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Contact stiffness is an important parameter for describing the contact behavior of rough surfaces. In this study, to more accurately describe the contact stiffness between grinding surfaces of steel materials, a novel microcontact stiffness model is proposed. In this model, the novel cosine curve-shaped asperity and the conventional Gauss distribution are used to develop a simulated rough surface. Based on this simulated rough surface, the analytical expression of the microcontact stiffness model is obtained using contact mechanics theory and statistical theory. Finally, an experimental study of the contact stiffness of rough surfaces was conducted on different steel materials of various levels of roughness. The comparison results reveal that the prediction results of the present model show the same trend as that of the experimental results; the contact stiffness increases with increasing contact pressure. Under the same contact pressure, the present model is closer to the experimental results than the already existing elastic–plastic contact (CEB) and finite-element microcontact stiffness (KE) models, whose hypothesis of a single asperity is hemispherical. In addition, under the same contact pressure, the contact stiffness of the same steel material decreases with increasing roughness, whereas the contact stiffness values of different steel materials under the same roughness show only small differences. The correctness and accuracy of the present model can be demonstrated by analyzing the measured asperity geometry of steel materials and experimental results.

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Well-structured design knowledge is crucial to Design for Mass Customization (DFMC). It is a formidable challenge to tackle various structures and meaning Chinese semi-structural design knowledge. Chinese text description is a notable data characteristic when analyzing the knowledge requirements of DFMC. A knowledge management system architecture is proposed based on a relational database server cooperating with a Chinese full text database server. Grounding on Chinese semantics, the system functions are implemented which include knowledge representation, knowledge acquisition, knowledge reasoning, and knowledge service and system management. With the intelligent processing and service of design knowledge based on Chinese semantics, the construction of the knowledge management system for DFMC facilitates product development.

The contour error of the machined parts is an important index to evaluate the accuracy of CNC machining. Considering multi-axis servo control system, a predictive compensation strategy for contour error is presented in this paper. First, the offline identification method is adopted to establish the transfer function of each motion system. In this case, the relationship between the interpolation command and the feedback position of the grating is determined for the selected machine tool. Thus, before machining, the trajectory information of each motion axis can be predicted according to the interpolation instruction and the transfer relationship. It can be converted into the contour trajectory of the part through kinematic analysis, so as to predict the contour error. Finally, the predicted contour error is compensated into the command trajectory to ensure the contour accuracy of the part to be machined. Compared to existing methods, our method can effectively reduce the trial-produced cycle of parts and avoid unnecessary waste of processing materials. Moreover, without increasing the complexity of the control system and greatly reducing the machining efficiency, the dynamic error caused by the dynamic characteristics of the shaft is reduced. Taking the starfish pattern and the contour line of the impeller as the milling processing experiment case, the contour error after compensation is greatly reduced compared with the contour error processed by the original command. Therefore, the predictive compensation method proposed in this paper can significantly improve the machining accuracy. In addition, it also has application value for trial production of complex curved parts.