Cutting force reduction and surface quality improvement in machining of aerospace duralumin AL-2017-T4 using carbon onion nanolubrication system

2012 ◽  
Vol 65 (9-12) ◽  
pp. 1493-1500 ◽  
Author(s):  
M. Sayuti ◽  
Ahmed A. D. Sarhan ◽  
Tomohisa Tanaka ◽  
M. Hamdi ◽  
Yoshio Saito
Keyword(s):  
Quality Improvement ◽  
Cutting Force ◽  
Surface Quality ◽  
Carbon Onion ◽  
Force Reduction

Concrete Surface Quality Improvement Technique Using Highly Water Repellent Sealing Method

2016 ◽  
Vol 54 (11) ◽  
pp. 1105-1110
Author(s):  
K. Watanabe ◽  
G. Sakai ◽  
N. Sakata ◽  
T. Ishida
Keyword(s):  
Quality Improvement ◽  
Surface Quality ◽  
Concrete Surface ◽  
Water Repellent

scholarly journals Influence of tool edge form factor and cutting parameters on milling performance

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110090
Author(s):  
Xuefeng Zhao ◽  
Hao Qin ◽  
Zhiguo Feng
Keyword(s):  
Form Factor ◽  
Simulation Model ◽  
Cutting Force ◽  
Surface Quality ◽  
High Speed ◽  
Orthogonal Cutting ◽  
Cutting Temperature ◽  
Tool Edge ◽  
Drag Finishing ◽  
Edge Preparation

Tool edge preparation can improve the tool life, as well as cutting performance and machined surface quality, meeting the requirements of high-speed and high-efficiency cutting. In general, prepared tool edges could be divided into symmetric or asymmetric edges. In the present study, the cemented carbide tools were initially edge prepared through drag finishing. The simulation model of the carbide cemented tool milling steel was established through Deform software. Effects of edge form factor, spindle speed, feed per tooth, axial, and radial cutting depth on the cutting force, the tool wear, the cutting temperature, and the surface quality were investigated through the orthogonal cutting simulation. The simulated cutting force results were compared to the results obtained from the orthogonal milling experiment through the dynamometer Kistler, which verified the simulation model correctness. The obtained results provided a basis for edge preparation effect along with high-speed and high effective cutting machining comprehension.

scholarly journals Surface quality improvement and adjustment of SLM-processed CM247LC samples by modulated laser parameters

Procedia CIRP ◽  
2020 ◽  
Vol 95 ◽  
pp. 109-114
Author(s):  
M. Gerstgrasser ◽  
M. Cloots ◽  
K. Wegener
Keyword(s):  
Quality Improvement ◽  
Surface Quality ◽  
Laser Parameters

scholarly journals The Comparative Study on Cutting Performance of Different-Structure Milling Cutters in Machining CFRP

2018 ◽  
Vol 8 (8) ◽  
pp. 1353
Author(s):  
Tao Chen ◽  
Fei Gao ◽  
Suyan Li ◽  
Xianli Liu
Keyword(s):  
Carbon Fiber ◽  
Cutting Force ◽  
Surface Quality ◽  
Cutting Edge ◽  
Cutting Performance ◽  
Machining Process ◽  
Carbon Fiber Composites ◽  
Machined Surface ◽  
Milling Cutter ◽  
Machined Surface Quality

Carbon fiber reinforced plastic (CFRP) is typically hard to process, because it is easy for it to generate processing damage such as burrs, tears, delamination, and so on in the machining process. Consequently, this restricts its wide spread application. This paper conducted a comparative experiment on the cutting performance of the two different-structure milling cutters, with a helical staggered edge and a rhombic edge, in milling carbon fiber composites; analyzed the wear morphologies of the two cutting tools; and thus acquired the effect of the tool structure on the machined surface quality and cutting force. The results indicated that in the whole cutting, the rhombic milling cutter with a segmented cutting edge showed better wear resistance and a more stable machined surface quality. It was not until a large area of coating shedding occurred, along with chip clogging, that the surface quality decreased significantly. At the stage of coating wear, the helical staggered milling cutter with an alternately arranged continuous cutting edge showed better machined surface quality, but when the coating fell off, its machined surface quality began to reveal damage such as groove, tear, and fiber pullout. Meanwhile, burrs occurred at the edge and the cutting force obviously increased. By contrast, for the rhombic milling cutter, both the surface roughness and cutting force increased relatively slowly.

scholarly journals Performance of Volcano-Like Laser Textured Cutting Tools: An Experimental and Simulative Investigation

Lubricants ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 98 ◽  
Author(s):  
Zhengyang Kang ◽  
Yonghong Fu ◽  
Xingyu Fu ◽  
Martin Jun
Keyword(s):  
Cutting Force ◽  
Cutting Tools ◽  
Surface Texturing ◽  
Temperature Fields ◽  
Small Scale ◽  
Rake Face ◽  
Forming Process ◽  
Force Reduction ◽  
And Performance ◽  
Distribution Of Stress

In recent years, surface texturing in micro-scale has been attempted on the surface of cutting tools for multiple purposes, e.g., cutting force reduction, prolonging life-span, anti-adhesion, etc. With respect to machinability and performance, micro-groove texture (MGT) has dominated in this field compared to other textured patterns. In this study, a novel volcano-like texture (VLT) was fabricated on the rake face of cemented carbide inserts (WC-Co, YG6) by fiber laser. The following cutting experiment tested the flat, MGT and VLT tools in turning aluminum alloy 6061. The effects of coolant and cutting conditions were investigated. In addition, a validated FEM model was employed to explore the distribution of stress and temperature fields in the tool-chip interface. The initial forming process of adhesion layer on rake face was investigated as well. The results indicated that lower cutting force and less adhesion can be achieved by small scale VLT. This study not only introduced VLT on cutting tools but also revealed its comprehensive performance.

Study on the cutting performance in machining assembled hardened steel workpiece with torus cutter

2019 ◽  
Vol 234 (4) ◽  
pp. 701-709
Author(s):  
Tao Chen ◽  
Weijie Gao ◽  
Guangyue Wang ◽  
Xianli Liu
Keyword(s):  
Tool Wear ◽  
Cutting Force ◽  
Surface Quality ◽  
Wear Mechanism ◽  
Hardened Steel ◽  
Cutting Performance ◽  
Machining Process ◽  
Machined Surface ◽  
Machined Surface Quality ◽  
Two Sides

Torus cutters are increasingly used in machining high-hardness materials because of high processing efficiency. However, due to the large hardness variation in assembled hardened steel workpiece, the tool wear occurs easily in machining process. This severely affects the machined surface quality. Here, we conduct a research on the tool wear and the machined surface quality in milling assembled hardened steel mold with a torus cutter. The experimental results show the abrasive wear mechanism dominates the initial tool wear stage of the torus cutter. As the tool wear intensifies, the adhesive wear gradually occurs due to the effect of alternating stress and impact load. Thus, the mixing effect of the abrasive and adhesive wears further accelerates tool wear, resulting in occurrence of obvious crater wear band on the rake face and coating tearing area on the flank face. Finally, the cutter is damaged by the fatigue wear mechanism, reducing seriously the cutting performance. With increase of flank wear, moreover, there are increasingly obvious differences in both the surface morphology and the cutting force at the two sides of the joint seam of the assembled hardened steel parts, including larger height difference at the two sides of the joint seam and sudden change of cutting force, as a result, leading to decreasing cutting stability and deteriorating seriously machined surface quality.

An intelligent prediction model of the tool wear based on machine learning in turning high strength steel

2020 ◽  
Vol 234 (13) ◽  
pp. 1580-1597
Author(s):  
Minghui Cheng ◽  
Li Jiao ◽  
Xuechun Shi ◽  
Xibin Wang ◽  
Pei Yan ◽  
...  
Keyword(s):  
Tool Wear ◽  
Prediction Model ◽  
Cutting Force ◽  
Surface Quality ◽  
Surface Texture ◽  
High Strength Steel ◽  
Prediction Models ◽  
High Strength ◽  
Support Vector ◽  
Time Frequency

In the process of high strength steel turning, tool wear will reduce the surface quality of the workpiece and increase cutting force and cutting temperature. To obtain the fine surface quality and avoid unnecessary loss, it is necessary to monitor the state of tool wear in the dry turning. In this article, the cutting force, vibration signal and surface texture of the machined surface were collected by tool condition monitoring system and signal processing techniques are being used for extracting the time-domain, frequency-domain and time-frequency features of cutting force and vibration. The gray level processing technique is used to extract the features of the gray co-occurrence matrix of the surface texture and found that these features changed simultaneously when the cutting tool broke. After this, an intelligent prediction model of tool wear was built using the support vector regression (SVR) whose kernel function parameters were optimized by the grid search algorithm (GS), the genetic algorithm (GA) and the particle swarm optimization algorithm respectively. The features extracted from the signals and surface texture are used to train the prediction model in MATLAB. It was found that after the surface texture features were fused using the intelligent prediction model on the basis of the features of cutting force and vibration, prediction accuracy of the proposed method is found as 97.32% and 96.72% respectively under the two prediction models of GA-SVR and GS-SVR. Moreover, the intelligent prediction model can not only predict the tool wear under different cutting conditions, but also the different wear stages in a single wear cycle and the absolute error between the predicted value and the actual value is less than 10 μm, the confidence coefficient of prediction curve is around 0.99.

Sign in / Sign up

Export Citation Format

Share Document