Predictive Modeling of Nonlinear Regenerative Chatter via Measurement, Analysis, and Simulation

1999 ◽  
Author(s):  
J. R. Pratt ◽  
M. A. Davies ◽  
M. D. Kennedy ◽  
T. Kalmár-Nagy
Keyword(s):  
Cutting Force ◽  
Initial Conditions ◽  
Stability Boundary ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Computational Techniques ◽  
Regenerative Chatter ◽  
Stability Lobe ◽  
Measurement Analysis ◽  
On Chip

Abstract A single-degree-of-freedom active cutting fixture is employed to reveal and analyse the hysteretic nature of the lobed stability boundary in a simple machining experiment. Specifically, the seventh stability lobe of a regenerative cutting process is mapped using experimental, analytical, and computational techniques. Then, taking width of cut as a control parameter, the transition from stable cutting to chatter is observed experimentally. The cutting stability is found to possess a substantial hysteresis so that either stable or chattering tool motions can exist at the same nominal cutting parameters, depending on initial conditions. This behavior is predicted by applying nonlinear regenerative chatter theory to an empirical characterization of the cutting force dependence on chip thickness. Time-domain simulations that incorporate both the nonlinear cutting force dependence on chip thickness and the multiple-regenerative effect due to the tool leaving the cut are shown to agree both qualitatively and quantitatively with experiment.

Experimental Study on Cutting Force and Cutting Power in High Feed Milling of Ti5Al5Mo5VCrFe

2016 ◽  
Vol 836-837 ◽  
pp. 88-93
Author(s):  
Hui Sun ◽  
Hu Xiao ◽  
Liang Li
Keyword(s):  
Cutting Force ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Rough Machining ◽  
Cutting Power ◽  
Actual Output ◽  
Calculation Results ◽  
High Feed ◽  
Coated Carbide ◽  
Carbide Inserts

In order to improve the rough machining efficiency of titanium alloy, experiments were carried out to investigate the influence of feed per tooth on cutting force and cutting power with index-able coated carbide inserts. The curves of cutting parameters, including cutting force and cutting power, were obtained by single factor test. The results showed that, as the feed per tooth increases, the cutting force increases, especially in the direction of cutting width. All forces almost changed linearly with the changing of feed, and the cutting force of feed direction was the smallest force among the three directions of cutting force. The analytical model of tangential cutting force in the x-y plane was established. By calculating average chip thickness and relationships between tangential cutting force and measurements of cutting force to predict the cutting power, the calculation results were accurate which compared with the actual output power of the machine tool.

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).

Experimental Investigations of Cutting Parameters Influence on Cutting Forces and Surface Roughness of Quartz Glass

2013 ◽  
Vol 641-642 ◽  
pp. 367-370
Author(s):  
Gui Qiang Liang ◽  
Fei Fei Zhao
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Diamond Wheel ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Feed Force

Abstract In the present study, an attempt has been made to investigate the effect of cutting parameters (cutting speed, feed rate and depth of cut) on cutting forces (feed force, thrust force and cutting force) and surface roughness in milling of Quartz glas using diamond wheel. The cutting process in the up-cut milling of glass is discussed and the cutting force measured. The cutting force gradually increases with the cutter rotation at the beginning of the cut, and oscillates about a constant mean value after a certain undeformed chip thickness. The results show that cutting forces and surface roughness do not vary much with experimental cutting speed in the range of 55–93 m/min. The suggested models of cutting forces and surface roughness and adequately map within the limits of the cutting parameters considered.

Segmented Cutting Coefficient Based Chatter Modeling for High-Speed Micromilling of Ti6Al4V

2016 ◽  
Author(s):  
Kundan K. Singh ◽  
V. Kartik ◽  
Ramesh Singh
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
High Speed ◽  
Stability Boundary ◽  
Force Model ◽  
Force Prediction ◽  
High Speeds ◽  
Cutting Coefficients ◽  
Stability Lobe ◽  
Chip Load

Miniature components with complex shape can be created by micromilling with high surface accuracy. However, for difficult-to-machine materials, such as Ti-alloys, failure of low flexural stiffness micro-tools is a big limitation. High spindle speeds (20,000 to 100,000 rpm) can be used to reduce the undeformed chip thickness and the cutting forces and hence the catastrophic failure of the tool can be avoided. This reduced uncut chip thicknesses, in some cases lower than the cutting edge radius, can result in intermittent chip formation which can lead to dynamic variation in cutting forces. These dynamic force variations coupled with low flexural rigidity of micro end mill can render the process unstable. Consequently, accurate prediction of forces and stability is essential in high-speed micromilling. Most of the previous studies reported in the literature use constant cutting coefficients in the mechanistic cutting force model which does not yield accurate results. Recent work has shown significant improvement in the prediction of cutting forces with velocity-chip load dependent coefficients but a single function velocity-chip model fails to predict the forces accurately at very high speeds (>80,000 rpm). This inaccurate force prediction affects the predicted stability boundary at those speeds. Hence, this paper presents a segmented approach wherein a function is fit for a given range of speed to determine the chip load dependent cutting coefficients. The segmented velocity-chip load cutting coefficient improves the cutting force prediction at high speeds. R2 value is found to be improved significantly (>90% for tangential cutting coefficient) which yields the better forces prediction and hence more accurate stability boundary. This paper employs two degrees of freedom (2-DOF) model with forcing functions based on segmented velocity-chip load dependent cutting coefficients. Stability lobe diagram based on 2-DOF model has been created for different speed ranges using Nyquist stability criteria. Chatter frequency ranges between 1.003 to 1.15 times the experimentally determined first modal frequency. Chatter onset has been identified via a laser displacement sensor to experimentally validate the predicted stability lobe.

Stochastic Cutting Force Modeling and Prediction in Machining

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Yang Liu ◽  
Zhenhua Xiong ◽  
Zhanqinag Liu
Keyword(s):  
Stochastic Model ◽  
Cutting Force ◽  
Metal Cutting ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Force Modeling ◽  
Cutting Coefficients ◽  
Machining System ◽  
Set Up ◽  
Multi Mode

Abstract As the cutting force plays an important role in machining, the modeling of cutting force has drawn considerable interests in recent years. However, most of current methods were focused on the deterministic modeling of cutting force, while the inherent stochasticity of cutting force is rarely considered for general metal cutting machining. Thus, a stochastic model is proposed in this paper to predict the stochastic cutting force by considering realistic cutting conditions, including the inhomogeneity of cutting material and the multi-mode machining system. Specifically, we transform the constant cutting coefficient in previous models into a stationary Gaussian process in the proposed stochastic model. As for the tool vibration, the uncut chip thickness is also modeled in a stochastic manner. Moreover, it is found that the random cutting coefficients can be estimated conveniently through experiments and effectively simulated by stochastic differential equations at any timescale. Then, the stochastic cutting force can be predicted numerically by combining the stochastic model and the multi-mode dynamic equations. For verification, a three-mode machining system was set up, and workpieces with different metal alloys were tested. It is found that the random cutting coefficients estimated are insensitive to cutting parameters, and the prediction results show satisfactory agreement with experimental results in both time and statistical domains. The proposed method can provide rich statistical information of cutting forces, which can facilitate related applications like tool condition monitoring when the on-line measurement of cutting force is not preferred or even impossible.

An experimental investigation of micro-milling brass considering run out by carbide micro-end mills

2017 ◽  
Vol 232 (20) ◽  
pp. 3675-3684 ◽  
Author(s):  
Xiubing Jing ◽  
Yanling Tian ◽  
Yanjie Yuan
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Micro Milling ◽  
Method Of Calculation ◽  
Micro End Mill ◽  
End Mills

This paper presented the effect of run out on the experimental characteristic of micro-milling brass using carbide micro-end mills. A method of calculation and measurement for the run out of tool-holder-spindle assembly in micro-end mill was developed. A series of micro-milling process experiments were carried out under varying cutting parameters. The effect of run out on cutting forces, effect of cutting parameters on surface roughness, and size effect were analyzed. It was seen that the cutting force signature was seriously affected by run out in the micro-milling process. When the feed per tooth is less than the run out, the cutting force signals showed that only one cutter flute engaged in cutting process due to the effect of run out. It was also seen that the cutting force signature showed erratic variations due to the effect of tool–workpiece and the run out of tool tip at higher spindle speed. Surface roughness was affected by both cutting speed and feed per tooth. For lower cutting speed, there was increase in the surface roughness with the decrease in the cutting speed due to the effect of built-up edge. For higher cutting speed, there was increase in the surface roughness with the increase in the cutting speed due to dominance of the shearing effects. When the feed per tooth was less than the minimum chip thickness, due to the indentation and ploughing-dominated process, nonlinear increase of specific shear energy can be obtained. At lower feed per tooth, the specific energy increases with increased cutting speed. These results are used to provide strategies to optimize cutting parameters and achieve better surface quality in micro-milling brass process.

Determination of Cutting Forces for Micro Milling

2008 ◽  
Author(s):  
Shih-Ming Wang ◽  
Zou-Sung Chiang ◽  
Da-Fun Chen
Keyword(s):  
Cutting Force ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Micro Milling ◽  
Force Model ◽  
Machining Parameters ◽  
Cutting Force Model ◽  
Optimal Cutting Parameters

To enhance the implementation of micro milling, it is necessary to clearly understand the dynamic characteristics of micro milling so that proper machining parameters can be used to meet the requirements of application. By taking the effect of minimum chip thickness and rake angle into account, a new cutting force model of micro-milling which is function the instantaneous cutting area and machining coefficients was developed. According to the instantaneous rotation trajectory of cutting edge, the cutting area projected to xy-plane was determined by rectangular integral method, and used to solve the instantaneous cutting area. After the machining coefficients were solved, the cutting force of micro-milling for different radial depths of cut and different axial depths of cut can be predicted. The results of micro-milling experimental have shown that the force model can predict the cutting force accurately by which the optimal cutting parameters can be selected for micro-milling application.

FEM Simulation on the Effect of Cutting Parameters in the Driven Rotary Cutting

2014 ◽  
Vol 625 ◽  
pp. 564-569 ◽  
Author(s):  
Wataru Takahashi ◽  
Hiroyuki Sasahara ◽  
Hiromasa Yamamoto ◽  
Yuji Takagi
Keyword(s):  
Cutting Force ◽  
Flow Direction ◽  
Fem Simulation ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Experimental Results ◽  
Tool Temperature ◽  
Chip Flow ◽  
Rotary Cutting ◽  
Machining Parameter

In this paper, the influence of machining parameter in the driven rotary cutting was examined by using finite element simulation. Three dimensional modeling of rotary cutting of Inconel 718 was conducted and then cutting force, temperature distribution of chip and tool, chip thickness and its flow direction were analyzed. Then, the effect of the tool rotation speed was mainly focused on. When peripheral speed of the rotating tool increased, resultant cutting force decreased and the chip flow direction inclined to the tool rotating direction. Then high temperature region of chip became large. It was also shown that tool temperature on the driven rotary cutting was lower than that of the conventional turning. FEM simulation results were compared with the experimental results. As a result, the resultant cutting force, chip flow direction and the tool temperature of the experimental results and the analysis results showed the same trend.

Identification of Cutter Axis Tilt in End Milling

1997 ◽  
Vol 119 (2) ◽  
pp. 178-185 ◽  
Author(s):  
Li Zheng ◽  
S. Y. Liang
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Mathematical Representation ◽  
Thickness Variation ◽  
Dynamic Force ◽  
Force Components

The scope of the paper is to discuss the identification of cutter axis tilt in end milling process via cutting force analysis. Cutter axis tilt redistributes the chip load among flutes thereby generating minor frequency components of cutting forces. These minor components can be utilized to infer the tilt geometry during the cutting action. This study involved the mathematical representation of chip thickness variation due to tilt, the modeling of local forces in relation to instantaneous chip thickness, the formulation of total cutting forces through convolution integration in the angle domain, the derivation of dynamic force components in the frequency domain, and the solution for tilt geometry from the dynamic cutting forces. Results show that the tilt magnitude and orientation can be estimated given the dynamic cutting force components along with the tool/work geometry, cutting parameters, and machining configuration. Numerical simulation results confirmed the validity of the angle domain convolution approach, and the end milling experimental data agreed with the analytical model.

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