Notch wear prediction model in high speed milling of AerMet100 steel with bull-nose tool considering the influence of stress concentration

Wear ◽  
2018 ◽  
Vol 408-409 ◽  
pp. 228-237 ◽  
Author(s):  
Haohao Zeng ◽  
Rong Yan ◽  
Pengle Du ◽  
Mingkai Zhang ◽  
Fangyu Peng
Keyword(s):  
Stress Concentration ◽  
Prediction Model ◽  
High Speed ◽  
Wear Prediction ◽  
High Speed Milling ◽  
Notch Wear

Vibration Analysis of High-Speed End Milling Operations Applied to Injection Mold Materials

2017 ◽  
Author(s):  
Andris Logins ◽  
Toms Torims ◽  
Pedro Rosado Castellano ◽  
Santiago Gutiérrez ◽  
Rafael Torres
Keyword(s):  
Prediction Model ◽  
Surface Topography ◽  
High Speed ◽  
End Milling ◽  
Dynamical Behavior ◽  
Milling Process ◽  
Injection Mold ◽  
High Speed Milling ◽  
3D Surface Topography ◽  
End Milling Process

High-speed milling has often been applied in injection mold manufacturing processes, where surface roughness is a significant criterion in product quality demands. It is equally applicable to automotive or industrial engineering and to toy manufacturing, where plastic parts with a high-quality surface finish have been processed using the injection molding technique. High-speed milling involves a number of process parameters that may affect the 3D surface topography formation. Literature analysis reveals that dynamical behavior is a significant factor in the end milling process on surface roughness parameters. To improve the accuracy of predicted surface topography models, it is important to include the dynamical behavior of milling factor. This paper describes the surface prediction model of combined end-milling geometrical and dynamical interaction models. The natural frequency of machine assembly and forced vibrations during the cutting process were measured during the flat-end milling process. Unevenly distributed cutting marks were revealed by surface 3D topography images and microscopy images of the machined samples. A mathematical model to predict surface topography was developed, including dynamical behavior and cutting geometries. Machine accuracy also has to be addressed. 3D surface topography parameters from the experimental sample provided the results for the mathematical prediction model. This model offers a software tool for manufacturers to improve the quality of machined part surfaces, taking into account the behavioral properties of their machining equipment. Relevant conclusions about the manufacturing equipment accuracy have been drawn. Vibrations in the milling system affect the cutting process and contribute to the surface topography prediction model. Local cutting tool vibrations do not have any influence on surface parameter mean values.

Wear behavior of tool flank in the side milling of Ti6Al4V: An analytical model and experimental validation

2021 ◽  
pp. 095440622110230
Author(s):  
Caixu Yue ◽  
Xiaochen Li ◽  
Xianli Liu ◽  
Jianbiao Du ◽  
Steven Y. Liang ◽  
...  
Keyword(s):  
Prediction Model ◽  
High Speed ◽  
Flank Wear ◽  
Wear Behavior ◽  
Cutting Parameters ◽  
Tool Geometry ◽  
End Mill ◽  
Wear Prediction ◽  
Side Milling ◽  
Temperature Field Model

Due to the poor machinability of Ti6Al4V material, the cutting tool can easily suffer flank wear during the process of high-speed side milling, which reduces the tool life as well as the surface integrity of workpiece. Further, an effective method for predicting the flank wear of end mill during side milling of Ti6Al4V is lacking in the existing literature, which makes it difficult to improve the productivity of the overall process. To this end, in this study, a flank wear prediction model is constructed based on three main mechanisms: abrasive wear, adhesive wear, and diffusive wear. Subsequently, a normal stress model and temperature field model of wear land on the flank of end mill are established. Finally, these two models are incorporated in the flank wear model to obtain the variation rate of wear land width, which is regarded as a criterion to evaluate the reliability of the proposed flank wear prediction model of side mill. The prediction results are found to be in excellent agreement with the experimental results, which verifies the high prediction accuracy of the proposed model. Overall, this model can serve as a useful theoretical basis for the rational selection of tool geometry and cutting parameters.

Notch wear prediction model in turning of Inconel 718 with ceramic tools considering the influence of work hardened layer

Wear ◽  
2014 ◽  
Vol 313 (1-2) ◽  
pp. 63-74 ◽  
Author(s):  
Kejia Zhuang ◽  
Dahu Zhu ◽  
Xiaoming Zhang ◽  
Han Ding
Keyword(s):  
Prediction Model ◽  
Inconel 718 ◽  
Hardened Layer ◽  
Wear Prediction ◽  
Ceramic Tools ◽  
Notch Wear

A Study of Cutting Parameters Optimization in High-Speed Milling GH4169 with TiAlN Coated Carbide Tool

2012 ◽  
Vol 628 ◽  
pp. 144-149
Author(s):  
Wei Wei Liu ◽  
Yuan Yu ◽  
Feng Li ◽  
Chang Feng Yao ◽  
Bin Liu
Keyword(s):  
Surface Roughness ◽  
Prediction Model ◽  
High Speed ◽  
Optimal Parameter ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Parameters Optimization ◽  
High Speed Milling ◽  
Cutting Parameters Optimization ◽  
Coated Carbide

The orthogonal experiment is processed for high-speed milling superalloy GH4169 with TiAlN coated carbide inserts. The surface roughness prediction model based on cutting parameters is established by using the least-squares regression method. And the effect of cutting parameters on surface roughness is studied. According to the prediction model of surface roughness, a model of cutting parameters optimization by using genetic algorithm based on annealing penalty function is established for maximum material removal rate under specified surface roughness values. Obtain the optimal parameter combination when the surface roughness Ra≤0.2µm, and the experimental validation is done. These results provide the basis for improving processing efficiency of processing GH4169 and choosing parameters under specified constraint conditions.

Cutting Temperature and Cutting Forces Investigation Based on the Taguchi Design Method when High-Speed Milling of Titanium Matrix Composites with PCD Tool

2016 ◽  
Vol 836-837 ◽  
pp. 168-174 ◽  
Author(s):  
Ying Fei Ge ◽  
Hai Xiang Huan ◽  
Jiu Hua Xu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
High Speed ◽  
Volume Fraction ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Speed Milling ◽  
Radial Depth

High-speed milling tests were performed on vol. (5%-8%) TiCp/TC4 composite in the speed range of 50-250 m/min using PCD tools to nvestigate the cutting temperature and the cutting forces. The results showed that radial depth of cut and cutting speed were the two significant influences that affected the cutting forces based on the Taguchi prediction. Increasing radial depth of cut and feed rate will increase the cutting force while increasing cutting speed will decrease the cutting force. Cutting force increased less than 5% when the reinforcement volume fraction in the composites increased from 0% to 8%. Radial depth of cut was the only significant influence factor on the cutting temperature. Cutting temperature increased with the increasing radial depth of cut, feed rate or cutting speed. The cutting temperature for the titanium composites was 40-90 °C higher than that for the TC4 matrix. However, the cutting temperature decreased by 4% when the reinforcement's volume fraction increased from 5% to 8%.

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