An Investigation on Machining Power of EN-AC 48000 Aluminum Alloy Used in Automotive and Aerospace Industries

2009 ◽  
Vol 83-86 ◽  
pp. 704-710 ◽  
Author(s):  
H. Shahali ◽  
Hamid Zarepour ◽  
Esmaeil Soltani
Keyword(s):  
Signal To Noise Ratio ◽  
Cutting Tools ◽  
Tool Material ◽  
Polycrystalline Diamond ◽  
Dimensional Accuracy ◽  
Machining Parameters ◽  
Anova Analysis ◽  
Essential Parameter ◽  
Cutting Velocity ◽  
Coated Carbide

In this paper, the effect of machining parameters including cutting velocity, feed rate, and tool material on machining power of EN-AC 48000 aluminium alloy has been studied. A L27 Taguchi's standard orthogonal array has been applied as experimental design to investigate the effect of the factors and their interaction. Twenty seven machining tests have been accomplished with two random repetitions, resulting in fifty four experiments. EN-AC 48000 is an important alloy in automotive and aerospace industries. Machining of this alloy is of vital importance due to build-up edge and tool wear. Machining power is an essential parameter affecting the tool life, dimensional accuracy, and cutting efficiency. Three types of cutting tools including coated carbide (CD 1810), uncoated carbide (H10), and polycrystalline diamond (CD10) have been used in this study. Statistical analysis has been employed to study the effect of factors and their interactions using ANOVA analysis. Moreover, optimal factor levels have been presented using signal to noise ratio (S/N) analysis. Also, regression model have been provided to predict the machining power. Finally, the results of confirmation tests have been presented to verify and compare the adequacy of the predictive models.

Turning Investigations on Machining of Ti64 Alloy with Different Cutting Tool Inserts

2013 ◽  
Vol 763 ◽  
pp. 1-27 ◽  
Author(s):  
S. Ramesh ◽  
L. Karunamoorthy
Keyword(s):  
Manufacturing Industry ◽  
Cutting Tools ◽  
Dimensional Accuracy ◽  
Advanced Materials ◽  
Machining Parameters ◽  
Close Proximity ◽  
Grey Relational Grade ◽  
Cylindrical Parts ◽  
Grey Relational ◽  
Machining Characteristics

Turning operation is fundamental in the manufacturing industry to produce cylindrical parts especially for producing near-nett shape, and aesthetic requirements with good dimensional accuracy. This present research chapter, an attempt has been made to investigate the machining characteristics of titanium alloys. The investigation has been carried out to measure the effect of tool flank wear, surface roughness, cutting force and temperature on different cutting tools by adopting Taguchi’s design of experiment concept. This investigation was set to analyse and develop a mathematical model using response surface methodology, fuzzy logic. The observed responses were optimized using grey relational grade algorithm. Except for a few cases, the experimental results have close proximity (95%) to the predicted value. This validates the model developed in this work. Orthogonal array with grey relational analysis has been successfully implemented for the optimization of the machining parameters. The optimized cutting conditions evolved in this research study will help to achieve better machinability of these advanced materials like titanium alloy.

scholarly journals Monitoring and neural network modeling of cutting temperature during turning hard steel

2018 ◽  
Vol 22 (6 Part A) ◽  
pp. 2605-2614
Author(s):  
Mirfad Taric ◽  
Pavel Kovac ◽  
Bogdan Nedic ◽  
Dragan Rodic ◽  
Dusan Jesic
Keyword(s):  
Neural Network ◽  
Cubic Boron Nitride ◽  
Cutting Tools ◽  
Cutting Temperature ◽  
Tool Material ◽  
Cutting Parameters ◽  
Neural Network Modeling ◽  
Machining Parameters ◽  
Average Temperature ◽  
Hard Steel

In this study, cutting tools average temperature was investigated by using thermal imaging camera of FLIR E50-type. The cubic boron nitride inserts with zero and negative rake angles were taken as cutting tools and round bar of EN 90MnCrV8 hardened steel was used as the workpiece. Since the life of the cutting tool material strongly depends upon cutting temperature, it is important to predict heat generation in the tool with intelligent techniques. This paper proposes a method for the identification of cutting parameters using neural network. The model for determining the cutting temperature of hard steel, was trained and tested by using the experimental data. The test results showed that the proposed neural network model can be used successfully for machinability data selection. The effect on the cutting temperature of machining parameters and their interactions in machining were analyzed in detail and presented in this study.

Strategies for Developing Milling Tools from the Viewpoint of Sustainable Manufacturing

2016 ◽  
Vol 10 (5) ◽  
pp. 727-736 ◽  
Author(s):  
A. M. M. Sharif Ullah ◽  
◽  
Takeshi Akamatsu ◽  
Masahiro Furuno ◽  
M. A. K. Chowdhury ◽  
...  
Keyword(s):  
Optimization Technique ◽  
Sustainable Manufacturing ◽  
Cutting Tools ◽  
Tool Material ◽  
Milling Tool ◽  
Cutting Velocity ◽  
High Feed ◽  
Material Energy ◽  
Sharp Corners ◽  
Milling Tools

This study addresses the strategies for developing the cutting tools used in the material removal process called milling from the viewpoint of sustainable manufacturing. Sustainable manufacturing can be achieved by improving the material, energy, and component efficiencies, simultaneously. Cutting tools are just as important as machine tools and process planning to the achievement of the abovementioned efficiencies. Accordingly, this study describes two strategies based on high cutting velocity and feed per revolution, respectively. Exercising the strategy of high cutting velocity requires a Monte Carlo simulation-driven optimization technique. It helps make a balance between the tool material driven environmental burden and the user-defined maximum allowable cutting velocity. Exercising the strategy of high feed per revolution requires an innovative problem-solving procedure (e.g., TRIZ). It helps create novel solutions (e.g., an oval-shaped milling tool) that eliminate the causes of unstable cutting forces or vibrations when the tool passes over sharp corners. Thus, this study clearly shows that developing a milling tool from the viewpoint of sustainable manufacturing requires a multi-faceted approach. Similar strategies can be used to solve the problems involved in developing other cutting tools.

Study on Wafer Thinning Characteristics of Ultimate Diamond Disk

2012 ◽  
Vol 591-593 ◽  
pp. 476-479
Author(s):  
Xu Xing Jin
Keyword(s):  
Cutting Tool ◽  
Cutting Tools ◽  
Polycrystalline Diamond ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Workpiece Material ◽  
Diamond Disk ◽  
Diamond Cutting Tools ◽  
Wafer Thinning ◽  
Wafer Surfaces

Silicon wafer is machined by diamond cutting tools to certain extent, the cutting tool currently used is polycrystalline diamond (PCD). However, as its cutting edges are not leveled to the same height, it will produce different depth of cut and the stress distribution is uneven on wafer surfaces, in the process of wafer thinning, both the workpiece and the cutting tool are probably damaged, this will increase the production cost accordingly. In this paper, a strategy is described to improve the ability of cutting tool for wafer thinning, a cutting tool named Ultimate Diamond Disk (UDD) designed by Taiwan Wheel Company is recommended, which can reduce both the crack of workpiece and the wear speed of cutting tool. Moreover, an experiment on base of different machining parameters including rotation speed of spindle, feed rate and depth of cut was tested and discussed. As a result, the removal mode of workpiece material and the wafer thinning characteristics of UDD are obtained.

scholarly journals Optimization of Turning Process Parameters for Their Effect on En 8 Material Work piece Hardness by Using Taguchi Parametric Optimization Method

2012 ◽  
pp. 230-234
Author(s):  
Ashish Yadav ◽  
Ajay Bangar ◽  
Rajan Sharma ◽  
Deepak Pal
Keyword(s):  
Process Parameters ◽  
Tool Material ◽  
Optimization Method ◽  
Material Surface ◽  
Depth Of Cut ◽  
Work Piece ◽  
Machining Parameters ◽  
Turning Process ◽  
Cylindrical Parts ◽  
Coated Carbide

A common method to manufacture parts to a specific dimension involves the removal of excess material by machining operation with the help of cutting tool. Turning process is the one of the methods to remove material from cylindrical and non-cylindrical parts. In this work the relation between change in hardness caused on the material surface due the turning operation with respect to different machining parameters like spindle speed, feed and depth of cut have been investigated. Taguchi method has been used to plan the experiments and EN 8 metal selected as a work piece and coated carbide tool as a tool material in this work and hardness after turning has been measured on Rockwell scale. The obtained experimental data has been analyzed using signal to noise and. The main effects have been calculated and percentage contribution of various process parameters affecting hardness also determined.

scholarly journals Turning operation of AISI 4340 steel in flooded, near-dry and dry conditions: a comparative study on tool-work interface temperature

2019 ◽  
Vol 23 (1) ◽  
pp. 172-182 ◽  
Author(s):  
Milon Selvam Dennison ◽  
Sivaram N M ◽  
Debabrata Barik ◽  
Senthil Ponnusamy
Keyword(s):  
Cutting Tool ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cutting Velocity ◽  
Dry Conditions ◽  
Cylindrical Steel ◽  
Coated Carbide ◽  
Full Factorial ◽  
Aisi 4340

Abstract The objective of this study is to analyse the effect of tool-work interface temperature observed during the turning of AISI 4340 cylindrical steel components in three machining conditions, namely flooded, near-dry and dry conditions with three separate CNMG-PEF 800 diamond finish Titanium Nitride (TiN) coated carbide cutting tool. The machining parameters considered in this study are cutting velocity, feed rate and depth of cut. The experiments were planned based on full factorial design (33) and executed in an All Geared Conventional Lathe. The tool-work interface temperature was observed using a K-type tool-work thermocouple, while the machining of steel, and subsequently, a mathematical model was developed for the tool-work interface temperature values through regression analysis. The significance of the selected machining parameters and their levels on tool-work interface temperature was found using analysis of variance (ANOVA) and F-test. The results revealed that machining under near-dry condition exhibited lesser temperature at the tool-work interface, which is the sign of producing better quality products in equivalence with the machining under flooded condition.

Taguchi Design of Experiment in the Optimization of Tool Life in Turning Process of Duplex Stainless Steel DSS

2015 ◽  
Vol 809-810 ◽  
pp. 189-194
Author(s):  
Grzegorz Krolczyk ◽  
Andrzej Metelski ◽  
Radoslaw Maruda ◽  
Stanislaw Legutko
Keyword(s):  
Tool Life ◽  
Design Of Experiment ◽  
Signal To Noise Ratio ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Cutting Condition ◽  
Machining Parameters ◽  
Deep Well ◽  
Optimal Values ◽  
Coated Carbide

The paper presents the contribution in methodology of production processes of difficulty to cut materials particularly in optimization method of Duplex Stainless Steels (DSS). In this work, Design of Experiment (DOE) is used to examine turning experimental data. The DOE, based on the Taguchi method with orthogonal array L9 and signal-to-noise ratio are used. The optimal values of the technological cutting parameters with coated carbide tool point are searched. ANOVA analysis was performed to determine the signification of machining parameters. The significance of various cutting parameters on tool life have been proven. The results at optimum cutting condition are predicted using estimated values. The study was performed within a production facility during the machining of electric motor parts and deep-well pumps.

Comparison and optimization of PVD and CVD method on surface roughness and flank wear in hard-machining of DIN 1.2738 mold steel

Sensor Review ◽  
2019 ◽  
Vol 39 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Fuat Kara ◽  
Burak Öztürk
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Flank Wear ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Experimental Results ◽  
Machining Parameters ◽  
Quadratic Regression ◽  
Content Type ◽  
Coated Carbide

Purpose This paper aims to examine the performance of the machining parameters used in the hard-turning process of DIN 1.2738 mold steel and identify the optimum machining conditions. Design/methodology/approach Experiments were carried out via the Taguchi L18 orthogonal array. The evaluation of the experimental results was based on the signal/noise ratio. The effect levels of the control factors on the surface roughness and flank wear were specified with analysis of variance performed. Two different multiple regression analyses (linear and quadratic) were conducted for the experimental results. A higher correlation coefficient (R2) was obtained with the quadratic regression model, which showed values of 0.97 and 0.95 for Ra and Vb, respectively. Findings The experimental results indicated that generally better results were obtained with the TiAlN-coated tools, in respect to both surface roughness and flank wear. The Taguchi analysis found the optimum results for surface roughness to be with the cutting tools of coated carbide using physical vapor deposition (PVD), a cutting speed of 160 m/min and a feed rate of 0.1 mm/rev, and for flank wear, with cutting tools of coated carbide using PVD, a cutting speed of 80 m/min and a feed rate of 0.1 mm/rev. The results of calculations and confirmation tests for Ra were 0.595 and 0.570 µm, respectively, and for the Vb, 0.0244 and 0.0256 mm, respectively. Developed quadratic regression models demonstrated a very good relationship. Originality/value Optimal parameters for both Ra and Vb were obtained with the TiAlN-coated tool using PVD. Finally, confirmation tests were performed and showed that the optimization had been successfully implemented.

Experimental Investigations into Electrochemical Spark Machining of Composites

1990 ◽  
Vol 112 (2) ◽  
pp. 194-197 ◽  
Author(s):  
V. K. Jain ◽  
S. Tandon ◽  
P. Kumar
Keyword(s):  
Cutting Tools ◽  
Tool Material ◽  
Poor Performance ◽  
Experimental Investigations ◽  
Machining Parameters ◽  
Reinforced Plastics ◽  
Kevlar Fiber ◽  
Viable Solution ◽  
Fiber Reinforced Plastics ◽  
Conventional Type

Reports have indicated the poor performance of the conventional type of cutting tools during machining of composites. In this paper electrochemical spark machining (ECSM) for the cutting and drilling of holes in the composites is being proposed. The feasibility of using ECSM for composites was first ascertained. Then, kevlar-fiber-epoxy and glass-fiber-epoxy composites as work material, copper as tool material, and an aqueous solution of NaCl as electrolyte were used. It has been concluded that the ECSM is a viable solution for cutting of Fiber Reinforced Plastics (FRP). For achieving desired accuracy, surface finish, and economics of the process, the machining parameters should be optimized.

Sign in / Sign up

Export Citation Format

Share Document