Cutting forces and cutting quality in the up-milling of solid wood using ceramic cutting tools

Guo, Xiaolei; Wang, Jinxin; Buck, Dietrich; Zhu, Zhi‐Biao; Ekevad, Mats

doi:10.1007/s00170-021-06991-x

Cited by 7 publications

(2 citation statements)

References 23 publications

(24 reference statements)

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“…At the moment when the cutter teeth leave the workpiece, the maximum chip thickness is a max . Taking the contact arc as the average calculation point, the average chip thickness, a av , is calculated using Equation (1) [20]:…”

Section: Experiments Designmentioning

confidence: 99%

Research on the End-Milling Surface Quality of Paulownia Based on Response Surface Model in Terms of Force and Chip Morphology

Wang,

Wu,

Zhang

et al. 2024

Forests

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To investigate the impact of different milling parameters on milling forces, chip morphology, and machined surface quality during the Paulownia milling process, we conducted experiments using cemented carbide single-tooth shank milling cutters. Additionally, we established a response surface model (RSM) to analyze milling surface quality. The key findings are as follows: milling forces along the parallel and tangential axes decrease with an increased tool rake angle and spindle’s rotational frequency, but they exhibit a positive correlation with milling depth. The effect of spindle’s rotational frequency on the milling force along the lateral axis differs due to the complex fiber characteristics of Paulownia. As milling depth decreases, chip morphology transitions from a block structure to a sheet structure, eventually becoming fragmented with shallow milling. Higher spindle’s rotational frequency and tool rake angle lead to a more fragmented direction in Paulownia chip morphology, while machined surface quality improves. Notably, under specific conditions, a striped chip morphology significantly enhances machined surface quality compared to similar milling parameters. The established RSM for machined Paulownia surface roughness is reliable and holds reference value for inhibiting surface damage in Paulownia machining.

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Section: Experiments Designmentioning

confidence: 99%

Research on the End-Milling Surface Quality of Paulownia Based on Response Surface Model in Terms of Force and Chip Morphology

Wang,

Wu,

Zhang

et al. 2024

Forests

Self Cite

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“…However, it decreased with the increase in the rake angle. A decrease in the cutting force has been observed with the increase in the rake angle [40][41][42], resulting in lower cutting power required [43]. With the increase in the depth of milling, the material removal rate increased, which consumed more energy.…”

Section: Influence Of Input Parameters On P C and ηmentioning

confidence: 99%

Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards

Yao

et al. 2022

Materials

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The cutting power consumption of milling has direct influence on the economic benefits of manufacturing particle boards. The influence of the milling parameters on the cutting power were investigated in this study. Experiments and data analyses were conducted based on the response surface methodology. The results show that the input parameters had significant effects on the cutting power. The high rake angle reduced the cutting force. Thus, the cutting power decreased with the increase in the rake angle and the cutting energy consumption was also reduced. The cutting power increased with the rotation speed of the main shaft and the depth of milling induced the impact resistance between the milling tool and particle board and the material removal rate. The P-values of the created models and input parameters were less than 0.05, which meant they were significant for cutting power and power efficiency. The depth of milling was the most important factor, followed by the rotation speed of the main shaft and then the rake angle. Due to the high values of R2 of 0.9926 and 0.9946, the quadratic models were chosen for creating the relationship between the input parameters and response parameters. The predicted values of cutting power and power efficiency were close to the actual values, which meant the models could perform good predictions. To minimize the cutting power and maximize the power efficiency for the particle board, the optimized parameters obtained via the response surface methodology were 2°, 6991.7 rpm, 1.36 mm for rake angle, rotation speed of the main shaft and depth of milling, respectively. The model further predicted that the optimized parameters combination would achieve cutting power and power efficiency values of 52.4 W and 11.9%, respectively, with the desirability of 0.732. In this study, the influence of the input parameters on the cutting power and power efficiency are revealed and the created models were useful for selecting the milling parameters for particle boards, to reduce the cutting power.

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A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of thin-walled structural components

Bai

Chen

et al. 2022

Front. Mech. Eng.

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Cutting forces and cutting quality in the up-milling of solid wood using ceramic cutting tools

Cited by 7 publications

References 23 publications

Research on the End-Milling Surface Quality of Paulownia Based on Response Surface Model in Terms of Force and Chip Morphology

Research on the End-Milling Surface Quality of Paulownia Based on Response Surface Model in Terms of Force and Chip Morphology

Study of Cutting Power and Power Efficiency during Straight-Tooth Cylindrical Milling Process of Particle Boards

A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of thin-walled structural components

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