A survey on artificial intelligence technologies in modeling of High Speed end-milling processes

Author(s):  
Amin J. Torabi ◽  
Er Meng Joo ◽  
Li Xiang ◽  
Lim Beng Siong ◽  
Zhai Lianyin ◽  
...  
Polymers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 312
Author(s):  
Naruki Hagiwara ◽  
Shoma Sekizaki ◽  
Yuji Kuwahara ◽  
Tetsuya Asai ◽  
Megumi Akai-Kasaya

Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources. A possible solution to this issue is the development of processing circuits that physically resemble an artificial brain, which can offer low-energy loss and high-speed processing. This study demonstrated the synaptic functions of conductive polymer wires linking arbitrary electrodes in solution. By controlling the conductance of the wires, synaptic functions such as long-term potentiation and short-term plasticity were achieved, which are similar to the manner in which a synapse changes the strength of its connections. This novel organic artificial synapse can be used to construct information-processing circuits by wiring from scratch and learning efficiently in response to external stimuli.


Author(s):  
Mohammad Malekan ◽  
Camilla D. Bloch-Jensen ◽  
Maryam Alizadeh Zolbin ◽  
Klaus B. Ørskov ◽  
Henrik M. Jensen ◽  
...  

2012 ◽  
Vol 576 ◽  
pp. 60-63 ◽  
Author(s):  
N.A.H. Jasni ◽  
Mohd Amri Lajis

Hard milling of hardened steel has wide application in mould and die industries. However, milling induced surface finish has received little attention. An experimental investigation is conducted to comprehensively characterize the surface roughness of AISI D2 hardened steel (58-62 HRC) in end milling operation using TiAlN/AlCrN multilayer coated carbide. Surface roughness (Ra) was examined at different cutting speed (v) and radial depth of cut (dr) while the measurement was taken in feed speed, Vf and cutting speed, Vc directions. The experimental results show that the milled surface is anisotropic in nature. Surface roughness values in feed speed direction do not appear to correspond to any definite pattern in relation to cutting speed, while it increases with radial depth-of-cut within the range 0.13-0.24 µm. In cutting speed direction, surface roughness value decreases in the high speed range, while it increases in the high radial depth of cut. Radial depth of cut is the most influencing parameter in surface roughness followed by cutting speed.


1996 ◽  
Vol 118 (2) ◽  
pp. 178-187 ◽  
Author(s):  
E. D. Tung ◽  
M. Tomizuka ◽  
Y. Urushisaki

Experiments are performed for end milling aluminum at 15,000 RPM spindle speed (1,508 m/min cutting speed) and up to 3 m/min table feedrate using an experimental machine tool control system. A digital feedforward controller for feed drive control incorporates the Zero Phase Error Tracking Controller (ZPETC) and feedforward friction compensation. The controller achieves near-perfect (±3 μm) tracking over a 26 mm trajectory with a maximum speed of 2 m/min. The maximum contouring error for a 26 mm diameter circle at this speed is less than 4 μm. Tracking and contouring experiments are conducted for table feedrates as high as 10 m/min. Frequency domain analysis demonstrates that the feedforward controller achieves a bandwidth of 10 Hz without phase distortion. In a direct comparison of accuracy, the machining errors in specimens produced by the experimental controller were up to 20 times smaller than the errors in specimens machined by an industrial CNC.


2009 ◽  
Vol 209 (5) ◽  
pp. 2585-2591 ◽  
Author(s):  
W.X. Tang ◽  
Q.H. Song ◽  
S.Q. Yu ◽  
S.S. Sun ◽  
B.B. Li ◽  
...  

2012 ◽  
Vol 576 ◽  
pp. 41-45
Author(s):  
A.K.M. Nurul Amin ◽  
M.A. Mahmud ◽  
M.D. Arif

The majority of semiconductor devices are made up of silicon wafers. Manufacturing of high-quality silicon wafers includes numerous machining processes, including end milling. In order to end mill silicon to a nano-meteric surface finish, it is crucial to determine the effect of machining parameters, which influence the machining transition from brittle to ductile mode. Thus, this paper presents a novel experimental technique to study the effects of machining parameters in high speed end milling of silicon. The application of compressed air, in order to blow away the chips formed, is also investigated. The machining parameters’ ranges which facilitate the transition from brittle to ductile mode cutting as well as enable the attainment of high quality surface finish and integrity are identified. Mathematical model of the response parameter, the average surface roughness (Ra) is subsequently developed using RSM in terms of the machining parameters. The model was determined, by Analysis of Variance (ANOVA), to have a confidence level of 95%. The experimental results show that the developed mathematical model can effectively describe the performance indicators within the controlled limits of the factors that are being considered.


2010 ◽  
Vol 118 (1383) ◽  
pp. 1053-1056 ◽  
Author(s):  
Seok-Jae HA ◽  
Bong-Cheol SHIN ◽  
Myeong-Woo CHO ◽  
Ki-Ju LEE ◽  
Won-Seung CHO

Sign in / Sign up

Export Citation Format

Share Document