ABSTRACT
A crucial component of CNC machine tools is the linear precision sliding table, but how to improve the support and fatigue resistance performance of the slide table base has been a problem to be solved. In this research, a variable density method based on interpolating functions is used to topologically optimise the slide table base for better load-carrying capacity. The minimal compliance subject to a specified mass percentage constraint is formulated, and a quadratic topology optimisation by expanding the solution domain yields an innovative base structure. A comprehensive assessment of the structural performance of the new base was performed, including maximum von Mises stresses and cumulative fatigue damage for the reference load case. The fatigue resistance of the optimised slide table base in the reference condition proved to be much better than that of the original structure, while the new design also reduced the mass of the base. These findings conclusively show that the proposed topology optimisation methodology can propose novel base designs that can reduce the experimental cycle time in the design of the base.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available from the corresponding author, Dr. XH Zhang, upon reasonable request.
Additional information
Funding
Notes on contributors
Xiaohong Zhang
Xiaohong Zhang, male, professor, research interest on Precision and ultra-precision machining.
Biao Wang
Biao Wang, male, Master student, research interest on Optimised design of linear slide table.
Liqu Wu
Liqu Wu, male, Master student, research interest on Hard and brittle material polishing processing.
Dongdong Wen
Dongdong Wen, male, PhD student, research interest on Precision and ultra-precision machining.
Zhiyuan Yang
Zhiyuan Yang, male, engineer, Research interest on electromagnetic stirring technology.
Hexing Zhang
Hexing Zhang, male, undergraduate, research interest on Mechanical engineering and automation.