Influence of the Cutting Parameters on the Cutting Forces of Carbon Steel

2002 ◽  
Author(s):  
Zulay Cassier ◽  
Patricia Mun˜oz-Escanola ◽  
Rolda´n Sa´nchez
Keyword(s):  
Carbon Steel ◽  
Cutting Forces ◽  
Low Cost ◽  
Cutting Parameters ◽  
Carbon Steels ◽  
Machining Process ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 1045 ◽  
Alloy Steels

Plain carbon steels and alloy steels have a great application in the manufacturing process especially due to their characteristic of high machinability and low cost. The machining of these materials, the study of the cutting forces, and the power required for the cutting process is one of the most important parameters to be evaluated. The relationship between this parameter and the other cutting variables process is crucial for the optimization of the machining process. The results of this research are empirical expressions, obtained from the cutting parameters (tool nose radius, feed rate and depth of cut) and the influence of these parameters on the cutting forces for each carbon steel studied (AISI 1020, AISI 1045 and AISI 4340), as well as a general expression which includes the mechanical properties of these carbon steels. These results enable the user to predict cutting forces when using a turning process.

scholarly journals Mechanistic modeling of cutting forces in high-speed microturning of titanium alloy with consideration of nose radius

2021 ◽  
Author(s):  
Kubilay Aslantas ◽  
Şükrü Ülker ◽  
Ömer Şahan ◽  
Danil Yu Pimenov ◽  
Khaled Giasin
Keyword(s):  
Cutting Forces ◽  
High Speed ◽  
Mechanistic Model ◽  
Cutting Speed ◽  
Mechanistic Modeling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Multilinear Regression Analysis ◽  
Edge Radius

AbstractMicroturning is a micromechanical machining process used to produce microcylindrical or axially symmetrical parts. Microcylindrical parts are mainly used in microfluidic systems, intravenous micromotors, microsurgical applications, optical lens applications, and microinjection systems. The workpiece diameter is very small in microturning and therefore is greatly affected by the cutting forces. For this reason, it is important to predict the cutting forces when machining miniature parts. In this study, an analytical mechanistic model of microturning is used to predict the cutting forces considering the tool nose radius. In the semi-empirically developed mechanistic model, the tool radius was considered. A series of semi-orthogonal microturning cutting tests were carried out to determine the cutting and edge force coefficients. The mechanistic model was generalized depending on the cutting speed and depth of cut by performing multilinear regression analysis. In the study, the depth of cut (ap = 30–90 µm) and feed values (f = 0.5–20 µm/rev) were selected considering the nose radius and edge radius of the cutting tool. The experiments were carried out under high-cutting speeds (Vc = 150–500 m/min) and microcutting conditions. Ti6Al4V alloy was used as the workpiece material and the tests were carried out under dry cutting conditions. Validation tests for different cutting parameters were carried out to validate the accuracy of the developed mechanistic model. The results showed that the difference between the mechanistic model and the experimental data was a minimum of 3% and a maximum of 24%. The maximum difference between the experimental and the model usually occurs in forces in the tangential direction. It has been observed that the developed model gives accurate results even at a depth of cut smaller than the nose radius and at feed values smaller than the edge radius.

Prediction of the Cutting Forces on Stainless Steels When Using a Turning Process

2003 ◽  
Author(s):  
Zulay Cassier ◽  
Patricia Mun˜oz-Escalona ◽  
Jannelly Moreno
Keyword(s):  
Stainless Steels ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Turning Process ◽  
High Corrosion Resistance ◽  
Aisi 304 ◽  
Heat Treated

Stainless steels have a great application in the manufacturing process especially due to their characteristic high corrosion resistance. The machining of these materials, the study of the cutting forces, and the power required for the cutting are important parameters to be evaluated. Their relationship with other cutting variables process is crucial for the optimization of the machining process. The results of this research are empirical expressions relating cutting parameters (cutting speed, feed rate and depth of cut) to cutting forces for each stainless steel studied, AISI 304, AISI 420 and AISI 420HT (HT: Heat treated). A general expression was also developed which includes the mechanical properties of these stainless steels. These results enable the user to predict cutting forces when using a turning process.

Cutting Force Modeling in Precision Turning 3J33 Alloy for Tool with Nose Radius

2009 ◽  
Vol 69-70 ◽  
pp. 167-171
Author(s):  
Yuan Sheng Zhai ◽  
Yu Wang ◽  
Ying Chun Liang
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Parameters ◽  
Multiple Correlation Coefficient ◽  
Depth Of Cut ◽  
Ratio Test ◽  
Nose Radius ◽  
Precision Turning ◽  
Force Modeling

Based on experimental results, a predictive model with certain constraints of cutting parameters (feed rate and depth of cut) and nose radius for cutting forces is solved in precision turning 3J33 alloy. The proposed model is adequate with F-ratio test and multiple correlation coefficient of it. Regression analysis shows that depth of cut and feed rate influence the principal cutting force significantly. The goal of this study is to predict cutting forces under certain constraints of cutting parameters and nose radius.

scholarly journals Determination of Energy Consumption during Turning of Hardened Stainless Steel Using Resultant Cutting Force

Metals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 565
Author(s):  
Rusdi Nur ◽  
Noordin Mohd Yusof ◽  
Izman Sudin ◽  
Fethma M. Nor ◽  
Denni Kurniawan
Keyword(s):  
Stainless Steel ◽  
Energy Consumption ◽  
Cutting Force ◽  
Cutting Forces ◽  
Electrical Energy ◽  
Machining Process ◽  
Depth Of Cut ◽  
Electrical Energy Consumption ◽  
Nose Radius ◽  
Finish Turning

Downsizing energy consumption during the machining of metals is vital for sustainable manufacturing. As a prerequisite, energy consumption should be determined, through direct or indirect measurement. The manufacturing process of interest is the finish turning which has been explored to generate (near) net shapes, particularly for hardened steels. In this paper, we propose using measured cutting forces to calculate the electrical energy consumption during the finish turning process of metals where typically the depth of cut is lower than the cutting tool nose radius. In this approach, the resultant cutting force should be used for calculating the energy consumption, instead of only the main (tangential) cutting force as used in the conventional approach. A case study was carried out where a hardened stainless steel (AISI 420, hardness of 47–48 HRC) was turned using a coated carbide tool, with a nose radius of 0.8 mm, without cutting fluid, and at 0.4 mm depth of cut. The experimental design varied the cutting speed (100, 130, and 170 m/min) and feed (0.10, 0.125, and 0.16 mm) while other parameters were kept constant. The results indicate that the electrical energy consumption during the particular dry turning of hardened steel can be calculated using cutting force data as proposed. This generally means machining studies that measure cutting forces can also present energy consumption during the finish or hard turning of metals, without specifically measuring the power consumption of the machining process. For this particular dry turning of hardened stainless steel, cutting parameters optimization in terms of machining responses (i.e., low surface roughness, long tool life, low cutting force, and low energy consumption) was also determined to provide an insight on how energy consumption can be integrated with other machining responses towards sustainable machining process of metals.

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.

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.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

Predicting the Effects of Cold Working on the Machining Characteristics of Low Carbon Steels

1987 ◽  
Vol 109 (3) ◽  
pp. 257-264 ◽  
Author(s):  
E. M. Kopalinsky ◽  
P. L. B. Oxley
Keyword(s):  
Flow Stress ◽  
Carbon Steel ◽  
Cutting Forces ◽  
Cold Working ◽  
Low Carbon Steel ◽  
Carbon Steels ◽  
Low Carbon ◽  
Low Carbon Steels ◽  
Steel Work ◽  
Machining Characteristics

Experiments show that the cold working of low carbon steel work materials can improve their machinability by reducing cutting forces and improving surface finish and tool life. The somewhat paradoxical result of reducing cutting forces by cold working a material so that its hardness is increased is explained in this paper by using a machining theory which takes account of the flow stress properties of the work material and can thus allow for the effects of cold working.

Low Cost Vibration Measurement and Optimization during Turning Process

2018 ◽  
Vol 1148 ◽  
pp. 103-108 ◽  
Author(s):  
N.V.S. Shankar ◽  
A. Gopi Chand ◽  
K. Hanumantha Rao ◽  
K. Prem Sai
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Low Cost ◽  
Machining Process ◽  
Vibration Measurement ◽  
Depth Of Cut ◽  
Turning Process ◽  
Taguchi Analysis ◽  
Series Of Experiments

During machining any material, vibrations play a major role in deciding the life of the cutting tool as well as machine tool. The magnitude acceleration of vibrations is directly proportional to the cutting forces. In other words, if we are able to measure the acceleration experienced by the tool during machining, we can get a sense of force. There are many commercially available, pre-calibrated accelerometer sensors available off the shelf. In the current work, an attempt has been made to measure vibrations using ADXL335 accelerometer. This accelerometer is interfaced to computer using Arduino. The measured values are then used to optimize the machining process. Experiments are performed on Brass. During machining, it is better to have lower acceleration values. Thus, the first objective of the work is to minimize the vibrations. Surface roughness is another major factor which criterion “lower is the better” applies. In order to optimize the values, a series of experiments are conducted with three factors, namely, tool type (2 levels), Depth of cut (3 levels) and Feed are considered (3 levels). Mixed level optimization is performed using Taguchi analysis with L18 orthogonal array. Detailed discussion of the parameters shall be given in the article.

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