Acoustic Emission from the Face Milling Process—the Effects of Process Variables

1987 ◽  
Vol 109 (2) ◽  
pp. 92-99 ◽  
Author(s):  
E. N. Diei ◽  
D. A. Dornfeld
Keyword(s):  
Acoustic Emission ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Face Milling ◽  
Vertical Milling ◽  
The Face ◽  
Vertical Milling Machine ◽  
Ae Signal ◽  
Engagement And Disengagement

This study investigates the nature of the acoustic emission (AE) signal generated during single and multitooth face milling of steel. For this purpose, cutting tests were conducted on a vertical milling machine to determine the effects of cutting parameters, especially the angle of tool engagement and disengagement, the varying chip thickness, and the number of engaged teeth. The results show good correlation between the rms AE signal and the severity of the contact conditions during chip formation and at tool entry and exit. Cutting forces were also measured and a qualitative correlation between the specific AE rms voltage and the specific cutting force is seen.

Specifics of Wear of Ceramic Cutting Tool Inserts Featuring Al2O3-TiC Dies when Face Milling Hardened Cast Iron

2016 ◽  
Vol 876 ◽  
pp. 43-49 ◽  
Author(s):  
Ramon Torrecillas San Millan ◽  
Anton Evgenievich Seleznev ◽  
Vladimir Dmitrievich Gurin ◽  
Pavel Yurievich Peretyagin
Keyword(s):  
Cast Iron ◽  
Cutting Parameters ◽  
Milling Process ◽  
Face Milling ◽  
Wide Range ◽  
The Face ◽  
Mixed Ceramics ◽  
Surface Transformation ◽  
Hardened Cast ◽  
Fine Milling

This work studies wear kinetics of index able inserts (II) made of mixed ceramics based on Russian-manufactured in case of fine milling of special hardened cast iron with globular graphite. In a wide range of cutting parameters typical for fine milling, an impact of tool insert wearing parameters on qualitative and quantitative characteristics of the cutting process have been studied. Morphological traits and nature of wear of work surfaces has been studied using optical and scanning electron microscopy. Criteria of II states, as well as specifics of contact work surface transformation, correlating with force parameters of the face milling process, have been determined.

scholarly journals Research and Optimization of Surface Roughness in Milling of SLM Semi-Finished Parts Manufactured by Using the Different Laser Scanning Speed

Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 9 ◽  
Author(s):  
Andrzej Matras
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Laser Scanning ◽  
Cutting Tool ◽  
Scanning Speed ◽  
Milling Process ◽  
Face Milling ◽  
Machining Parameters ◽  
The Face ◽  
Laser Scanning Speed

The paper studies the potential to improve the surface roughness in parts manufactured in the Selective Laser Melting (SLM) process by using additional milling. The studied process was machining of samples made of the AlSi10Mg alloy powder. The simultaneous impacts of the laser scanning speed of the SLM process and the machining parameters of the milling process (such as the feed rate and milling width) on the surface roughness were analyzed. A mathematical model was created as a basis for optimizing the parameters of the studied processes and for selecting the sets of optimum solutions. As a result of the research, surface with low roughness (Ra = 0.14 μm, Rz = 1.1 μm) was obtained after the face milling. The performed milling allowed to reduce more than 20-fold the roughness of the SLM sample surfaces. The feed rate and the cutting width increase resulted in the surface roughness deterioration. Some milled surfaces were damaged by the chip adjoining to the rake face of the cutting tool back tooth.

Acoustic Emission Sensing of Tool Wear in Face Milling

1987 ◽  
Vol 109 (3) ◽  
pp. 234-240 ◽  
Author(s):  
E. N. Diei ◽  
D. A. Dornfeld
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Cutting Forces ◽  
Flank Wear ◽  
Face Milling ◽  
Processing Scheme ◽  
Acoustic Emission Sensing ◽  
Vertical Milling Machine ◽  
Time Domain Averaging ◽  
Ae Signals

Acoustic Emission (AE) signal analysis was applied to on-line sensing of tool wear in face milling. Cutting tests were conducted on a vertical milling machine. AE signals, feed and normal components of cutting force and flank wear were measured and compared. A signal processing scheme for intermittent cutting forces and AE signals, based on the concept of time domain averaging (TDA) is proposed. The results indicate that both AE and cutting forces have parameters that correlate closely with flank wear.

scholarly journals FPGA Based Real Time Simulations of the Face Milling Process

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 215987-216002
Author(s):  
Michal R. Mazur ◽  
Marek A. Galewski ◽  
Krzysztof J. Kalinski
Keyword(s):  
Real Time ◽  
Milling Process ◽  
Face Milling ◽  
The Face ◽  
Real Time Simulations

scholarly journals Analysis of the Face Milling Process Based on the Imitation Modelling

2016 ◽  
Vol 126 ◽  
pp. 012001 ◽  
Author(s):  
V A Khomenko ◽  
A O Cherdancev ◽  
P O Cherdancev ◽  
V D Goncharov ◽  
A Kulawik
Keyword(s):  
Milling Process ◽  
Face Milling ◽  
The Face

Assessment of Tool Wear in Milling Using Acoustic Emission Detected by a Fiber-Optic Interferometer

1996 ◽  
Vol 118 (3) ◽  
pp. 428-433 ◽  
Author(s):  
T. A. Carolan ◽  
D. P. Hand ◽  
J. S. Barton ◽  
J. D. C. Jones ◽  
P. Wilkinson ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Fiber Optic ◽  
Cutting Tools ◽  
Piezoelectric Sensor ◽  
Absolute Calibration ◽  
Limited Bandwidth ◽  
The Face ◽  
Ae Signal ◽  
Fiber Optic Interferometer

Acoustic emission (AE) has previously been shown to be a useful technique in monitoring the state of wear of cutting tools. The piezo-electric transducers conventionally used for AE detection are contacting devices with a limited bandwidth. This paper describes the use of a robust fiber optic interferometer for the in-process measurement of AE during the face milling of annealed En24 steel to provide tool wear information via analysis of the rms AE signal. The interferometer displayed an improved diagnostic capability over a conventional piezoelectric sensor due to its advantages of being non-contacting, broadband with a flat frequency response to displacement, and providing absolute calibration.

Prediction of Surface Roughness Profiles for Milling Process with Fractal Parameters Based on LS-SVM

2010 ◽  
Vol 97-101 ◽  
pp. 1186-1193 ◽  
Author(s):  
Ben Gan ◽  
Yi Jian Huang ◽  
Gui Xia Zheng
Keyword(s):  
Surface Roughness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Face Milling ◽  
Cutting Conditions ◽  
Vertical Scaling ◽  
Support Vector ◽  
Fractal Function ◽  
Milling Operations ◽  
Fractal Parameters

Least squares support vector machines (LS-SVM) were developed for the analysis and prediction of the relationship between the cutting conditions and the corresponding fractal parameters of machined surfaces in face milling operation. These models can help manufacturers to determine the appropriate cutting conditions, in order to achieve specific surface roughness profile geometry, and hence achieve the desired tribological performance (e.g. friction and wear) between the contacting surfaces. The input parameters of the LS-SVM are the cutting parameters: rotational speed, feed, depth of milling. The output parameters of the LS-SVM are the corresponding calculated fractal parameters: fractal dimension D and vertical scaling parameter G. The LS-SVM were utilized successfully for training and predicting the fractal parameters D and G in face milling operations. Moreover, Weierstrass-Mandelbrot（W–M ）fractal function was integrated with the LS-SVM in order to generate an artificially fractal predicted profiles at different milling conditions. The predicted profiles were found statistically similar to the actual measured profiles of test specimens and there is a relationship between the scale-independent fractal coefficients(D and G).

scholarly journals Influence of the cutting parameters on the selected machinability indicators in the milling of steel EZ6NCT25

Mechanik ◽  
2018 ◽  
Vol 91 (8-9) ◽  
pp. 772-774
Author(s):  
Agnieszka Skoczylas ◽  
Kazimierz Zaleski
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Turbine Blades ◽  
Experimental Tests ◽  
Cutting Parameters ◽  
Face Milling ◽  
Steel Grade ◽  
Technological Parameters ◽  
The Face ◽  
D 12

The paper reports results of an investigation of the cutting torque and surface roughness in the face milling of EZ6NCT25 steel. Classified as stainless steel, EZ6NCT25 is effectively used in the aviation and shipbuilding industries. This steel grade is used for producing elements such as turbine blades and combustion chamber assemblies. Experimental tests were performed with the use of full-carbide monolithic tools with the diameter of d = 12 mm. The tests were conducted at variable technological parameters. It has been observed that that cutting torque and amplitude cutting torque depend on machining conditions, and also, although to a lesser extent the surface roughness.

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