Dynamic modelling for the family of 5-axis CNC milling machines with application to feed-rate optimization

Chu, Anh-My; Nguyen, Van-Cong; Le, Chi-Hieu; Gao, James; Packianather, Michael; Soe, Shwe

Abstract

The 5-axis CNC milling machines are complex mechanical systems, and they can be designed with hundreds of 5 degrees of freedom mechanisms. The kinematic and dynamic modelling of machines is crucial for optimising the machine design and the milling process. However, formulating the dynamics model of 5-axis milling machines has never been proposed so far. Moreover, efforts have been made to develop kinematic models for the machines; however, formulating the generalized kinematic model for all possible 5-axis milling machines in closed form is challenging. In this paper, a novel method of kinematic and dynamic modelling for the entire family of 5-axis milling machines is developed. First, the special features of the machines family are fully studied to formulate effectively the generalized forward and inverse kinematic equations in closed-form. Second, by treating each 5-axis mechanism as a closed mechanism subject to a nonlinear kinematic constraint characterizing the machining process, the dynamics model for the whole family of 5-axis milling machines is successfully formulated, and the inverse dynamic equation is derived in closed-form. Finally, to demonstrate the importance and impact of the proposed method, useful applications were conducted; and these were supported by both numerical simulations and actual cutting experiments. Compared with previous works, our study includes new generalized equations of kinematics and dynamics for the family of 5-axis milling machines, and useful applications of the proposed equations for optimization of the 5-axis machining.

• Journal Article Type: Article
• Acceptance Date: Feb 18, 2025
• Online Publication Date: Mar 13, 2025
• Publication Date: May 31, 2025
• Deposit Date: Mar 22, 2025
• Publicly Available Date: Mar 25, 2025
• Journal: Engineering Science and Technology, an International Journal
• Print ISSN: 2215-0986
• Electronic ISSN: 2215-0986
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 65
• Article Number: 102015
• DOI: https://doi.org/10.1016/j.jestch.2025.102015
• Public URL: https://uwe-repository.worktribe.com/output/13970672
• Additional Information: This article is maintained by: Elsevier; Article Title: Dynamic modelling for the family of 5-axis CNC milling machines with application to feed-rate optimization; Journal Title: Engineering Science and Technology, an International Journal; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jestch.2025.102015; Content Type: article; Copyright: © 2025 Published by Elsevier B.V. on behalf of Karabuk University.