Elliptical vibration-assisted cutting technology has been widely applied in complicated functional micro-structured surface texturing. Elliptical-arc-beam spherical flexure hinges have promising applications in the design of 3D elliptical vibration-assisted cutting mechanisms due to their high motion accuracy and large motion ranges. Analytical compliance matrix formulation of flexure hinges is the basis for achieving high-precision positioning performance of these mechanisms, but few studies focus on this topic. In this paper, analytical compliance equations of spatial elliptic-arc-beam spherical flexure hinges are derived, offering a convenient tool for analysis at early stages of mechanism design. The mechanical model of a generalized flexure hinge is firstly established based on Castigliano’s Second Theorem. By introducing the eccentric angle as the integral variable, the compliance matrix of the elliptical-arc-beam spherical flexure hinge is formulated. Finite element analysis is carried out to verify the accuracy of the derived analytical compliance matrix. The compliance factors calculated by the analytical equations agree well with those solved in the finite element analysis for the maximum error; average relative error and relative standard deviation are 8.25%, 1.83% and 1.78%, respectively. This work lays the foundations for the design and modeling of 3D elliptical vibration-assisted cutting mechanisms based on elliptical-arc-beam spherical flexure hinges.

Stability prediction of the securing system for autonomous trucks is an important prerequisite for achieving safety monitoring of large cargo transportation and improving logistics efficiency. Considering the side slide risk of large cargo and the inability to predict stability using the existing under-constrained friction securing model, this paper proposes a new vehicle–cargo securing model based on the 6-SPS parallel mechanism. By establishing an analytical 3-DOF model, the dynamics performance of the vehicle–cargo system is analyzed based on the response solution under sinusoidal excitations. To verify the correctness of the analytical model, a multi-body dynamics model of the whole vehicle–cargo system based on the three-dimensional geometric model and the 6-SPS parallel mechanism is established for simulation in ADAMS. According to road class, pavement roughness is modeled by a white noise power spectrum method as the excitation in the simulation. The results show that the dynamics response of the analytical model accords well with that of the simulation model, with relative errors of 8.34% and 0.036% in amplitude and frequency, respectively. The proposed method can provide theoretical support for accurate stability prediction and for achieving safety monitoring of large cargo transportation for autonomous trucks.

The dynamic servo error of heavy-duty vertical machining centres is one of the decisive factors affecting the machining accuracy of large and complex parts. Due to the characteristics of large mass, large load, and the large travel distance of the machine tool, non-linear factors such as friction, backlash, and lateral shift are more likely to cause unstable behaviours such as stick-slip and oscillation of the servo feed system of the machine tool, and reduce the performance and servo accuracy of the motion axis. In this paper, to consider the influence of non-linear factors such as friction, backlash, and lateral shift, an appropriately simplified representation of the mechanical transmission system of the ball screw has been used. According to the control structure of the Siemens 840D numerical control system, a theoretical model of the servo feed system for the heavy-duty vertical machining centre was established based on three-loop control. Then, the single-axis and double-axis closed-loop simulation models of the servo feed system were built in Simulink, and the influence pattern of control parameters and nonlinear factors on the dynamic servo error was obtained through simulation analysis. Finally, the validity of the theoretical model for the servo feed system was verified through a comprehensive comparison of simulation and experimental outcomes. This encompasses an analysis of the control system Bode plots, critical stick-slip velocity, and tracking errors in the X-axis with linear motion. The validation provides theoretical guidance for parameter design and mechanical adjustments of the servo feed system in heavy-duty vertical machining centres.

Due to the large size and large span of heavy-duty machine tools, the structural deformation errors caused by gravity account for a large proportion of the static errors, and the influence of gravity deformation must thus be considered in the machine tool precision design. This paper proposes a precision design method for heavy-duty vertical machining centers based on gravity deformation error modelling. By abstracting the machine tool into a multibody system topology, the static error model of the machine tool is established based on the multibody system theory and a homogeneous coordinate transformation. Assuming that the static error of each motion axis is composed of two parts, i.e., the manufacturing-induced geometric error and the gravity deformation error, the machine tool stiffness model of the relationship between gravity and deformation error is developed using the spatial beam elements. In the modelling process, the stiffness coefficients and volume coefficients of the components are introduced to fully consider the influences of structural parameters on machine tool precision. Taking the machine tool static precision, the component stiffness coefficients and the volume coefficients as the design variables, based on the use of the worst condition method, error sensitivity analysis and global optimization algorithm, the optimal allocation of the static error budget of the machine tool and the structural design requirements of each component are determined, providing a valuable guide for the detailed structure design and manufacture processing of the machine tool components.

This paper focuses on the MKE1620A CNC cylindrical grinder, using an equivalent analysis of the joint spring-damping characteristics to investigate the overall performance of the grinder and propose directions for design optimization. A total of 168 spring-damper elements were established to model the fixed, movable, and bearing joints. These elements were classified and calculated to determine their parameters, which were then incorporated into a finite element analysis model to examine the impact of joint stiffness on the static and dynamic performance of the machine tool, with results showing less than a 10% error compared to actual measured data. Additionally, the paper investigates how the quality of six common structural materials influences the first-order natural frequency of components and explores the relationship between variations in joint stiffness and changes in the machine tool’s natural frequency. The findings provide theoretical and data-driven insights for the design and optimization of CNC cylindrical grinding machines, serving as a valuable reference for enhancing machine tool performance and machining quality.

A high vacuum environment safeguards the performance of special processing technologies and high-precision parts such as nanosecond laser processing, chip packaging, and optical components. However, it poses higher requirements for the machine tool, which makes the temperature control of machine tools an important goal in design and development. In this paper, the thermal properties of a large-scale 5-axis laser processing machine tool in a vacuum environment were investigated. The thermal contact resistance between parts is identified by the parametric simulation and experiment. The whole machine temperature field was then obtained based on the fluid–thermal coupling model and verified by experiment. The results showed that the thermal contact resistance of the motor and reducer with the water cold plate was 560 W/(m²∙°C) and 510 W/(m²∙°C), respectively, and the maximum temperature increase of the machine was 3 °C. Based on the results, the machine tool’s temperature increase prediction chart was obtained by simulation under different processing conditions such as cooling water flow rate, cooling water temperature, motor speed, and ambient temperature. It provides technical and data references for the research on the thermal stability of the machine tool in processing.