high precision, usually reaching the micrometer level, and is applied in scenarios with high precision requirements. The new linear feed mechanism represents the direction of technological development and guides the optimization design of machine tools. Results The performance-oriented classification framework developed in this study effectively resolves the selection challenge for precision linear feed mechanisms in machine tools. Its theoretical contribution lies in proposing a systematic performance spectrum, while its practical significance is to provide engineers with a clear decision-making tool for mechanism selection and to illuminate directed pathways for future innovation in precision motion systems.
Zhou et al. (Thu,) studied this question.