An Experimental Investigation of the Cutting Force in High Speed Ball-End Rough Milling of Cr12MoV

2012 ◽  
Vol 426 ◽  
pp. 193-196
Author(s):  
Zi Ye Liu ◽  
Chuan Zhen Huang ◽  
Xin Qiang Zhuang ◽  
Bin Zou ◽  
Han Lian Liu ◽  
...  
Keyword(s):  
Cutting Force ◽  
High Speed ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Wave Form ◽  
Range Analysis ◽  
Cutting Force Components ◽  
Rough Milling ◽  
Force Components

An orthogonal test was carried out so as to analyze the cutting force in high speed rough milling with ball-end cutting tools. The wave form of the cutting force components was analyzed. The range analysis was performed to investigate the effect of cutting parameters on the cutting force. The analysis results show that the depth of cut and feed rate have the most significant effect on the resultant force. An empirical equation to describe the resultant cutting force was developed.

Cutting Performance of Diamond Coated, TiAlN Coated and Carbide Cutting Tools in High Speed Milling Graphite

2014 ◽  
Vol 800-801 ◽  
pp. 451-459
Author(s):  
Yu Hai Zhou ◽  
Cheng Yong Wang ◽  
Qi Ming Wang
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
High Speed ◽  
Orthogonal Experiment ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Cutting Performance ◽  
Depth Of Cut ◽  
High Speed Milling ◽  
Radial Depth

This paper focusing on cutting performance high speed milling Electrical Discharging Machining (EDM) graphite with diamond coated、Carbide (WC) and TiAlN coated cutting Tools. tools wear, cutting force and machined surface had been researched. Experiment study including cutting speed, feed rate per tooth, radial depth of cut, axial depth of cut, and material of tools factors effects on the cutting forces. Cutting parameters are optimized based on the orthogonal experiment. Experiment in high speed milling with diamond coated tools all comparison with TiAlN coated and Carbide (WC) tools. On the surface quality, cutting forces and tool wear influence graphite cutting tool materials research, process parameters, tool design and optimization of processing parameters to provide supportive data. The minimum cutting force as the goal, through the orthogonal experiment for the optimization of cutting parameters obtained for the high speed milling graphite with diamond-coated tool: cutting force 360m/min,feed per tooth 0.15mm/z, radial depth of cut 0.9mm, axial depth of 9mm.

Prediction of Cutting Forces during Turning PA66 GF-30 Glass Fiber Reinforced Polyamide by Soft Computing Techniques

2013 ◽  
Vol 766 ◽  
pp. 37-58 ◽  
Author(s):  
Nikolaos A. Fountas ◽  
Ioannis Ntziantzias ◽  
John Kechagias ◽  
Aggelos Koutsomichalis ◽  
João Paulo Davim ◽  
...  
Keyword(s):  
Glass Fiber ◽  
Cutting Force ◽  
Soft Computing ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Fiber Reinforced ◽  
Glass Fiber Reinforced ◽  
Soft Computing Techniques ◽  
Cutting Force Components ◽  
Force Components

In the present paper the influence of the main cutting parameters on process performance during longitudinal turning of PA66 GF-30 Glass Fiber Reinforced Polyamide is investigated. The selected cutting parameters are cutting speed and feed-rate whilst depth of cut is kept constant. As outputs (responses), cutting force components Ft, FV and Fr were selected. Test specimens in the form of round bars and cemented carbide cutting tool were used during the experimental process. Fifteen experiments were conducted having all different combinations of cutting parameter values. Analysis of Variance (ANOVA), statistical approaches and soft computing techniques (artificial neural network) were applied in order to formulate stochastic models for relating the responses with main cutting parameters. The results obtained, indicate that the proposed soft computing techniques can be effectively used to predict the cutting force components (Ft, FV and Fr) thus; facilitating decision making during process planning since costly and time-consuming experimentation can be avoided.

Diamond tool wear monitoring by sensory analysis in milling of absolute black granite

2021 ◽  
pp. 095440542110406
Author(s):  
Sandro Turchetta ◽  
Luca Sorrentino ◽  
Gianluca Parodo
Keyword(s):  
Tool Wear ◽  
Cutting Tools ◽  
Depth Of Cut ◽  
Surface Machining ◽  
Diamond Tools ◽  
The Matrix ◽  
Cutting Force Components ◽  
Force Components ◽  
Natural Stones ◽  
And Performance

Diamond tools suitable for machining operations of natural stones can be divided into two groups: cutting tools, including blades, the circular blades and the wires, and the surface machining ones, involving mills and grinders, that can be of different shapes. For the stone sawing process, the most adopted tool type is the diamond mill, whose duration and performance are influenced by various elements such as: the mineralogical characteristics of the material to be machined; the working conditions such as the depth of cut, the feed rate and the spindle speed; the production process of the diamond segment and the characteristics of both the matrix and the diamond, such as the size, the type and the concentration of the diamonds and the metal bond formulation hardness. This work allows to indirectly assess the wear of sintered diamond tools by signal analysis (in time and frequency domain) of the cutting force components acquired in the process. The results obtained represent a fundamental step for the development of a sensory supervision system capable of assessing the tool wear and hence to modify the process parameters in process, in order to optimize cutting performance and tool life.

scholarly journals Experiments in the Machining of Ice at Negative Rake Angles

1984 ◽  
Vol 30 (104) ◽  
pp. 77-81 ◽  
Author(s):  
D.K. Lieu ◽  
C.D. Mote
Keyword(s):  
Cutting Force ◽  
Chip Formation ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Rake Angle ◽  
Cutting Depth ◽  
Orthogonal Machining ◽  
Cutting Force Components ◽  
Force Components

AbstractThe cutting force components and the cutting moment on the cutting tool were measured during the orthogonal machining of ice with cutting tools inclined at negative rake angles. The variables included the cutting depth (< 1 mm), the cutting speed (0.01 ms−1to 1 ms−1), and the rake angles (–15° to –60°). Results of the experiments showed that the cutting force components were approximately independent of cutting speed. The resultant cutting force on the tool was in a direction approximately normal to the cutting face of the tool. The magnitude of the resultant force increased with the negative rake angle. Photographs of ice-chip formation revealed continuous and segmented chips at different cutting depths.

scholarly journals Trochoidal Milling and Neural Networks Simulation of Magnesium Alloys

Materials ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2070 ◽  
Author(s):  
Ireneusz Zagórski ◽  
Monika Kulisz ◽  
Mariusz Kłonica ◽  
Jakub Matuszak
Keyword(s):  
Neural Networks ◽  
Cutting Force ◽  
Magnesium Alloys ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Machining Parameters ◽  
Cutting Force Components ◽  
Multilayered Perceptron ◽  
Force Components

This paper set out to investigate the effect of cutting speed vc and trochoidal step str modification on selected machinability parameters (the cutting force components and vibration). In addition, for a more detailed analysis, selected surface roughness parameters were investigated. The research was carried out for two grades of magnesium alloys—AZ91D and AZ31—and aimed to determine stable machining parameters and to investigate the dynamics of the milling process, i.e., the resulting change in the cutting force components and in vibration. The tests were performed for the specified range of cutting parameters: vc = 400–1200 m/min and str = 5–30%. The results demonstrate a significant effect of cutting data modification on the parameter under scrutiny—the increase in vc resulted in the reduction of the cutting force components and the displacement and level of vibration recorded in tests. Selected cutting parameters were modelled by means of Statistica Artificial Neural Networks (Radial Basis Function and Multilayered Perceptron), which, furthermore, confirmed the suitability of neural networks as a tool for prediction of the cutting force and vibration in milling of magnesium alloys.

scholarly journals Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6

2018 ◽  
Vol 14 (1) ◽  
pp. 67-76
Author(s):  
Mohanned Mohammed H. AL-Khafaji
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Thickness Ratio ◽  
Depth Of Cut ◽  
Feed Force ◽  
Machining Force ◽  
Force Components

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

Modelling and Analysis of Relationship between Cutting Parameters Surface Roughness and Cutting Forces Using Response Surface Methodology when Hard Turning with Coated Ceramic Inserts

2016 ◽  
Vol 686 ◽  
pp. 19-26 ◽  
Author(s):  
Ildikó Maňková ◽  
Marek Vrabeľ ◽  
Jozef Beňo ◽  
Mária Franková
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Oxide Ceramic ◽  
Cutting Force Components ◽  
Force Components

Experimental research and modeling in the field of turning hardened bearing steel with hardness of 62 HRC using TiN coated mixed oxide ceramic inserts is presented. The main objective of the article is investigation the relationship between cutting parameters (cutting speed and feed rate) and output machining variables (surface roughness and cutting force components) through the response surface methodology (RSM). The mathematical model of the effect of process parameters on the cutting force components and surface roughness is presented. Moreover, the influence of TiN coating on above mentioned variables was monitored. The design of experiment according to Taguchi L9 orthogonal matrix (32) was applied for trials. Pearson´s correlation matrix was used to examine the dependence between the factors (f, vc) and the machining variables (surface roughness and cutting force components). The results show how much surface roughness and cutting force components is influenced by cutting speed and feed in hard turning with coated ceramics.

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