scholarly journals A Linguistic Model Based on if-then Rules for Cutting Force Predictions in End Milling

Author(s):  
Franc Čuš ◽  
Tomaž Irgolič ◽  
Zoran Pandilov ◽  
Uroš Župerl
2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xiaoping Liao ◽  
Zhenkun Zhang ◽  
Kai Chen ◽  
Kang Li ◽  
Junyan Ma ◽  
...  

Micro-end milling is in common use of machining micro- and mesoscale products and is superior to other micro-machining processes in the manufacture of complex structures. Cutting force is the most direct factor reflecting the processing state, the change of which is related to the workpiece surface quality, tool wear and machine vibration, and so on, which indicates that it is important to analyze and predict cutting forces during machining process. In such problems, mechanistic models are frequently used for predicting machining forces and studying the effects of various process variables. However, these mechanistic models are derived based on various engineering assumptions and approximations (such as the slip-line field theory). As a result, the mechanistic models are generally less accurate. To accurately predict cutting forces, the paper proposes two modified mechanistic models, modified mechanistic models I and II. The modified mechanistic models are the integration of mathematical model based on Gaussian process (GP) adjustment model and mechanical model. Two different models have been validated on micro-end-milling experimental measurement. The mean absolute percentage errors of models I and II are 7.76% and 6.73%, respectively, while the original mechanistic model’s is 15.14%. It is obvious that the modified models are in better agreement with experiment. And model II performs better between the two modified mechanistic models.


Fractals ◽  
2018 ◽  
Vol 26 (06) ◽  
pp. 1850089 ◽  
Author(s):  
HAMIDREZA NAMAZI ◽  
ALI AKHAVAN FARID ◽  
TECK SENG CHANG

Analysis of cutting forces in machining operation is an important issue. The cutting force changes randomly in milling operation where it makes a signal by plotting over time span. An important type of analysis belongs to the study of how cutting forces change along different axes. Since cutting force has fractal characteristics, in this paper for the first time we analyze the variations of complexity of cutting force signal along different axes using fractal theory. For this purpose, we consider two cutting depths and do milling operation in dry and wet machining conditions. The obtained cutting force time series was analyzed by computing the fractal dimension. The result showed that in both wet and dry machining conditions, the feed force (along [Formula: see text]-axis) has greater fractal dimension than radial force (along [Formula: see text]-axis). In addition, the radial force (along [Formula: see text]-axis) has greater fractal dimension than thrust force (along [Formula: see text]-axis). The method of analysis that was used in this research can be applied to other machining operations to study the variations of fractal structure of cutting force signal along different axes.


Magnesium alloys have a tremendous possibility for biomedical applications due to their good biocompatibility, integrity and degradability, but their low ignition temperature and easy corrosive property restrict the machining process for potential biomedical applications. In this research, ultrasonic vibration-assisted ball milling (UVABM) for AZ31B is investigated to improve the cutting performance and get specific surface morphology in dry conditions. Cutting force and cutting temperatures are measured during UVABM. Surface roughness is measured with a white light interferometer after UVABM. The experimental results show cutting force and cutting temperature reduce due to ultrasonic vibration, and surface roughness decreases by 34.92%, compared with that got from traditional milling, which indicates UVABM is suitable to process AZ31B for potential biomedical applications.


2013 ◽  
Vol 70 (9-12) ◽  
pp. 1835-1845 ◽  
Author(s):  
Junzhan Hou ◽  
Wei Zhou ◽  
Hongjian Duan ◽  
Guang Yang ◽  
Hongwei Xu ◽  
...  

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