deform2d

DETERMINATION OF DEPTH OF PLASTIC DEFORMATION ON MACHINED SURFACE

ABSTRACT

Metal cutting is the most important process amongst all the manufacturing

processes as it produces the metal components very close to the desired surface integrity

and size. Modern usage of edge prepared cutting tools motivates to study the depth of

plastic deformation under machined surface. Study of various edge prepared tool is

similar to a tool with a flank wear land. When the tool gets worn it develops a plastic

zone below the surface to a certain depth during machining. In this plastically affected

zone grain of the metal slightly elongate in the direction of machining which distinguish

it from rest of the sub surface area. The nature and depth of this plastically affected zone

are expected to be depends on fundamental machining parameters, extent of tool wear

and materials of work. To experimentally investigate depth of plastically affected zone

as well as to study the parameters influencing it can be accomplished by studying the

micro photographs of the subsurface zone. The study of micro photographs also enables

us to determine strain induced in that zone by studying the amount of elongation of

grains. This can be accomplished by conducting machining experiments on shaping

machine using Mild steel and HSS tool. Worn tools required for conducting the

experiments may be induced by appropriately developing an artificially induced flank

wear land in the HSS tools. An attempt is made to simulate the machining with different

flank wear land inclination. The deformation of microstructure clearly indicates the

depth of plastic deformation increases with the increase in flank wear land inclination.

Similar trend is found with the simulation of machining process with DEFORMA-2D.

DEPARTMENT OF INDUSTRIAL AND PRODUCTION ENGINEERING Page 1


CONTENTS

CHAPTER 1 INTRODUCTION PAGE NO

1.1Back ground and Motivation 3 1.2

Plastic deformation 4

CHAPTER 2 LITERATURE REVIEW

2.1 Effect of flank wear 5

2.2 Effect of cutting speed 6

2.3 Influence of parameters on microstructure 6

2.4 Influence of parameters on surface integrity 7

2.5 Influence of cutting parameters on plastic deformation 7

CHAPTER 3 OBJECTIVES OF THE PRESENT WORK AND

METHODOLOGY 9

CHAPTER 4 EXPERIMENTAL PROCEDURE

4.1 Design of experiment 11

4.2 Cutting tool and Work piece material 15

4.3 Results and discussions 16

CHAPTER 5 FINITE ELEMENT METHOD

5.1 Introduction to DEFORM 2D 19

5.2 Pre-processor in deform 2D 19

5.3 Meshing in DEFORM 2D 20

5.4 Simulation in DFEROM 2D 21

5.5 Finite element modelling 21

5.6Test run simulations 23

5.7Results and discussion 23

CHAPTER 6 CONCLUSION 28

6.1 Feature scope of work 28

REFERENCES 29



CHAPTER 1

INTRODUCTION

1.1 General Background and motivation

High speed turning technology is growing rapidly in the recent years especially in

area of manufacturing, aerospace, and defense and missile components. The behavior of

work metal changes with the change in cutting speed. The transition of chips from

continuous to shear localized is also dependent on machining speed. The range of the

high speed machining aluminum components is about 500- 1000 m/min. One of the

major benefits of cutting at higher speed is the reduction of cutting forces leading to

improvement in surface integrity in terms of lower cutting force magnitude, fine surface

finish, and lower depth of deformation in machined surface. Surface integrity of the

machined component (the nature of surface condition of a work piece after machining

process) is a critical parameter in deciding the component performance, reliability and

service life. Surface integrity of the machined component (the nature of surface condition

of a work piece after machining process) is a critical parameter in deciding the component

performance, reliability and service life.

There are two aspects to surface integrity i.e.

Surface topography characteristics

Surface layer characteristics.

The surface topography comprises of surface roughness, waviness, from errors, and

flaws. Work material below the machined surface is highly influenced by machining

parameters (speed, depth of cut).



1.2 PLASTIC DEFORMATION

In materials science, plasticity describes the deformation of a material undergoing

non-reversible changes of shape in response to applied forces.

Plastic deformation is observed in most materials including metals, soils, rocks,

concrete, foams, bone and skin. However, the physical mechanisms that cause plastic

deformation can vary widely. At the crystal scale, plasticity in metals is usually a

consequence of dislocations. In most crystalline materials such defects are relatively rare.

But there are also materials where defects are numerous and are part of the very crystal

structure, in such cases plastic crystallinity can result. In brittle materials such as rock,

concrete, and bone, plasticity is caused predominantly by slip at micro cracks.


http://en.wikipedia.org/wiki/Plastic_crystallinity

http://en.wikipedia.org/wiki/Dislocation

http://en.wikipedia.org/wiki/Deformation_(engineering)

http://en.wikipedia.org/wiki/Materials_science


CHAPTER 2

LITERATURE SURVEY

2.1 Effect of flank wear

The effect of flank wear on the topography of machined surfaces is investigated by

studying its effect on the shape of the tool nose. For this purpose, turning experiments

were performed to produce surfaces corresponding to different levels of flank wear. The

distribution of flank wear at the tool nose during these experiments caused the nose radius

to decrease, which when replicated on the machined surface resulted in narrower and

deeper feed marks. This change in the geometry of feed marks was represented by the

increase in the arithmetic average roughness of the surface profile heights [5].

Journal of material shaping technology, page no 255-265.



2.2 Effect of cutting speed:

In this study, an attempt has been conducted to investigate the effects of cutting

parameters on tool wear and surface roughness during hard turning of Inconel material.

The experimental results have revealed that the cutting speed is the most significant effect

to the flank wear; whereas the surface roughness is strongly influenced by the feed rate

and slight related to the tool wear mechanisms. Due to the high pressure at elevated

temperature, a micro-welding and built-up-edge are formed even at relatively low cutting

speeds of 30-45m/min; it is a disadvantage for the machined surface quality. Particular,

the surface roughness tends to decreased with the increased of the cutting speed when the

built-up-edge was disappeared. However, the tool wear increased rapidly when the

cutting speed increased over 90 m/min. This phenomenon is therefore inevitable affected

to the tool life and the machined surface quality [3].

2.3 Influence of parameters on microstructure:

Microstructure and material flow of aluminium alloys have a significant influence on

the mechanical properties and surface quality. A prediction of grain size and precipitation

is of increasing importance in order to design the process by adjustment of parameters

such as speed, temperatures, and quenching. To give references for microstructure

prediction based on material flow, and with it strain and strain rate history, this paper

deals with the microstructure during the extrusion process of AA6060, AA6082, and

AA7075 alloys. Billets have been partly extruded to axisymmetric round profiles and the

microstructure of the press rests consisting of the billet rests in container and die has been

considered. Furthermore, these rests have been analyzed to show the material flow,

dynamic and static recrystallization based on macro etchings and visible microstructure

under different conditions, e.g. as in the area of high strain rate near the container wall, or

in dead zones. To allow an accurate simulation of the extrusion process, punch force and

temperature conditions during the tests have been measured. [1].



2.4 Influence of parameters on surface integrity:

The paper presents surface integrity analysis in high speed machined titanium

alloy. The experiments were conducted in dry environment. Response surface method

based CCD was used to analyse the effect of machining parameters on surface roughness,

degree of work hardening and the induced residual stresses after machining. The analysis

of results shows a micro deformation layer up to a depth of 200 μm influencing the micro

hardness and residual stresses. The degree of work hardening in this layer is found to

influence by the machining conditions up to a depth of 100 μm, beneath the machined

surface. Predominant thermal softening effect at higher cutting speed causes the

restructuring of the micro deformation layer. Thus the machined surface shows less

alterations and correspondingly lower surface roughness. Higher cutting speed also

favours induction of higher compressive residual stresses [2].

2.5 Influence of cutting parameters on plastic deformation:

Because plastic deformation is a nuisance in the metal cutting process, its proper account

is of high interest. A new meaning for the chip compression ratio is discussed showing

that, on the contrary to shear strain, this parameter represents the true plastic deformation

in metal cutting. The chip compression ratio can be used to calculate the total work done

by the external force applied to the tool and then might be used for optimization of the

cutting process. It is demonstrated that the cutting speed influences the energy spent on

the deformation of the chip through temperature, dimensions of the deformation zone

adjacent to the cutting edge and velocity of deformation. The separate impacts of these

factors have been analyzed and the physical background behind the known experimental

dependence of the chip compression ratio on the cutting speed is revealed. The influence

of the cutting feed, tool cutting edge angle, cutting edge inclination angle and tool rake

angle also have been analysed.

A R Rodrigues et.al studied the effect of milling conditions on the surface

integrity of steels. Cutting speed, feed rate and depth of cut were related to microstructure

of the work piece beneath machined surface the microstructure shows the deformation of

microstructure were observed in work piece subsurface as shown in figure[4].



Figure 2.1 No deformation at the edge

Figure 2.2 Grain deformation is observed at the edge



CHAPTER 3

OBJECTIVES OF PRESENT WORK AND METHODOLOGY

The main objectives of the present work are as stated:

1. To get introduced to the systematic research in the area of metal machining.

2. To study the influence of machining parameters on sub-surface layer.

3. To study the change in the shape of the grains structure.

4. To study the depth of plastically affected zone due to tool flank wear land.

5. Finite element method is used to study the strain deformation in the work material

using DEFORMED 2D machining software.

METHODOLOGY

The plastic deformation beneath the flank wear land is estimated by observing the

deformation of microstructure of the material. For this HSS cutting tool with artificially

created wear land .This wear land makes an inclination with cutting direction as

suggested by N S Das and S T Dundur as shown in Figure 3.1. In the present study 2

degree and 4 degree inclination is considered. The mild steel work piece are shaped by

using the above mentioned tool, and is polished by emery paper and wet circular disc for

the metallography observation. The flow diagram of the methodology of microstructure

observation is shown in figure 3.2

As experiments consume time and cost simulation techniques are widely used

nowadays. In the present study DEFORMA 2D software is used to simulate the

orthogonal machining.



Figure 3.1 Flank wear land making an inclination with respect to cutting direction

Figure 3.1 Methodology flow diagram



CHAPTER 4

EXPERIMENTAL PROCEDURE

To conduct orthogonal machining experiments the inclined artificial flank wear land are

created on the tool and grinding cutter. These tools are used set on the shaper machine.

The mild steel work pieces are shaped with different cutting speeds. Later work pieces are

prepared for microstructure observation by polishing them with different grades of emery

papers and polishing disc. Using Meta Tech image analyser image are captured after

applying Nital etchant. The experiments are planned as per the half factorial matrix of

design of experiments. The following section describes the DOE and other details of the

experiments.

4.1 Design Of Experiments (DOE)

“Design of experiment (DOE) is a structured, organized method that is used to

determine the relationship between the different input parameters (X) affecting a process



and the out put parameters of that process (Y)”. This method was first developed in the

1920s and 1930s by sir Ronald.A.Fisher, the renowned mathematician and geneticist.

Design of experiment involves designing a set of experiments, in which all

relevant factors are varied systematically. When the results of these experiments are

analysed, they help to identify optimal conditions, the factors that are more influential on

the results and those that are not, as well as details such as the existence of interactions

and synergies between the factors.

Statistical design of experiments refers to the process of planning the experiment so

that appropriate data that can be collected and analysed by statistical methods resulting in

valid and objective conclusions. The statistical approach to experimental design is

necessary to get meaningful conclusions from the data. Thus, there are two aspects to any

experimental problem: the design of experiment and the statistical analysis of the data.

These two subjects are closely related because the method of analysis depends directly on

the design employed .

4.1.1 The Objectives Of Design Of Experiments

In general, experiments are used to study the performance of processes and systems. A

model shown in the figure can represent the process or system. We can visualize the

process as a combination of the machines, methods, people, and other resources that

transform some input into an output that has one or more observable responses. Some of

the process variables x1, x2, ….., xp are controllable, whereas other variables z1, z2, ….., zq

are uncontrollable.



Fig. 3.1: General model of a process or system

1. Determining which variables are most influential on the response Y (output).

2. Determining where to set the influential factors X’s so that Y response is almost

always near the desired nominal value.

3. Determining where to set the influential factors X’s so that variability in response

Y is small.

4. Determining where to set the influential factors so that the effects of the

uncontrollable variables Z1, Z2 ….Zn are minimized.

5. Developing a robust process, that is, a process affected minimally by external

sources of variability.

4.1.2 Steps Of Design Of Experiment

1. Recognition of and statement of the problem.

2. Identification of process parameters (input variables), levels and ranges.

3. Selection of response variables.

4. Choice of experimental design.

5. Conduction of experiments and recording of the response variables.

6. Development of mathematical models, using linear and/or non linear regression

modelling.

7. Checking the statistical adequacy of the model through significance test (F-test) and

ANOVA test.

8. Performance evaluation of the developed models using some random test cases.

++++++



4.2 Steps of Experimentation

The input parameters are of the experiments are given in the table 4. The design matrix as

per the half factorial and response of the experiments are shown in table 4.2

Table 4.1 Parameter Descriptions

Sl no

Parameters Description Levels

FactorsNotatio

nUnit High (+1) Low (-1)

1 Flank width A Mm .4mm .2mm

2 Flank angle B Degrees 6º 0º

3 Speed D m/sec 20 10

Table 4.2 Deign Matrix of experiments

Std

Order

Flank

land

Flank

angle

Speed Depth of

plastic

deformatio

n

1 .300 0 10 0.0258

2 .315 2 20 0.0310

3 .350 3 10 0.0421

4 .400 6 20 0.0594

The detail steps of the of the experimental procedure is explained below

1. The experiments are planned as per the design of experiments. Half full factorial

matrix is used in the present study.

2. Consider the pure specimen (mild steel) of length=30mm Breadth=30mm

height=10mm.



3. Polish this specimen with emery paper before machining and apply the etchants

over the surface, wash with water and then dry it, and note the grain size and

structure with the help of digital microscope.

4. Consider the new specimen and mount it on the shaper machine and perform

machining operation on the top surface of the sample by applying suitable

machining parameters.

5. Polish the sub-surface of the sample by using emery paper, note the depth of

plastic deformation using digital microscope.

6. Apply the etchants over the surface, wash with water and then dry it, and note the

grain size and structure with the help of digital microscope.

7. Repeat the procedure for different machining parameters, and note down the depth

of plastic deformation, grain size and structure.

8. Take all the microscopic photographs.

9. Etchants are: Ethanol 100ml and nitric acid 5-10 ml, together makes the etchants

called NITAL.

10. DEFORMA 2D is utilized to simulate the orthogonal machining operation to

determine the strain variations in the workpiece

4.3 Cutting Tool and Work piece Material.

Table 3 Chemical composition of the commercial purity of mild steel used in

present work.

Chemicals C Si Mn P S Cr Mo Ni

Report in

%

.533 .318 .521 .035 .039 .117 .002 .073

Chemicals Al Zn Ca Pr CE Cu Fe

Report in

%

.013 .062 .001 .001 .651 .122 98.16

4.4 Results And Discussions

The workpieces after machining are prepared for microstructure observation . first

top most part of the workpiece(approx 10x10 mm) is cut from the main work



piece. Then it is polished with grades as 200,300,400,600 and 800 to obtain the

smooth surface. The wet circular polishing disc provides the required mirror finish

on the machined surface to enable clear microstructure under the microscope. The

workpiece are observed under 200 x magnifications. The figure 4.1 shows the

microstructure of the unmachined portion of mild steel work piece. Which shows

the uniform grains of the work material? Figure 4.2 shows the microstructure of

the machined work piece for the 2 degree inclination of flank wear land with the

cutting direction. The figure 4.2 shows the deformed grain zone and unreformed

grain zone clearly. The figure 4.3 shows a significant deformed zone because of

higher flank wear land inclination, 4 degrees. From the figure 4.2 and 4.3it is

evident that the plastic deformation of grains of the machined sub surface is

affected by the increase in flank wear land inclination.

Figure 4.1 The microstructure of the unmachined portion of mild steel work piece.

Figure 4.2 The microstructure of the machined work piece for the 2 degree inclination of

flank wear land



Figure 4.3 Significant deformed zone because of higher flank wear land inclination 4

degree

Figure 4.4 highest deformation found because of larger flank wear land inclination zone

CHAPTER 5

FINITE ELEMENT METHOD

5. Introduction To Finite Element Method

Finite element analysis is preferred than the laborious experimental work in order

to save time and cost. Researchers have found that the results obtained from finite

element analysis stays close to the experimental results. Hence finite element analysis is

preferred in this work. Development of the Finite Element Method (FEM) in early 1970s



first pioneered simulations of orthogonal machining process. First research work used as

self-developed finite element code. From 1990s massive use of commercial software

starts, which is capable of modelling the machining process, as a NIKE2,

ABAQUS/Standard, MARC, DEFORM 2D, FORGE 2D, ALGOR, FLUENT, ABAQUS/

Explicit, LS DYNA. Deform is an engineering simulation software used by designers to

analyze metal forming, machining and heat treatment processes by trial and error method.

DEFORM-2D is based on an updated Lagrangian formulation that employs implicit

integration method designed for large deformation simulations, is used to simulate the

cutting process. The strength of the FEM software is its ability to automatically remesh

and generate a very dense grid of nodes near the tool tip so that large gradients of strain,

strain-rate and temperature can be handled. Deform is effective in wide range of research

and industrial applications due to its effectiveness.

5.1 Introduction To Deform 2d

Deform 2D is a software code used widely for finite element analysis in metal forming

operations which involves deformations and heat transfer. The FE tool is capable of

converting large scale problems in magnitude and complexity into solvable 2D problems.

The domain is divided into nodes and elements which store the values calculated at

various time intervals during the simulation process. The large non-steady state

calculations are reduced to smaller steady state equations and solved one step at a time

over the course of the simulation. Figure 4.1 shows the structure in Deform 2D.

Figure5.1 Structure of Deform2D (Deform user manual)



5.2 Pre-Processor In Deform 2D

The pre-processor uses a graphical user interface to assemble the data required to run the

simulation. The orthogonal cutting process is modelled as a plane strain problem which

assumes the geometry to have a unit depth with both front and back faces constrained.

The simulation assumes that the objects will behave identically in any given cross-section

across the width and height of the object. The instructions on conditions of the processing

environment, physical processes to be modelled, discrete time steps are called simulation

data input. Metal cutting process involves heat transfer and deformations. The heat

transfer module simulates thermal effects in the simulation, including heat transfer

between objects and the environment, and heat generation due to deformation or phase

transformation, wherever it is applicable. The deformation module simulates deformation

due to mechanical, thermal, or phase transformation effects. The materials are imported

from the material database or created manually by defining the flow stress value. The

geometry of plastic, elastic and finite element mesh of linear quadrilateral elements

represents non- isothermal rigid objects.

5.3 Meshing In Deform 2D

Finite element meshes are created within the Deform environment using the

automatic mesh generator. The object border geometry is defined before creating a FE

mesh. Mesh density refers to the relative sizes of the elements, which will be generated

within an object boundary. The mesh density is primarily based on the specified total

number of elements and point or parameter density controls. When the mesh is generated,

it will contain approximately the number of elements specified by the user. Mesh density

is specified by either assigning relative densities to graphically selected points within the

object boundary (user defined mesh density), or by assigning values to a set of automatic

mesh density parameters (system defined mesh

density). The mesh is generated by the Automatic mesh generator which determines the

need for remeshing and determines the optimum mesh density based on the geometric

shape and prior solution behaviour. It constructs the mesh based on the optimum mesh

density and transfers information including boundary conditions from the old mesh to the

new one.

5.4 Simulation In Deform 2D

To perform a simulation, a database containing the process data and simulation controls is

prepared. The database is created using the above pre-processor inputs. The control,



material, object and inter-object options of the pre-processor allow for interactive input of

the simulation parameters. The specified database is executed as simulation steps are

generated. The output is written back into the database file. The basic equation of

equilibrium, constitutive relationship and boundary conditions are converted to non-linear

algebraic equations. All the input and output data are stored in binary form and are

accessed through the post processor. The results of the simulation are displayed in

graphical and alphanumeric form. It is important to note that this module only reads the

results of the database file and no modifications can be executed here.

5.5 FINITE ELEMENT MODELLING

Assumptions Of The FE Model

The finite element model in metal cutting requires a number ofassumptions in defining

the problem which are as follows

1. The tool is rigid.

2. The chip is a continuous ribbon for ductile materials.

3. The cutting velocity is normal to the cutting edge.

4. The work material is isotropic.

5. The work material is at room temperature.

6. The cutting is performed with no coolants.

The chip formation occurs due to natural flow around the tool tip where the material splits

in to two parts: one flowing parallel to tool rake face (chip) and other flowing under the

tool flank face (machined surface). The automatic remeshing capability helps to create

new mesh, whenever the current mesh gets distorted. Explicit control parameters such as

element size and distribution, element geometric shape and order, creation of nodes on

boundaries vertices, and the node numbering sequence of elements are assumed by the

software itself. The generated nodes match the geometry and the distributions of nodes

are evenly spaced on curves and surfaces regardless of the parametric distortion of the

surface.

Input Requirements for the FE Model is shown in the following diagram



Figure5.2 Input requirements for the FE model

5.6 Test Run Simulation

The following steps are followed to simulate the machining operations in

DEFORM 2D.

Step Involved in simulation

1. The pre-processor of DEFORMA-2D, is used to create tool geometry and work piece

geometry. Later cutting conditions are selected. The tool is meshed with 700 meshes.

2. Trial run without flank wears land inclination.

3. Tool material is selected from library.

4. Work piece material is selected and meshed with 1500 meshes.

5. Near tool tip fine mesh should be created and away corous.

6. After completion of geometry it is submitted to simulation.

7. After process completion pre-post process window is opened.

8. Through which, clearly step wise many variables such as temperature, pressure, strain



etc can be observed.

5.7 Results and Discussion

The tool with different flank wear land inclinations (0º, 2 º, 3 º ,6 º ) are used for

simulation. Initially the flank wear land is kept parallel to cutting direction and

strain effective is determined. The Figure 5.3(a) shows the geometry of the tool is

where in flank wear land is parallel to cutting direction. Figure 5.3(b) shows the

variation of strain in work material and the maximum effective strain deformation

found to be 2.15. The effect of deformation is found to be 0.053452 mm. The

Figure 5.4 (a) and 5.4(b) shows that flank inclination is 2º with respect to cutting

direction. The maximum effective strain found to be is 2.87, which is higher

value then the found when its angle was zero. The Figure 5.5(a) shows that flank

wear land inclination value is 3º and figure 5.5 (b) shows the maximum effective

strain deformation is 3.35.In Figure 5.6 (a) the flank wear land inclination is 6º

and Figure 5.6(b) shows the maximum effective strain deformation is 5.94.From

the above simulation results trial we found that the effective strain value

increases as the flank wear land inclination increases. The presence of flank wear

land on the tool effects on the friction conditions prevailing at the inter face of

tool and work piece. The change in friction condition generates more at the inter

face. The rise in the temperature of the work material allows the more deformation

to takes place below the flank wear land. Because of this the depth of plastic

deformation below the flank wear land increase with the increase in the flank wear

land inclination.



Figure 5.3(a) : Zero wear land i.e. parallel to cutting direction

Figure 5.3(b) : Depth of plastic deformation based on the strain effectiveness

δ = 00 d= 0.0534 mm



Figure 5.4(a) : Flank wear land inclined at 20 with the cutting direction

Figure 5.4(b) :Depth of plastic deformation based on the strain effectiveness

δ = 20 d= 0.096898 mm



Figure 5.5 (a): Flank wear land inclined at 30 with the cutting direction

Figure 5.5 b) :Depth of plastic deformation based on the strain effectiveness

δ = 30 d= 0.11807 mm



Figure 5.6 (a) : Flank wear land inclined at 60 with the cutting direction

Figure 5.6 (b) :Depth of plastic deformation based on the strain effectiveness

δ = 60 d= 0.12587 mm



CHAPTER 6

CONCLUSION

Orthogonal machining experiments are conducted successfully as per the half

factorial matrix of design of experiments. The various flank land inclination are used to

study effect on plastic deformation. The deformation of microstructure clearly indicates

the flank wear land inclination effects on plastic deformation of work under flank wear

land. As inclination increased the depth of plastic deformation also increases. Similarly

trend is also observed with the simulation conducted by DEFORM-2D.

6.1 Future Scope

1. The minute deformation can be visible if SEM techniques are used.

2. By conducting full factorial or response method can give accuracy results.

3. The effects of other parameters as temperature, strain rate, stress, pressure will

affects the plastic deformation too.

REFERENCES

1. Microstructure analysis of aluminum extrusion: grain size distribution in

AA6060, AA6082 and AA7075 alloys, M. Schikorra':', L. Donate, L. 'Iomesani/

and A. E. Tekkaya‘

2. Surface Integrity Analysis in Dry High Speed Turning of Titanium Alloy Ti-

6Al-4V Rajendra Pawar and Raju Pawade, International Conference on

Trends in Industrial and Mechanical Engineering (ICTIME'2012) March 24-25,

2012 Dubai.

3. Effect of cutting condition on tool wear and surface roughness during

machining of inconel 718. Duong Xuan-Truong1,2, Tran Minh-Duc2

4. Surface integrity in finishing turning of Inconel 718, J. Díaz, A. Díaz-Álvarez,

X. Soldani, J.L. Cantero, H. Miguélez,



5. Aluminium Etching Revised: 2013-11-07 Source:

www.microchemicals.com/downloads/application_notes.html

6. Effect of High Speed Cutting Parameters on the Surface Characteristics of

Super alloy Inconel 718, D. G.Thakur*, B. Ramamurthy**, L.

Vijayaraghavan**.

7. Tribology Transactions volume 36 issue3, 1993.(Journal of material shaping

technology, page no 255-265.)

8. The assessment of plastic deformation in metal cutting

Viktor P. Astakhov, S. Shvets

Astakhov Tool Service, Rochester Hills, MI 48309, USA

Received 21 October 2002; received in revised form 10 March 2003; accepted 30

October 2003


http://www.microchemicals.com/downloads/application_notes.html

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