Operational Cutting Force Identification in End Milling Using Inverse Technique to Predict the Fatigue Tool Life

2020 ◽  
Author(s):  
Ratan A. Patil ◽  
Shrinivas L. Gombi
Keyword(s):  
Cutting Force ◽  
Tool Life ◽  
End Milling ◽  
Inverse Technique ◽  
Force Identification

scholarly journals Multi Objective Optimization of Machining Parameters in End Milling of AISI1020

2021 ◽  
Vol 10 (8) ◽  
pp. 54-63
Author(s):  
Jignesh G Parmar ◽  
Komal G Dave
Keyword(s):  
Cutting Force ◽  
Tool Life ◽  
End Milling ◽  
Experimental Results ◽  
Multi Objective Optimization ◽  
Machining Time ◽  
Multi Objective ◽  
Average Accuracy ◽  
Milling Operation ◽  
Predicted Values

In current research, artificial neural network (ANN) and Multi objective genetic algorithm (MOGA) have been used for the prediction and multi objective optimization of the end milling operation. Cutting speed, feed rate, depth of cut, material density and hardness have been considered as input variables. The predicted values and optimized results obtained through ANN and MOGA are compared with experimental results. A good correlation has been established between the ANN predicted values and experimental results with an average accuracy of 91.983% for material removal rate, 99.894% for tool life, 92.683% for machining time, 92.671% for tangential cutting force, 92.109% for power and 90.311% for torque. The MOGA approach has been proposed to obtain the cutting condition for optimization of each responses. The MOGA gives average accuracy of 96.801% for MRR, 99.653% for tool life, 86.833% for machining time, 93.74% for cutting force, 93.74% for power and 99.473% for torque. It concludes that ANN and MOGA are efficiently and effectively used for prediction and multi objective optimization of end milling operation for any selected materials before the experimental. Implementation of these techniques in industries before the experimentation is useful to reduce the lead time, experimental cost and power consumption also increase the productivity of the product.

Investigation on the Tool Wear Model and Equivalent Tool Life in End Milling Titanium Alloy Ti6Al4V

2018 ◽  
Author(s):  
Kai Guo ◽  
Bin Yang ◽  
Jie Sun ◽  
Vinothkumar Sivalingam
Keyword(s):  
Tool Wear ◽  
Titanium Alloys ◽  
Tool Life ◽  
End Milling ◽  
Cutting Speed ◽  
Carbide Tool ◽  
Wear Model ◽  
Wear Process ◽  
Coated Carbide Tool ◽  
Coated Carbide

Titanium alloys are widely utilized in aerospace thanks to their excellent combination of high-specific strength, fracture, corrosion resistance characteristics, etc. However, titanium alloys are difficult-to-machine materials. Tool wear is thus of great importance to understand and quantitatively predict tool life. In this study, the wear of coated carbide tool in milling Ti-6Al-4V alloy was assessed by characterization of the worn tool cutting edge. Furthermore, a tool wear model for end milling cutter is established with considering the joint effect of cutting speed and feed rate for characterizing tool wear process and predicting tool wear. Based on the proposed tool wear model equivalent tool life is put forward to evaluate cutting tool life under different cutting conditions. The modelling process of tool wear is given and discussed according to the specific conditions. Experimental work and validation are performed for coated carbide tool milling Ti-6Al-4V alloy.

FRACTAL-BASED ANALYSIS OF THE VARIATIONS OF CUTTING FORCES ALONG DIFFERENT AXES IN END MILLING OPERATION

Fractals ◽  
2018 ◽  
Vol 26 (06) ◽  
pp. 1850089 ◽  
Author(s):  
HAMIDREZA NAMAZI ◽  
ALI AKHAVAN FARID ◽  
TECK SENG CHANG
Keyword(s):  
Fractal Dimension ◽  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Fractal Theory ◽  
Radial Force ◽  
Machining Conditions ◽  
Feed Force ◽  
Milling Operation ◽  
Force Signal

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.

Tool life model for end milling steel (190 BHN)

1997 ◽  
Vol 68 (1) ◽  
pp. 50-59 ◽  
Author(s):  
M. Alauddin ◽  
M.A. El Baradie
Keyword(s):  
Tool Life ◽  
End Milling ◽  
Life Model

scholarly journals Influence of Ultrasonic Vibration-Assisted Ball-End Milling on the Cutting Performance of AZ31B Magnesium Alloy

2020 ◽  
Vol 9 (4) ◽  
pp. 271-276
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Ultrasonic Vibration ◽  
Biomedical Applications ◽  
End Milling ◽  
Cutting Temperature ◽  
Cutting Performance ◽  
Machining Process ◽  
Dry Conditions ◽  
Good Biocompatibility

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.

Sign in / Sign up

Export Citation Format

Share Document