CAVIJET Coal-cutting parameters

2009 ◽  
pp. 562-562-20
Author(s):  
AF Conn ◽  
SL Rudy
Keyword(s):  
Cutting Parameters ◽  
Coal Cutting

scholarly journals Discrete Element Simulation of Conical Pick’s Coal Cutting Process under Different Cutting Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jinxia Liu ◽  
Chao Ma ◽  
Qingliang Zeng ◽  
Kuidong Gao
Keyword(s):  
Angular Velocity ◽  
Cutting Force ◽  
Cutting Parameters ◽  
Discrete Element ◽  
Cutting Process ◽  
Conical Pick ◽  
Force Fluctuation ◽  
Installation Angle ◽  
Coal Cutting ◽  
Coal Particles

To explore how the cutting parameters affect the conical pick’s cutting force in coal cutting process, some simulation tests were carried with EDEM based on analysis of coal cutting process of conical pick and micro mechanical characteristic of coal particles. In this paper, traction speed, drum angular velocity, and installation angle of conical pick were considered as the main coal cutting parameters. The discrete element simulations were conducted under 7 sets of various cutting parameters, which were determined in the range of empirical parameters. From the results of the simulation tests, it can be concluded that the fragmentation of coal particles appears in a compacted, squeezed, and crumbling state in coal cutting process; the traction speed has the greatest impact on the conical pick’s cutting force and cutting force fluctuation and the influence of drum angular velocity and installation angle reduce in turn; the force and force fluctuation tend to decrease and obviously increase, respectively, with the increase of drum angular velocity and traction speed; and they will reach the minimum when the pick’s installation angle is 45° under certain traction speed and drum angular velocity.

scholarly journals Research of Response Difference on Coal Cutting Load under Different Cutting Parameters

2019 ◽  
pp. 420-429
Author(s):  
Lirong Wan ◽  
Kao Jiang ◽  
Kuidong Gao ◽  
Qingliang Zeng ◽  
Xin Zhang
Keyword(s):  
Cutting Parameters ◽  
Coal Cutting

An Investigation of the Mechanics and Noise Associated with Coal Cutting

1981 ◽  
Vol 103 (3) ◽  
pp. 257-269 ◽  
Author(s):  
R. S. Becker ◽  
G. R. Anderson ◽  
J. Kovac
Keyword(s):  
Underground Mining ◽  
Cutting Tools ◽  
Health And Safety ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Analytical Models ◽  
Mining Machine ◽  
Cutting Mechanics ◽  
Coal Cutting ◽  
Continuous Mining

The results of a laboratory investigation of coal cutting mechanics and noise are presented. These experiments were performed using a linear cutting apparatus that operates over a broad cutting speed range. The influence of several coal cutting parameters on the noise, force, productivity, and specific energy associated with linear cuts was ascertained. Some basic theoretical aspects of coal cutting mechanics and noise generation are discussed, and the results of the laboratory experiments are used to formulate analytical models of the coal cutting forces and noise. The analytical model for coal cutting noise is then generalized to account for the more important effects of rotary cutting. Based on the generalized model, an estimate of the sound pressure level at an operator’s position is made for a typical continuous mining machine. It is concluded that by employing linear rather than rotary cuts, using deeper depths of cut, slower cutting speeds, and more efficient cutting tools, it is possible to reduce the level of coal cutting noise, as well as provide benefits to other important areas of health and safety in underground mining.

Optimization of Cutting Parameters Considering Surface Roughness When Milling AISI 304 Steel Using Coated Wc-Co and Tialn / Wc-Co Coated

2019 ◽  
Author(s):  
Murilo Pereira Lopes ◽  
Jose Rubens Gonçalves Carneiro ◽  
Gilmar Cordeiro da Silva ◽  
Carlos Eduardo Santos ◽  
Ítalo Bruno dos Santos
Keyword(s):  
Surface Roughness ◽  
Cutting Parameters ◽  
Aisi 304 ◽  
Aisi 304 Steel ◽  
Optimization Of Cutting Parameters

Studying The Effect of a New Mixed Cutting Fluid on Surface Roughness

2020 ◽  
Vol 38 (11A) ◽  
pp. 1593-1601
Author(s):  
Mohammed H. Shaker ◽  
Salah K. Jawad ◽  
Maan A. Tawfiq
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Machining Processes ◽  
Dry Cutting ◽  
Cutting Speeds

This research studied the influence of cutting fluids and cutting parameters on the surface roughness for stainless steel worked by turning machine in dry and wet cutting cases. The work was done with different cutting speeds, and feed rates with a fixed depth of cutting. During the machining process, heat was generated and effects of higher surface roughness of work material. In this study, the effects of some cutting fluids, and dry cutting on surface roughness have been examined in turning of AISI316 stainless steel material. Sodium Lauryl Ether Sulfate (SLES) instead of other soluble oils has been used and compared to dry machining processes. Experiments have been performed at four cutting speeds (60, 95, 155, 240) m/min, feed rates (0.065, 0.08, 0.096, 0.114) mm/rev. and constant depth of cut (0.5) mm. The amount of decrease in Ra after the used suggested mixture arrived at (0.21µm), while Ra exceeded (1µm) in case of soluble oils This means the suggested mixture gave the best results of lubricating properties than other cases.

Prediction of Surface Roughness and Optimization of Cutting Parameters in CNC Turning of Rotational Features

2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Non Linear ◽  
Optimization Of Cutting Parameters

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

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