Nonlinear Influence of Effective Lead Angle in Turning Process Stability

2002 ◽  
Vol 124 (2) ◽  
pp. 473-475 ◽  
Author(s):  
Michael P. Vogler ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Depth Of Cut ◽  
Stability Prediction ◽  
Turning Process ◽  
Process Stability ◽  
Nose Radius ◽  
Lead Angle ◽  
Proposed Model ◽  
Cutting Insert ◽  
Two Degree Of Freedom ◽  
Stability Results

An analytical method for stability prediction incorporating the nonlinear influence of the effective lead angle in turning is proposed and validated. It is shown that as the effective lead angle changes, due to depth of cut variations on a nose radiused cutting insert, different structural modes are excited, resulting in different stability results. Experiments have been performed on a two degree-of-freedom system representative of the turning of long, slender bars. It is shown that chatter may be present at low depths of cut, typically less than the nose radius of the insert. The proposed model is also capable of predicting the chatter present at larger depths of cut that is typically reported in literature.

scholarly journals Development of surface roughness model in turning process of 3X13 steel using TiAlN coated carbide insert

2021 ◽  
pp. 113-124
Author(s):  
Nhu-Tung Nguyen ◽  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Machining Process ◽  
Quadratic Model ◽  
Depth Of Cut ◽  
Turning Process ◽  
Nose Radius ◽  
Machining Processes ◽  
Roughness Model ◽  
Input Parameters ◽  
Coated Carbide

Surface roughness that is one of the most important parameters is used to evaluate the quality of a machining process. Improving the accuracy of the surface roughness model will contribute to ensure an accurate assessment of the machining quality. This study aims to improve the accuracy of the surface roughness model in a machnining process. In this study, Johnson and Box-Cox transformations were successfully applied to improve the accuracy of surface roughness model when turning 3X13 steel using TiAlN insert. Four input parameters that were used in experimental process were cutting velocity, feed rate, depth of cut, and insert-nose radius. The experimental matrix was designed using Central Composite Design (CCD) with 29 experiments. By analyzing the experimental data, the influence of input parameters on surface roughness was investigated. A quadratic model was built to explain the relationship of surface roughness and the input parameters. Box-Cox and Johnson transformations were applied to develop two new models of surface roughness. The accuracy of three surface roughness models showed that the surface roughness model using Johnson transformation had the highest accuracy. The second one model of surface roughness is the model using Box-Cox transformation. And surface roughness model without transformation had the smallest accuracy. Using the Johnson transformation, the determination coefficient of surface roughness model increased from 80.43 % to 84.09 %, and mean absolute error reduced from 19.94 % to 16.64 %. Johnson and Box-Cox transformations could be applied to improve the acuaracy of the surface roughness prediction in turning process of 3X13 steel and can be extended with other materials and other machining processes

scholarly journals The Possibility of Monitoring Forces during Turning Process of Shafts Made of AW-7020 Aluminium Alloy for Variable Treatment Conditions

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Aluminium Alloy ◽  
Cutting Speed ◽  
Radial Force ◽  
Cover Plate ◽  
Depth Of Cut ◽  
Turning Process ◽  
Treatment Conditions ◽  
Feed Force ◽  
Orthogonal Components ◽  
Cutting Insert

The article presents the research results referring to the analysis of the influence of cuttingparameters on value of cutting forces during turning pins of shaft. For the monitoring of forces during lathingprocess used Kistler dynamometer. The dynamometer is used for dynamic and quasistatic measurements of the3 orthogonal components of any forces acting on the cover plate (Fx - radial force, Fy - feed force andFz - cutting force). The turning process was carried out on a universal CU500MRD/1000 centre lathe. Theresearch was performed on a shaft made of 7020 aluminium alloy. Chemical composition of aluminium alloywas measured by Solaris-ccd plus optical spectrometer. The finishing turning process was carried out by cuttingtool with CCGT09T302-DL removable insert by Duracarb. During turning the following machining parameterswere used: cutting speed, feed and depth of cut. The goal of the paper was to define the influence of treatmentconditions on values of forces during turning process, and thus monitoring the wear of the cutting insert.

Predicting the Effects of Tool Nose Radius and Lead Angle on Hard Turning Process Using 3D Finite Element Method

2010 ◽  
Author(s):  
Xueping Zhang ◽  
Heping Wang ◽  
C. Richard Liu
Keyword(s):  
Experimental Data ◽  
Finite Element Method ◽  
Finite Element ◽  
Hard Turning ◽  
Tangential Force ◽  
Chip Morphology ◽  
Turning Process ◽  
Nose Radius ◽  
Lead Angle ◽  
Tool Nose Radius

Finite element method (FEM) has been qualified as an excellent method to analyze machining processes. Many researchers commonly adopt an orthogonal FE model to simulate hard turning process without considering the effect of tool nose radius and/or lead angle. However, the PCBN cutting tools usually possess a nose radius of 0.4mm to 0.8mm, which equals to the magnitude of cutting depth/feed in hard turning. To explore the effect of tool nose radius and rake angle on hard turning AISI 52100 steel process, an explicit dynamic thermo-mechanical three-dimensional (3D) FEM is developed. The model considers tool nose radius as 0.4mm and 0.8mm, respectively with a tool lead angle of 0° and 7°. The model successfully simulates 3D saw-tooth chip morphology generated by periodic adiabatic shear and demonstrates the continuous and saw-tooth chip morphology, chip characteristic line and the material flow direction between the chip-tool interfaces. The predicted chip morphology, cutting temperature, plastic strain distribution and cutting forces agrees well with the experimental data. The oblique cutting process simulation reveals that larger lead angle enables work material deformation more severely, the maximum temperature on the chip-tool interface reaches 1289°, close to the measured average temperature of 1100°; the predicted average tangential force is 150N, with 7% difference from the experimental data. When the cutting tool nose radius increases to 0.8mm, the chip’s temperature and strain becomes relatively higher, and average tangential force increases 10N. This paper also discusses the disagreement between the predicted and experimental cutting force.

Surface Roughness Prediction Based on Cutting Parameters and Nose Radius in Precision Turning

2007 ◽  
Vol 329 ◽  
pp. 539-544 ◽  
Author(s):  
Ying Chun Liang ◽  
Yuan Sheng Zhai ◽  
H.X. Wang ◽  
Qing Shun Bai ◽  
Y. Zhao
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Ratio Test ◽  
Nose Radius ◽  
Precision Turning ◽  
Proposed Model ◽  
Roughness Prediction ◽  
Optimal Cutting Parameters

In precision turning, the quality of surface finish is an important requirement for machined workpiece. Thus, the choice of optimal cutting parameters is very important for controlling the required surface quality. The focus of the present study is to find a correlation between surface roughness and cutting parameters (feed rate, depth of cut) and nose radius in turning 3J33 maraging steel, and to derive mathematical models for the predicted surface roughness based on both of cutting parameters and nose radius. The experimental design is carried out using the quadratic rotary combination design. The regression analysis shows feed rate and nose radius influence surface roughness significantly. With F-ratio test the proposed model is adequate. The method could be useful in predicting roughness parameters as a function of cutting parameters and nose radius.

scholarly journals A combination method for multi-criteria decision making problem in turning process

2021 ◽  
Vol 8 ◽  
pp. 26
Author(s):  
Do Duc Trung
Keyword(s):  
Decision Making ◽  
Removal Rate ◽  
Entropy Method ◽  
Combination Method ◽  
Depth Of Cut ◽  
Multi Criteria Decision Making ◽  
Turning Process ◽  
Nose Radius ◽  
Cutting Force Components ◽  
Force Components

This paper presents a multi-criteria decision making (MCDM) for a turning process. An experimental process was performed according to the sequence of a matrix using the Taguchi method with nine experiments. The parameters including workpiece speed, feed rate, depth of cut, and nose radius were selected as the input variables. At each experiment, three cutting force components that were measured in the three directions X, Y, and Z, were Fx, Fy, and Fz, respectively. The value of Material Removal Rate (MRR) was also calculated at each experiment. The main purpose of this study is determination of an experiment in total performed experiments simultaneously ensuring the minimum Fx, Fy, and Fz and the maximum MRR. The Entropy method was applied to determine the weights for parameters Fx, Fx, Fx, and MRR. Eight MCDM methods were applied for multi-criteria decision making, this has not been performed in any studies. The implementation steps of each method were also presented in this paper. Seven ones of these eight methods determined the best experiment in total nine performed experiments. A new multi-criteria decision-making method as well as orientation for the further works were also proposed in this study.

Study of Factors Effecting Surface Roughness and Tool Tip Temperature in Step Turning Using Factorial Technique

2015 ◽  
Vol 15 (4) ◽  
pp. 319-326
Author(s):  
Kondapalli Siva Prasad
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Regression Analysis ◽  
Process Parameters ◽  
Depth Of Cut ◽  
Turning Process ◽  
Nose Radius ◽  
Five Factors ◽  
The Mathematical Model ◽  
Anova Technique

AbstractThe paper focuses on the effect of various process parameters like spindle speed, feed, depth of cut, nose radius and machining condition on the Tool tip temperature and surface roughness in step turning process is investigated by using Factorial Technique. Five factors- Two levels are used and total 32 experiments are performed. The coefficients are calculated by using regression analysis and the model is constructed. The adequacy of the developed model is checked using Analysis of Variance (ANOVA) technique. By using the mathematical model the main and interaction effect of various process parameters on tool tip temperature and surface roughness are studied.

Calculation of Effective Ground Depth of Cut by Means of Grinding Process Model

2011 ◽  
Vol 496 ◽  
pp. 7-12 ◽  
Author(s):  
Takazo Yamada ◽  
Michael N. Morgan ◽  
Hwa Soo Lee ◽  
Kohichi Miura
Keyword(s):  
Process Model ◽  
Ground Surface ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Wheel Wear ◽  
Elastic Deformations ◽  
Proposed Model ◽  
Effective Depth ◽  
Grinding Machine

In order to obtain the effective depth of cut on the ground surface, a new grinding process model taking into account thermal expansions of the grinding wheel and the workpiece, elastic deformations of the grinding machine, the grinding wheel and the workpiece and the wheel wear was proposed. Using proposed model, the effective depth of cut was calculated using measured results of the applied depth of cut and the normal grinding force.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

Dynamics of a Two-DOF Parallel Pointing Mechanism

2005 ◽  
Author(s):  
Alessandro Cammarata ◽  
Rosario Sinatra
Keyword(s):  
Numerical Simulation ◽  
Parallel Mechanism ◽  
Inverse Dynamics ◽  
Kinematic Model ◽  
Degree Of Freedom ◽  
Numerical Examples ◽  
Proposed Model ◽  
Dynamic Analyses ◽  
Moving Platform ◽  
Two Degree Of Freedom

This paper presents kinematic and dynamic analyses of a two-degree-of-freedom pointing parallel mechanism. The mechanism consists of a moving platform, connected to a fixed platform by two legs of type PUS (prismatic-universal-spherical). At first a simplified kinematic model of the pointing mechanism is introduced. Based on this proposed model, the dynamics equations of the system using the Natural Orthogonal Complement method are developed. Numerical examples of the inverse dynamics results are presented by numerical simulation.

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