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Ball screw mechanisms (BSMs) are used as accuracy transmission components in a wide range of industries and are characterized by their high accuracy. More specifically, the positioning accuracy of BSM has a significant effect on the accuracy of machine tool. Based on the macro-micro multiscale method, an exponential prediction model for the BSM positioning accuracy was developed considering time-varying working conditions (load and rotational speed) and feed modes. Since the accuracy degradation is mainly caused by wear, a microscopic approach was proposed to describe the positioning accuracy retention and the microscopic wear process was investigated. The sliding contact of the asperities between the ball and raceway was analyzed, and the microscopic wear behavior of the asperities was determined. Considering the time-varying working conditions, the BSM positioning accuracy characteristics were obtained under the normal feed mode by conducting suitable tests. The exponential wear model used the wear index to describe the wear status based on the positioning accuracy measurement. The accuracy loss value and the prediction index of positioning accuracy were determined based on an exponential model, and the effective lifetime of the BSM was predicted. Finally, the exponential prediction model was used in negative/positive skew feed distribution, and the effective lifetime determined.

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A flexible manufacturing system (FMS) improves productivity and makes it more efficient. Maintaining reliability levels and reducing costs through proper maintenance strategies are key problems for the development and application of a FMS. This paper proposes a grouping preventive maintenance strategy of a FMS with optimized parameters by considering both reliability and cost. In this work, a three-layer evaluation index system is first presented to accurately estimate the reliability of the FMS; index weights of each layer were obtained by reliability importance modeling and analysis, considering maintenance strategies. An element-grouping preventive strategy is proposed based on an influencing analysis, and a parameter optimization problem (considering reliability and maintenance costs) was established. In this strategy, three maintenance methods are presented for the elements, including low-level maintenance with a large period, low-level maintenance with a small period, as well as the combination of low-level maintenance with a small period and high-level maintenance with a large period; the effects of reliability improvement of the elements on the subsystem’s reliability were analyzed to provide evidence for element grouping. Finally, the proposed method was applied to a box-part finishing FMS; the results indicate that this method can effectively reduce maintenance costs on the premise of satisfying the reliability requirements.