CWE identification and cutting force prediction in ball-end milling process. (1st February 2023)

• Record Type: Journal Article
• Authors: Qin, Shaoqing; Hao, Yanpeng; Zhu, Lida; Wiercigroch, Marian; Yuan, Zonghui; Shi, Chuanliang; Cui, Dayu
• Is Part Of: International journal of mechanical sciences. Volume 239(2023)
• Publication Date: 2023-02-01
• Subjects: Cutting force -- Ball-end milling -- Cutter workpiece engagement -- Instantaneous undeformed chip thickness -- Sculptured surfaces; Mechanical engineering -- Periodicals; Génie mécanique -- Périodiques; Mechanical engineering; Maschinenbau; Mechanik; Zeitschrift; Periodicals; 621.05
• DOI: 10.1016/j.ijmecsci.2022.107863
• Languages: English
• ISSNs: 0020-7403

Abstract

Highlights: A new versatile algorithm to compute CWE boundaries for the ball-end milling is developed. A simplified but accurate IUCT model is proposed. Cutting force generation mechanism is analyzed via CWE and IUCT. Abstract: Ball-end milling of sculptured surfaces is an efficient and cost effective manufacturing technique when compared with other methods. However, an accurate cutting force prediction is still challenging when the Cutter Workpiece Engagement (CWE) and Instantaneous Undeformed Chip Thickness (IUCT) vary simultaneously. In order to predict the milling force accurately, an algorithm is designed to obtain the CWE boundaries with the variable tool orientations. Inspired by the main idea of analytical CWE model, an improved Z-map method is developed, which is based on the classic Z-map method. The point cloud of tool envelope surface method is generated based on the classic Z-map and the points of the CWE are screened according to the chosen criteria. Afterwards, the IUCT is calculated numerically by the accurate cutting thickness model. In order to overcome the drawbacks of the IUCT method, a simplified IUCT model is proposed to eliminate the iterative calculation. Related milling experiments were carried out on Al7075 workpiece to validate the proposed models showing a good agreement with errors smaller than 12.5%. It can be concluded from simulation results that tool postures have a significant effect on the machining process. This contributes to in-depth understanding the material removal process and optimizing the process parameters of multi-axis machining processes. Graphical abstract: Image, graphical abstract