In this paper, the traditional bee colony algorithm is improved, and its roundness error evaluation method is improved. For the roundness profile data of the part, the improved bee colony algorithm is used to determine the position and size of the circle. In order to improve the efficiency of the algorithm, the local search region of the population initialization is determined according to the definition of roundness error. The evaluation accuracy of this algorithm is better than common ones.

A novel parallel leaf-spring carrying mechanism was designed and studied for high-precision fast wafer positioning and transfer in lithography. Displacement was used to calculate the equilibrium attitude, and the laser triangulation coordinate method was used for attitude measurement. The effectiveness of the attitude model was shown by numerical analysis and experimental verification. The methods can be used as a reference for the analysis and design of a complex parallel compliant mechanism.

This paper takes the special machine tool for VH-CATT cylindrical gears as the research object. On the premise of machine tool modularization, the module configuration sequence of the machine tool is determined based on the depth-first search algorithm. The module is retrieved based on rough set theory and the fuzzy similarity priority ratio algorithm, and the module is instanced and traversed according to the configuration sequence to obtain the machine tool module configuration scheme.

In the early stage of the creative design of mechanisms, design work was accomplished mainly based on researchers' experience and inspiration, resulting in a low design efficiency. Moreover, the derived mechanism configurations were very limited. An effective mechanism design method is based on the atlas of topological structures of kinematic chains. Our research on the structural synthesis of kinematic chain inversions plays an important role in the improvement of mechanism design efficiency.

Springback is an inevitable problem in the local bending process of hull plates, which leads to low processing efficiency and affects the assembly accuracy. Therefore, the prediction of the springback effect, as a result of the local bending of hull plates, bears great significance. In total, four springback prediction models, based on genetic and back propagation neural network (GA-BPNN) algorithms and the improved particle swarm optimization (PSO)-BPNN algorithms, are established.