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CHAPTER 2

LITERATURE SURVEY

2.1 INTRODUCTION

The investigation on the machining characteristics such as cutting

force, temperature generation, surface roughness, tool wear and surface

integrity etc., during turning of nickel based super alloys was carried out by

many researchers. The investigation on these machining characteristics are

important as these nickel based super alloys are difficulty to machine material

due to high shear strength, rapid work hardening rate during machining and

low thermal conductivity etc., The machining of these materials are needed to

achieve near-net shape. Many researchers also investigated the machinability

of nickel based super alloys using different cutting tool inserts viz., residual

stress, micro surface hardness, and surface roughness that are generated on

the machined surface, while machining the nickel based super alloys.

In order to predict the machining characteristics during machining,

many researchers modelled the machining parameters using Response Surface

Methodology (RSM) and Artificial Neutal Network (ANN) etc., A lot of

research works in machining nickel based super alloys are also performed

using Finite Element Method (FEA) based simulation using software

packages in the recent years.

34

Of the nickel based super alloys, nimonic C-263 is currently being

applied in the combustion chamber of aircraft engine, due to its unique

resistance to thermal fatigue and creep characteristics. In order to understand

and access the current status of research in the turning of nimonic C-263

alloy, an extensive literature survey relevant to the present investigation is

given below:

2.2 MACHINING OF NICKEL-BASED SUPER ALLOYS

Many researchers carried out experimental investigation during

turning of nickel based super alloys like Inconel 718, Inconel 625, nimonic

75, hastelloy, nimonic C-263 etc., for their machining characteristics. These

materials nowadays used for aerspace applications due to their superior

mechanical properties that are maintained at elevated temperatures.

Choudhury and El-Baradie (1998) presented a general review for

nickel based super alloys on their machinability during turning using different

cutting tool materials. They stated that nickel based super alloys are hard to

machine, because of their rapid work hardening during machining, chip

segmentation resulting in severe tool wear, and their strong tendency to form

a built-up edge by welding to the tool material at high cutting temperatures.

They pointed out that, the notch wear is generated by the adhesion of the

work material to the tool in turning Inconel with ceramic inserts and the flank

wear of the whisker –reinforced alumina and sialon tools are considered as a

diffusion type wear. Fritz Klocke et al (2012) also stated that the nickel based

super alloys generate high cutting forces and temperatures during machining

due to their stability under high mechanical and thermal loads which

adversely affect tool life.

35

Konig and Gerschwiler (1999) stated that nickel based alloys

frequently employed materials for components subjected to high dynamic

stresses at working temperatures of up to 1100°C. These materials are used to

make blades, disks and housing components for hot sections of gas turbines

and jet engines.

Ezugwu et al (2003) discussed about the machinability of aeroengine

alloys during turning operations. They stated that the machining of aero

engine alloys provide a serious challenge for cutting tool materials during

machining due to their unique properties such as high temperature strength,

hardness and chemical wear resistance. The poor thermal conductivity of

these alloys result in concentration of high temperatures at the tool-workpiece

interface. The cutting tool materials such as cemented carbides, ceramics and

cubic boron nitride (CBN) are the frequently used for machining aeroengine

alloys. Further, they reported that the machining of aeroengine alloys at high

speed conditions can be achieved by selecting appropriate tool material and

cooling technology like high pressure coolant, cryogenic cooling and MQL

systems.

Manonukul et al (2002) stated that aero-engine components

operating under in-service conditions are often subjected to a range of

complex cyclic mechanical and thermal loading, leading to combined creep

and cyclic plasticity. They developed physically-based constitute equations

for creep deformations of nickel based C-263 alloy which is a commercial

alloy used for stationary components in aero-engines such as combustion

chambers, casings, liners, exhaust ducting and bearing housings.

Ezugwu and Okeke (2002) investigated the behavior of coated

carbide tools in high speed machining of a nickel based nimonic C-263 super

36

alloy in terms of tool life, surface finish and component forces generated.

They identified that triple layer, TiN/TiCN/TiN, coated carbide inserts gave

longer tool life when machining at higher speed and depth of cut conditions,

whereas the single layer, TiAlN, coated inserts produced better results.

Ankamma et al (2011) described about the nimonic C-263 alloy

that the higher percentage of chromium and molybdenum strengthens the

grain boundaries with the formation of complex metallic carbides, such as

M6C and M23C6, and the high cobalt content (19-21%) strengthens the

material by solution hardenings, which impede the movement of dislocation,

thus inducing higher plastic deformation. Further, the nimonic C-263 alloy

contains a large volume of uniformly distributed ' (Ni3 (Al, Ti)) precipitates,

which causes the main strengthening phase in the solution treated condition of

the material.

Ezugwu (2005) presented an overview on the machining of

difficult-to-cut aerospace superalloys. He pointed out that, to resolve the

machining difficulty and to ensure the functional characteristics with desired

quality, suitable machining conditions and cutting tools are to be established.

2.2.1 Investigation on the machining characteristics in the machining

of Nickel based alloys

Ezugwu and okeke, (2000) found out that machining under lower

feed rate conditions reduces the tool wear rate due to a drop in the component

forces and a reduction in the chip-tool contact time, leading to a reduction in

the temperature and stresses acting on the tool. They have also investigated

the characteristic features of a Nickel based super alloy in the generation of

high component forces during machining. Further, they observed that the

37

component forces are affected by machining parameters (Cutting speed

m/min, feed mm/rev, depth of cut mm), properties of the work material

(Hardness, stress, etc), tool geometry as well as lubrication properties and

their concentration.

Wang et al (2003) introduced a new approach for machining of

nickel based super alloy Inconel 718, in which they combined the traditional

turning with cryogenically enhanced machining and plasma enhanced

machining. Further, they reported that, by joining these two non-traditional

techniques, they found that the surface roughness was reduced by 250%; the

cutting force was decreased by 30-50%; and the tool life was extended up to

170% over conventional machining.

Thakur et al (2008) stated that the nickel based superalloy Inconel

718 has many applications in the engineering industries, due to it unique

proprties such as high oxidation resistance, corrosion resistance even at very

high temperatures. They carried out an experimental investigation in the

turning of Inconel 718 using tungsten carbide (K20) to study the

machinability of this alloy in terms of the cutting forces, cutting temperature

and tool wear. They reported that the machining parameters are to be selected

carefully to achieve lower cutting forces and cutting temperature due to the

typical machining characteristics of the Inconel 718. The cutting force was

observed to decrease with increasing cutting speed due to the high

temperatures generated at the cutting zone.

Fnides et al (2011) conducted an experimental study in hard turning

of AISI H11 hot work steel (50HRC) to determine the statistical models of

cutting forces using Response surface Methodology (RSM). They carried out

the experiments based on L27 orthogonal array. Further, they reported that the

38

depth of cut was the dominant factor affecting cutting force components. The

feed rate influences tangential cutting force more than radial and axial forces.

The cutting speed affects radial force more than tangential and axial forces.

Thakur et al (2009 A) investigated the machinability of super alloy,

Inconel 718 during high speed turning using tungsten carbide insert (K20)

tool. They studied the effect of machining parameters on the responses such

as the cutting force, specific cutting pressure, cutting temperature, tool wear

and surface finish. They identified that, the cutting force magnitude is found

to be higher than the feed force, change in the specific cutting pressure is

attributed to the loss of form stability of the cutting edge. The optimum

surface finish was found in the cutting range of 45-55m/min cutting speed,

0.08mm/rev feed rate and 0.50mm depth of cut and also they observed that

the main type of wear is abrasion, microchipping and plastic deformation.

Ezugwu and okeke (2000) investigated the performance of PVD

coated carbide inserts during machining of nimonic C-263 alloy at high speed

conditions in terms of cutting force, tool wear, surface finish.They reported

that, the TiN/TiCN/TiN coated carbide inserts with positive, honed and

chamfered edge was found to be suitable for machining nimonic C-263 alloy

and also they identified the failure modes in machining nimonic C-263 alloy

with the coated carbide inserts include flank wear, notching, burr formation,

excessive chipping and catastrophic failure and also they reported that the

feed rate was identified as significant factor in affecting the surface finish,

tool wear and the generation of cutting force.

Pawade et al (2007) presented an experimental investigation into

the effect of various process and tool-dependent parameters on cutting force,

39

an indirect measure of machined surface integrity besides a microstructural

analysis of the machined surface damage, in high speed machining of super

alloy Inconel 718 using PCBN inserts. They reported that, the magnitude of

cutting force was two to three times higher than that of other force

components. The generation of larger cutting forces produce poor surface

finish as well as extensive surface damage.

Arunachalam et al (2004 B) stated that the considerable attention

has been given to use of ceramic cutting tools for improving productivity in

the machining of heat resistant super alloys (HRSA). However, because of

their negative influence on the surface integrity, ceramic tools are generally

avoided particularly for finishing applications. They dealt with the residual

stresses and surface finish components of surface integrity when machining

(facing) age hardened Inconel 718 using two grades of coated carbide cutting

tools specifically developed for machining HRSAs. Finally, they suggested

that coated carbide cutting tool inserts of round shape, chamfered cutting edge

preparation, negative type and small nose radius (0.8 mm) and coolant will

generate primarily compressive residual stresses.

The effects the effects of cutting tool coating material and cutting

speed on cutting forces and surface roughness were investigated by Muammer

Nalbant (2007) on machining nickel based super alloy Inconel 718 in dry

environments. They reported that there was an increment-decrement

relationship between cutting speed and cutting force. The minimum cutting

force was obtained with SCMT 120412 type multicoated Al2O3 carbide tools

while maximum cutting force with RCMT 120400 type single coated TiN

carbide tools. Also, they observed that an increasing relation between cutting

speed and arithmetic average surface roughness as well as between coating

number and average surface roughness. Minimum average surface roughness

40

was determined with single layer (TiN) coated cemented carbide tools while

maximum average surface roughness was observed with multicoated

Al2O3tools.

Du Jin Zhanquiang Liu (2012) Investigated the surface integrity of

nickel based super alloy FGH95 in terms of surface roughness, microhardness

and white layer during milling operations. The influence of the cutting speed

on chip morphology was also investigated. He reported that the surface

integrity and chip morphology are very sensitive to the cutting speed. The

surface roughness has very little variations at below 2,400 m/min and the

value of surface roughness is high for the range of 2,800-3,600 m/min cutting

speed. The degree of chip segmentation increases with the increases of cutting

speed.

Bin Zou et al (2011) used Al2O3/TiN-coated tungsten carbide tools

for finish turning of NiCr20TiAl nickel-based alloy under various cutting

conditions. They investigated the cutting forces, Surface integrity, tool wear

and inter-diffusing, transferring of elements between Al2O3/TiN-coated

tungsten carbide tool and NiCr20TiAl nickel-based alloy during machining.

They reported that the flaking of coating matrix of tools and the heavier

plucking, cavities of the machined surface were induced by the higher cutting

forces at higher cutting parameters. The recommended the cutting speed of 60

m/min, feed rate of 0.15 mm/rev and 0.40 mm depth of cut in view of surface

quality and tool wear.

Altin et al (2007) investigated the influence of the cutting speed on

tool wear and tool life in turning Inconel 718 nickel based super alloy using

silicon nitride based and whisker reinforced ceramic tools.They stated that the

crater and flank wears are usually dominant wear types in ceramic square type

41

(SNGN) inserts while flank and notch wear are dominant in round type

(RNGN) inserts. Further, they reported that square type inserts showed good

performance compared to round type inserts at low cutting speed and they

recommended the tool inserts for the machining of Inconel 718 are square

type KYON 4300 insert at low cutting speeds whilst round type KYON 4300

at high cutting speeds.

Ezugwu et al (2002) analyzed the effect of machining parameters

on flank wear during turning of nimonic C-263 alloy and they have reported

that increasing the cutting speed and depth of cut results in accelerated flank

wear.

Li et al (2002) studied the influence of the machining parameters

on tool wear and tool life during turning of Inconel using coated carbide and

ceramic inserts. They reported that at lower speed (120m/min), the inserts are

prone to depth-of-cut notching, and a transition was observed at about 240

m/min. At increasing the speed to 300 m/min leads to a reduction in depth-of-

cut notching and an increase in nose and flank wear. Further, they reported

that PVD coated carbides KC7310 are more suitable for cutting Inconel 718

than CVD coated carbides and ceramic inserts of KY2000.

Ezugwu Okeke (2002) investigated the behavior of coated carbide

tools in high speed machining of a nickel based super alloy C-263. They

reported that the machining of C-263 alloy with PVD coated carbide offers

greater advantage due to its higher resistance to characteristic wear

mechanisms encountered.

Abhay Bhatt et (2010) experimentally investigated the wear

mechanisms of uncoated and coated carbide tools in turning the nickel based

42

super alloy Inconel 718, in which they have reported that abrasive and

adhesive wear were the most influenced wear mechanisms. The triple layer

CVD coated tools exhibited the highest wear resistance at high cutting speeds

and low feed rates and the uncoated tools outperformed the single and multi

layer coated tools in the low range of cutting speeds and intermediated feed

rates.

Devillez et (2007) investigated the influence of different coated

tools and cutting conditions on the machinability of Inconel 718 during

turning, in which they observed that the cutting force magnitude is higher at

low cutting speed and high feed rate. They have also observed the dominant

wear modes such as welding and adhesion of workpiece material onto the

cutting tool faces. The work material adheres to the cutting edge to form a

built-up-edge (BUE), and a built-up-layer (BUL) on tool faces. They have

reported finally that the AlTiN seems to be best coatings.

Gatto and Iuliano (1994) performed high speed turning on a heat

resistant alloy Inconel 718, using SiC (20%) whiskers reinforced ceramic

tools. They analyzed and modelled analytically the tool wear mechanisms,

chip formation process. Further, they observed that the variable wear

mechanisms along the tool-chip contact length that were attributed to

variations in plastic deformation energy.

Ezugwu and Tang (1995) carried out experimental investigation on

G-17 cast iron and a nickel base Inconel 718 alloy during turning operations

using round and rhomboid-shaped pure oxide (Al2O3 + ZrO2) and mixed oxide

Al2O3+ TiC) ceramic tools. They reported that the shape and geometry of

cutting tools play an important role in determining the nature of machined

surfaces. The round inserts produced a better surface finish than rhomboid

43

inserts. Prolonged machining with these two ceramic inserts resulted in an

increase in the hardness values of the work materials. This increase was more

pronounced with Inconel 718 due to its high rate of work hardening, increased

compressive stresses and plastic deformation.

Kadirgama et al (2011) described the wear mechanism and tool life

when machining nickel based superalloy Hastelloy C-22HS with coated

carbide. They conducted experiment using four different cutting tool materials

under wet condition – namely, Physical Vapor Deposition (PVD) coated with

TiAlN; TiN/TiCN/TiN; Chemical Vapor Deposition (CVD) coated with

TiN/TiCN/Al2O3; and TiN/TiCN/TiN – to study the tool behavior, in terms of

wear and tool life. They observed tool failure modes and wear mechanism

like Flank wear, chipping, notching, plastic lowering at cutting edge,

catastrophic and wear at nose to be the predominant tool failure for the four

types of cutting tools, especially with CVD tools. Attrition/adhesion,

oxidation and built-up edge (BUE) were the wear mechanisms observed in all

cutting tools. Finally, they suggested that the PVD cutting tools performed

better than CVD cutting tools, in terms of tool life.

Senthilkumar et al (2006) conducted machining studies on

hardened martensitic steel (HRC 60) to analyse the effect of tool wear on tool

life of alumina ceramic cutting tools. The tool wear such as flank wear, crater

wear and notch wear were noted under different cutting conditions.They

developed wear model for the prediction of flank wear, crater wear and notch

wear using multi regression analysis and the tool life of the alumina-based

ceramic cutting tools were evaluated from these tool wear models. Furthe they

stated that, the tool wear affects dimensions and surface quality of the

workpiece and is one of the important criteria in determining the tool life.

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Vigneau and Boulanger (1982) stated that the machining of nickel

base alloys can be made by ceramic tools with metal removal rate four times

greater than carbide tools. However, among twenty ceramic grades tested,

only two have a sufficient strength to be used in industrial conditions, the first

is alumina base containing 30 % titanium carbide, the second is a sialon

material. Further they stated that the tool life increased four times with a

special edge preparation depending on the wear mechanism. The machining

of the nickel base alloy with ceramic has not any effect on the fatigue strength

of the parts.

Bushlys et al (2012) stated that the nickel based super alloy Inconel

718, is currently machined with cemented carbide tools at low speed (60

m/min) due to its unfavourable mechanical and thermal properties. They

attempted to study the machinability of Inconel 718 in terms of tool life, tool

wear and surface integrity using uncoated and coated PCBN tools aiming on

increased speed and efficiency. They found out that the protective function of

coating, increasing tool life up to 20 %, is limited to low cutting speed and the

EDX and AFM analyses suggested dominance of chemical and abrasive wear

mechanisms. The residual stress analysis shown advantageous compressive

surface stresses.

Costes et (2007) stated that the demand for increasing productivity

when machining heat resistant alloys has resulted in the use of new tool

materials such as cubic boron nitride (CBN) or ceramics. The grade of these

tools was not optimized for superalloys. They made investigation to show

which grade is optimal and what the wear mechanisms are during finishing

operations of Inconel 718. The result shown that a low CBN content with a

ceramic binder and small grains gives the best results. The dominant wear

45

mechanisms such as adhesion and diffusion due to chemical affinity between

elements from workpiece and insert were observed.

Thakur et al (2012) studied the relationship of degree of work

hardening and tool life as a function of cutting parameters like cutting speed,

feed rate, depth of cut, untreared tungsten carbide and postcryogenic-treared

tool. They reported that a significant performance in tool life was observed

due to cryogenic treatment given to tungsten carbide tool and also they said

that the optimized machining parameters minimize work hardening

characteristics and improve the tool life in high-speed machining of Inconel

718.

Field et al (1989) stated that the characteristics of machined surface

such as surface roughness and surface damage have significant influence on

fatigue life, creep, corrosion, and dimensional accuracy of a machined

component.

Outeiro et al (2008) investigated the generation of the residual

stresses during turning of Inconel 718 and AISI 316L using coated and

uncoated cemented carbide tools. They reported that higher residual stresses

are generated when machining with the uncoated tool than the coated tool.

Also, higher residual stress values were observed on the transient surface than

on the machined surface.

Guo et al (2009) reviewed the surface integrity characterization,

especially the characteristics of residual stresses produced in machining of

hardened steels, titanium and nickel based superalloys. They also discussed

the interrelationship among residual stresses, microstructures and tool-wear.

They stated that the residual stresses are classified into two kinds: they are

46

termed as macro residual stress (which existed in the order of hundred

microns in the subsurface) and micro residual stress (which formed at a

distance of few grains) and the residual stress is identified as the main factor

among the surface integrity parameters which influences the product

performance such as fatigue life, creep, corrosion, and dimensional accuracy

of a machined component.

Kitagawa et al (1997) investigated the performance of ceramic

tools in high speed machining of super alloy Inconel 718. The study indicated

that the tool wear developed more due to abrasive process than to a thermally

activated mechanism.

Chakraborty et al (2000) used commercially available tungsten

carbide (WC)-based tools and oxide-based ceramic cutting tools such as

alumina (A12O3) and zirconia toughened alumina (ZTA) during machining

hardened steel. They reported that the ceramic tools exhibited superior

performance as compared to the WC tools, especially at higher machining

speeds, both in terms of tool life and surface finish of the work-piece. They

observed severe crater wear in the WC tools, whereas, only a small amount of

edge chipping and nose wear occurred in the ceramic tools during high speed

machining.

Li (2009) investigated the residual stress distributions introduced in

a new generation nickel-based super alloy RR1000 by surface finish turning

using round and rhombic, coated and uncoated inserts, new and worn tools

and chipped tool. The concluded that compared with the rhombic insert, the

round insert generated a slightly higher tensile stress up to 1500 MPa and

turning of this alloy using chipped tool introduced a large compressive radial

47

stress field with the maximum value reaching -1000 MPa and the penetration

depth 400µm.

Aucote (1986) used range of sialon compositions to machine the

nickel-based alloy incoloy 901 to observe the flank wear and tool life. They

reported that the tool life and flank wear resistance increase with -sialon than

-sialon. Also, they stated that at high cutting speed one of the tool wear was

rake face flaking and the resistance to this mechanism was found to increase

with tool material grain size and at lower cutting speeds depth-of-cut notch

wear was of major importance and resistance to this wear was found to

decrease with increasing grain size.

Arunachalam et al (2004 A) investigated the residual stresses in the

machining of age-hardened Inconel 718 material using cubic boron nitride

(CBN) and ceramic cutting tools. The results showed that mixed ceramic

cutting tools induce residual tensile stresses of a much higher magnitude than

CBN cutting tools. The residual stresses and surface roughness generated by

the CBN cutting tools are more sensitive to cutting speeds than the depth of

cut.

Berruti et al (2009) investigated the residual stresses generated into

longitudinal and tangential directions during turning of the nickel based

superalloy Inconel 718 using carbide inserts. They observed that the residual

stresses are tensile on the surface and compressive below the surface. Further,

they stated that at higher cutting speed and feed rates produce higher tensile

stresses and the surface stresses in longitudinal direction are more sensitive to

the variation of the machining parameters than the stresses in the tangential

direction.

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Durul Ulutan and Tugrul Ozel (2011) reviewed the machining

induced surface integrity in Titanium and Nickel based superalloys. The

review identified that the residual stresses, white layer and work hardening

layers, as well as microstructural alterations, as being important surface

integrity problems, to improve the surface qualities of the end products. They

reported that the main surface defects during machining of nickel based

superalloys are surface drag, material pull-out/cracking,feed marks, adhered

material particles, tearing surface,chip layer formation, debris of microchips,

surface plucking,deformed grains, surface cavities,slip zones,laps (material

folded onto the surface) and lay patterns. Also, they stated that the surface and

immediate sub-surface of the material becomes harder due to work hardening

occurring because of high mechanical and thermal loads on the workpiece

during machining of the nickel based superalloys.

Veldhuis et al (2010) investigated the surface integrity in the

turning of nickel-based ME 16 super alloy using a TiAlN coated carbide

insert. They analyzed the formation of a white layer on the machined surface

under different cutting conditions. They found that a 2-4 µm thick white layer

forms during turning of ME 16 superalloy. Further, they stated that these

layers contains a high amount of aluminium, enriched by chromium and

tungsten and under specific cutting conditions, the structure of the white layer

transforms into -alumina and this could negatively affect surface integrity of

the machined parts and cutting tool life at higher cutting speed.

Subhas et al (2000) studied the plastic deformation characteristics

during turning of nickel based superalloy Inconel 718, and also they

investigated the effect of machining parameters (speed, feed, depth of cut,

rake angle, and tool nose radius) on responses such as machined surface,

subsurface, and dimensional instability. Further, they stated that the negative

49

rake angle increases and a positive rake angle decreases the residual stresses,

and as the chip tool contact length increases, cutting force and frictional force

increases; therefore, the controlled chip-tool contact length reduces residual

stresses compared to natural chip tool contact length. Also, they developed an

empirical relationship for the prediction of surface residual stresses,

dimensional instability, surface finish and tool life in machining Inconel 718

superalloy.

Sharman et al (2006) evaluated the effects of varying cutting tool

materials, the geometry, wear level and machining parameters on the surface

integrity while turning the nickel based superalloy Inconel 718. They reported

that the largest influence on surface integrity was tool wear and machining

with wornout tool resulted in greater microstructural deformation,

microhardness changes, and high surface tensile stresses. Further, they stated

that the controlling the level of tool wear is crirical and to produce consistent

surface integrity, tool wear should be kept to a minimum.

2.3 EXPERIMENTATION USING TAGUCHI’S ORTHOGONAL

ARRAY

Taguchi (1990) stated that the Taguchi’s experimental design using

orthogonal array is a well known technique used for experimentation, which

in turn reduces number of experiments. Ross (1996) stated that the orthogonal

array is used to study many design parameters simultaneously and the

orthogonal arrays are being used widely for conducting experiments

economically. An orthogonal array is the matrix of numbers of numbers

arranged in columns and rows. The use of orthogonal arrays gives minimum

number of experiments and does not have any mixed levels. Taguchi method

is capable of establishing an optimal design configuration, even when

50

significant interactions exist between and among the control variables. The

Taguchi method can also be applied to design factorial experiments and

analyzing their outcomes.

The objective of Taguchi’s quality loss function is quantitative

evaluation of quality loss due to functional variation. A quality characteristic

is the objective of interest of a product or process. It is called fundamental

characteristic. The difference between the functional value and objective

value is emphasized and identified as the loss function. There are three

categories of quality characteristic in the analysis of S/N ratio, (i) the-lower-

the-better, (ii) the-higher-the-better and (iii) the-nominal-the-better.

Regardless of the category of the quality characteristic, process parameter

settings with the highest S/N ratio always yield the optimum quality with

minimum variance (Sungh and Park 1996).

Chua et al (1993) stated that the optimimal cutting conditions are to

be determined using reliable mathematical models representing the machining

conditions of a particular work-tool combination. Further, they stated that

such mathematical models require detailed planning and proper analysis of

experiments.

Nalbant et al (2007) presented an application of the parameter

design of the Taguchi method in the optimization of the machining

parameters for surface roughness in turning AISI 1030 steel bars using TiN

coated tools. They stated that the parameter design of the Taguchi method

provides a simple, systematic and efficient methodology for the optimization

of the cutting parameters.

51

Thakur et al (2009 B) attempted to suggest the Taguchi

optimization technique to study the machinability of Inconel 718 using

cemented tungsten carbide (K20) cutting tool. They developed regression

model to correlate the machining parameters with the responses such as

cutting force, cutting temperature and tool life. Also, they studied the effect of

high speed cutting parameters on the tool wear mechanism and chip analysis.

Xue Ping et al (2007) adopted Taguchi method for the conduction

of the experiment to investigate the surface integrity (surface roughness,

residual stress, and thermal damage layer) of hardened bearing steel in hard

turning. They stated that the surface finish, metallurgical change and residual

stresses are the most important concern for the machined component. They

reported the effect sequence of hard turning parameters and optimized

combination of machining parameters to achieve superior surface finish,

residual stresses.

El-Tamimi and Ei-Hossainy (2008) investigated the machinability

of austenitic AISI 302 stainless steel under oblique cutting. They used

factorial experiment and analysis of variance (ANOVA) technique to evaluate

the influence of the machining parameters on the responses such as surface

rpoghness, material removal rate and tool life. Also, they developed empirical

equations for all the responses using Response Surface Methodology (RSM).

Ibrahim et al (2010) used Taguchi optimization methodology to

optimize the machining parameters such as cutting speed, feed rate, depth of

cut and tool grade in turning of Ti-6Al-4V ELI using coated and uncoated

cemented carbide tools. The results shown that the feedrate and type of tool

have the most significant effect on the surface roughness with contributions of

47.15% and 38.88% respectively. The optimal condition for the surface

52

roughness was at cutting speed of 95 mm/min, feed rate of 0.15 mm/rev,

depth of cut of 0.10 mm and using tool grade of KC9225.

Konda et al (1999) stated that the design of experiment is one of

the many problem-solving quality tools that can be used for various

investigations such as finding the significant factors in a process, the effect of

each factor on the outcome, the variance in the process, troubleshooting the

machine problems, screening the parameters, and modeling the processes.

Further, they described the experimental design technique and multi-objective

optimization problem of wire electrical discharge machining process for

machining beryllium copper alloys.

Yang and Tarng (1988) used Taguchi method to find out the

optimal cutting parameters in turning of S45C steel bars. They employed an

orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance

(ANOVA) to investigate the machining characteristics of S45C steel bars

using tungsten carbide cutting tools.

Ilhan Asilturk et al (2011) optimized the machining parameters

based on the Taguchi method to minimize the surface roughness (Ra and Rz)

in turning of AISI 4140 (51 HRc) with coated carbide cutting tools. They

applied the statistical methods of signal-to-noise (SNR) and the analyse of

variance (ANOVA) to investigate the effects of machining parameters on

surface roughness. The results indicated that the feed rate has the most

significant effect on RA and Rz followed by the two factor interactions of the

feed rate-cutting speed and depth of cut-cutting speed.

Palanikumar et al (2006) conducted experiment based on design of

experiment to assess the influence of the machining parameters on turning

53

GFRP composities. They developed response model to predict the surface

roughness and also they reported that the surface roughness plays an

important role in many areas and is a factor of great concern in the evaluation

of machining accuracy.

Many researchers have used orthogonal arrays for conducting

experiments and used the Response Surface Methodology (RSM) and analysis

of variance (ANOVA) approaches for the prediction and analysis on the effect

of machining parameters with the responses (Paluo Davim et al 2008, Kwak

2005, Gaitonde et al 2008, Palanikumar 2008 and Mata et al 2010).

2.4 MODELLING OF MACHINING PARAMETERS USING

RESPONSE SURFACE METHODOLOGY (RSM)

Montgomery (2007) stated that the Response Surface Methodology

(RSM) is a collection of mathematical and statistical technique that is useful

for modelling and analysing of problems in which a response of interest is

influenced by several variables and the objective is to optimize the response.

Dilbag singh and Venkateswara Rao (2007) developed

mathematical model for the surface roughness in the finish hard turning of the

bearing steel (AISI 52100) using Response Surface Methodology (RSM).

Further , they determined the effects of cutting conditions and tool geometry

on the surface roughness in the finish hard turning of the bearing steel (AISI

52100) using mixed ceramic inserts made up of aluminium oxide and titanium

carbonitride (SNGA), having different nose radius and different effective rake

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angles. They reported that the feed rate was the dominant factor determining

the surface finish followed by nose radius and cutting velocity.

Choudhury and El-Baradie (1999) carried out an experimental

investigation in turning Inconel 718 using coated and uncoated carbide inserts

under dry conditions. They developed response model for tool life, surface

roughness and cutting force utilizing factorial design of experiment and

Response Surface Methodology. Further, they identified the feed rate is the

significant parameter in affecting the tool life, surface roughness and the

generation of cutting forces for both coated carbide and uncoated carbide

inserts.

Lalwani et al (2008) investigated the effect of machining

parameters such as cutting speed, feed rate and depth of cut on cutting forces

(feed force, thrust force and cutting force) and surface roughness in finish

hard turning of MDN250 steel using coated ceramic tool. The machining

experiments were conducted based on response surface methodology and

sequential approach using face centered central composite design and they

developed regression model for the responses.

Sahin and Motorcu (2004) developed a theoretical model based on

Response Surface Methodology to predict the surface roughness in turning of

mild steel using coated carbide tools. The established equation shown that the

feed rate was main influencing factor on the surface roughness.

Noordin et al (2004) investigated the performance of a multilayer

tungsten carbide tool using Response Surface Methodology (RSM) in turning

AISI 1045 steel. They developed mathematical models for the prediction of

cutting force and surface roughness and they identified that the feed rate was

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the most significant factor that influence the cutting force and surface

roughness.

Singh and Kumar (2003, 2004, and 2005) applied Taguchi’s

technique for optimizing the surface finish, tool wear, cutting force and power

consumed in turning operations for machining En24 steel with titanium

carbide-coated tungsten carbide inserts.

Suresh et al (2002) carried out an experiment to determine the

effect of machining parameters in turning mild steel using TiN-coated

tungsten carbide insert. They developed a second order mathematical model

in terms of the machining parameters for surface roughness prediction using

Response Surface Methodology (RSM). Also, they attempted to optimize the

surface roughness prediction model using Genetic Algorithm (GA).

Eyup Bagci and Birhan Isik (2006) designed the experiments based

on statistical three level full factorial experimental design technique for

machining the unidirectional glassfibre reinforced plastics (GFRP), using

cermet tools. They developed a model for the prediction of surface roughness

using artificial neural network (ANN) and response surface methodology

(RSM). Further, they compared ANN and RSM models for GFRPs turned

part surfaces for accuracy and computational cost.

Palanikumar (2007) conducted an experiment based on four factors

five level central composite, rotatable design matrix for machining GFRP

composite. He developed a mathematical model for the prediction of surface

roughness using response surface methodology (RSM).Analysis of variance

(ANOVA) was used to check the validity of the model.

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Pawade et al (2008) investigated the effect of the machining

parameters and cutting edge geometry on surface integrity during the turning

of the nickel base Inconel 718 alloy in terms of residual stress, microhardness,

and degree of workhardening. They conducted the experiments based on the

Taguchi’s method L27 orthogonal array, and the significant machining

parameters and their interaction effects were all identified with the help of the

analysis of variance (ANOVA). Further, they found that the highest cutting

speed, lowest feed rate and the moderate depth of cut coupled with the use of

honed cutting edge ensured the induction of compressive residual stresses in

the machined surfaces.

2.5 MODELLING OF MACHINING PARAMETERS USING ANN

A neuron is the basic element of neural networks, and its shape and

size may vary depending on its duties. Analyzing a neuron in terms of its

activities is important, since understanding the way it works also helps us to

construct the ANNs. An ANN may be seen as a black box which contains

hierarchical sets of neurons (e.g., processing elements) producing outputs for

certain inputs. Each processing element consists of data collection, processing

the data and sending the results to the relevant consequent element. The

whole process may be viewed in terms of the inputs, weights, the summation

function, and the activation function.

Massie (2001) stated that neural networks are massively parallel

processors that have the ability to learn patterns through a training experience.

Because of this feature, they are often well suited for modeling complex and

non-linear processes. Further, they explained that the determination of

transfer and summation function is made depending on the nature of the

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problem and the transfer function generally consists of algebraic equations of

linear or nonlinear form.

Hagan et al (1996) described that the use of a nonlinear transfer

function makes a network capable of storing nonlinear relationships between

the input and the output and the commonly used function is sigmoid function

because it is self-limiting and has a simple derivative.

Abdullah Kurt (2009) investigated the effect of the cutting

parameters (speed, feed rate, depth of cut) on the cutting forces and cutting

tool stresses (normal, shear, Von Mises) in the machining of the nickel based

Inconel 718 alloy, by means of the finite element method using ANSYS

software.Further, they developed an artificial neural network (ANN) model

using the back propagation algorithm to analyse and predict the cutting tool

stresses.

Tugrul Ozel et al (2007) investigated the surface finish and tool

flank wear in finish turning of AISI D2 steels (60 HRC) using ceramic wiper

(multi-radii) design inserts. They developed model using regression analysis

and artificial neural network (ANN) for the prediction of surface finish and

flank wear. Also, they reported that the neural network based prediction of

surface roughness and tool flank wear are carried out and compared with a

non-training experimental data. These results shown that the neural network

models are suitable to predict tool wear and surface roughness for a range of

cutting conditions.

Ezugwu et al (2005) developed artificial neural network (ANN)

model for the analysis and prediction of the relationship between cutting and

process parameters in high-speed turning of nickel-based Inconel 718 alloy

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using triple layered (TiCN/Al2O3/TiN) PVD-coated carbide (K 10) inserts.

They considered seven output parameters of the model such as cutting force,

axial force, spindle motor power consumption, surface roughness, average

flank wear, maximum flank wear and nose wear. Finally, they concluded that

a very good performance of the neural network, in terms of aggrement with

experimental data was achieved and they suggested that the ANN model can

be used for the analysis and prediction of the complex relationship between

cutting conditions and the process parameters in metal cutting operations.

Umbrello et al (2007) presented a predictive model based on the

artificial neural network (ANN) approach on hard turning of 52100 bearing

steel.They stated that the prediction errors ranged between 4 and 10 % and

this ANN approach based regression approach provided a robust framework

for forward analysis.

Nihat Tosun and Latif Ozler (2002) developed regression model

and an ANN model using backpropagation (BP) algorithm for the prediction

of tool life in machining manganese steel. They compared the experimental

data with both the regression analysis results and the estimated value of ANN.

Further, they stated that ANN method seems to have the prediction potential

for non-experimental patterns and this methodology consumes lesser time

giving higher accuracy.

Latha and Senthil Kumar (2010) used neural network based on

back-propagation (BP) algorithm with two hidden layers for the modelling of

delamination factor in drilling glass fibre reinforced plastic (GFRP)

composites. They used Fifty-four sets for training and 18 sets of data for

testing. The result shown that the well trained BP network model predict the

delamination in drilling of GFRP composites.

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Raganathan et al (2010) carried out turning operations on stainless

steel (Type 316) using tungsten carbide (WC) cutting tool insert and the

experiments were designed based on stastical three level full factorial

experiment design techniques. Further, they modelled the machining

parameters using Response Surface Methodology and an optimisation tool

Neurointelligence evaluation software.

Tugrul Ozel and Yigit Karpat (2005) developed neural network and

regression models for the prediction of surface roughness and tool flank wear

in finish turning of AISI 52100 steel using cubic boron nitride (CBN) inserts.

They compared the neural network models with regression models and they

found that the neural network models were capable for better prediction for

surface roughness and tool flank wear.

2.6 MODELLING OF MACHINING PARAMETERS USING FEA

Finite Element Method (FEM) permits the prediction of cutting

forces, stresses, tool wear, and temperatures of the cutting process so that the

cutting tool can be designed. With this method the best cutting parameters are

determined. However, accuracy of the obtained results with finite element

method depends mainly on the accuracy of the input values so it is of extreme

importance to understand how the input data affect the prediction of the Finite

Element Models (FEMs) analysis. Also, accurate physical, mechanical and

thermal modelling of deformation and solidification behaviour and the

interface conditions are essential to the optimal use of these advanced models

for industrial applications which tend to be difficult in formulation

Maranhao and Paulo Davim (2010) modelled the thermo

mechanical behavior when machining a stainless steel (AISI 316) using FEA

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package AdvantEdge. The also evaluated the influence of friction coefficient

in the tool-chip interface on cutting and feed forces, cutting temperature,

plastic strain, plastic strain rate, maximum shear stress and residual stresses.

They concluded that the friction coefficient has strong effect in the cutting

process and is crucial to obtain valuable predictions when machining with the

FEM model.Also, they pointed out that to improve the surface quality and

integrity, the working parameters should be selected properly; otherwise, the

cutting tool wears quickly or gets broken abruptly.

Chandrakanth shet, Xiaomin Deng (2000) analyzed the orthogonal

metal cutting process with finite element method under plane strain

conditions. They modelled the frictional interaction along the tool-chip

interface with a modified coulomb friction law. Finite element solutions of

temperature, stress, strain and strain rate fields were obtained for a range of

tool rake angle and friction coefficient values. Also, they reported specific

modelling techniques for simulating the orthogonal metal cutting process

using a general-purpose finite element computer code.

Guoquin Shi et al (2002) developed computional procedure for

simulating orthogonal metal cutting using a general-purpose finite element

computer code.They performed series of finite element simulations, in which

a modified coulomb friction law was used to model the friction along the tool-

chip interface and a finite element nodal release procedure was adopted to

simulate chip separation from the workpiece. A tool rake angle ranging 15º to

30º and a friction coefficient ranging from 0.0 to 0.6 were considered in the

simulations. Further, they reported that the general-purpose finite element

code ABAQUS can be used to simulate the orthogonal metal cutting process

through a poper combination of user options and subroutines. Chip formation,

the tool-chip contact length, the shear angle of the primary shear zone, the

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reuired tool cutting force and the maximum temperature rise all depend

strongly on the coefficient of friction and on the rake angle.

Outeiro et al (2008) investigated the influence of the cutting

process parameters on machining performance and surface integrity generated

during turning of Inconel 718 and austenitic stainless steel AISI 316L using

coated and uncoated carbide tools. They developed three dimensional Finite

Element Model using DEFORM 3D software based on lagrangian implicit

code for the prediction machining performance and surface integrity. The

predicted values were compared with measured results.

The chip shape, insert and workpiece temperature were predicted

by Bareggi et al (2007) in turning of AISI 1020 steel using Finite Element

Model. They used commercial software DEFORM 3D with incremental

lagrangian formulation.

Ceretti et al (2000) presented the simulation of the three

dimensional cutting operations using lagrangian formulation with continuous

remeshing. They modelled particular orthogonal and oblique cutting

operations and compared the simulated results with experimental data found

in the literature.

Grzesik et al (2005) created FEM simulation model to obtain

numerical solutions of the cutting forces, specific cutting energy and adequate

temperatures occurring at different points through the chip/tool contact region

and the coating/substrate boundary for a range of coated tool materials and

defined cutting conditions. The various thermal simulation results were

obtained and compared with the measurements of the average interfacial

temperature and discussed in terms of various literature data.

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Li et (2008) introduced Finite Element Method (FEM) to study the

chip formation process when machining nickel-based super alloy

GH80A.They modelled saw-tooth with ASB (adiabatic shear bond) and

periodic fracture under different cutting speeds. They compared the chip

morphology between the FEM and experiment and they observed that the Gs

(degree of segmentation) of FEM matches well of the experiments; however,

Pc (pace of tooth) does not match exactly but has the same trend. Further,

they stated that the Johnson Cook (JC) model is suitable for modelling

materials, which are having high strain, strain rate, strain hardening and non-

linear material properties.

Sool et al (2004) developed 3D finite element model to simulate

turning of Inconel 718 super alloy using ABAQUS/Explicit, employing

experimentally determined mechanical properties at elevated strain rates and

temperatures. The cutting force predicted by the Finite Element Model

showed good aggrement with experimentally measured data with an error of

less than 6%; however the feed forces were under predicted by 13-29% which

was probably due to an inadequate friction description. Further, they stated

that the simulation was unable to predict chio morphology due to the lack of a

suitable sub-routine to properly define the onset and propagation of shear

localisation and fracture along the shear plane.

Hendri et al (2010) simulated 3D finite element model using

DEFORM 3D to study the effect of rake angle on cutting force, stress, strain

and temperature on the edge of carbide cutting tool in the orthogonal cutting

process. They stated that the increase in the rake angle from negative to

positive angle, causing the decrease in the cutting force, effective stress and

total von Misses strain. Increasing the rake angle caued the higher

temperature generated on the edge of the carbide cutting tool and resulted in

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bigger contact area between the clearance face and the workpiece,

consquently caused more friction and wear. Further, they reported that the

biggest deformation (chip deformation) was occurred in the primary

deformation zone, followed by the secondary deformation zone. Therefore the

highest stress was also occurred in the sliding region, while the heat generated

in the sticking region caused the workpiece material to adhere with the tool.

Later, it was sheared which resulted the high frictional force and generated

higher temperature in the sliding region.

Mitrofanov et al (2005) modelled 2D and 3D thermomechanically

coupled FE model of both ultrasonically assisted turning (UAT) and

conventional turning of elasto-plastic materials to study the influence of

lubrication and cutting parameters on the process performances. Further, they

stated that the mechanical behaviour of Inconel 718 at high strains, strain

rates and elevated temperatures can be adequately described by the Johnson

Cook (JC) model, accounting for the strain-rate sensitivity that was employed

in simulations for the aged Inconel 718.

Yung-Chang Yen et al (2004) stated that, in metal cutting the tool

wear on the tool-chip and too-workpiece interfaces is strongly influenced by

the cutting temperature, contact stresses and relative sliding velocity at the

interface. They reported their research into three parts. In the first part, tool

wear model for the specified tool-workpiece pair was developed using a

calibration set of tool wear cutting tests in conjunction with cutting

simulations. In the second part, modifications were made to the commercial

FEM code used to allow tool wear calculation and tool geometry updating. In

the third part includes the experimental validation of the developed

methodology.

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Yahya Dogu et al (2006) developed Finite Element Model to

determine the temperature generated in the primary deformation zone, the

secondary deformation zone and along the sliding frictional zone at the tool-

tip interface. The developed FEM model, estimates the temperature as a

function of hear generation.

Tugrul Ozel (2009) presented 3D finite element model using

DEFORM 3D in turning of AISI 4340 alloy steel to predict the chip

formation, forces, stresses, temperatures and tool wear on uniform and

variable edge design tools of PcBN inserts.They used implicit lagrangian

computional routine with continuous adaptive remeshing. The workpiece

were modelled as rigid-perfectly plastic material where the material

constitutive model is represented with Johnson-cook material model. The

cutting tool was modelled as a rigid body which movies at the specified

cutting speed by using 125,000 elements with very fine mesh density. Further,

they stated that the variable micro-geometry insert edge design reduces the

heat generation and stress concentration along the tool cutting edge

significantly and induced less plastic strain on the machined workpiece.

Salio et al (2006) developed a finite element model using the

general purpose nonlinear finite element code MSC Marc for turning of

Inconel 718 alloy turbine disks to predict the stresses, strain, temperatures,

chip shape and residual stresses. The modelled results were compared with

the results of analytical models with a perfectly rigid plastic material and the

real material Inconel and the FEM predicted results found to be good

agreement with analytical results.

Yigit Karpat and Tugrul Ozel (2007) presented 3D Finite Element

Modelling using DEFORM 2D in hard turning of AISI H13 steel with the

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polycrystalline cubic boron nitride (PCBN) inserts. They investigated the

effect of the cutting edge microgeometry, feed rate and cutting speed on tool

flank wear and resultant forces. Further, they reported that, the hone micro-

geometry inserts have tendency to result in lower forces, hence lower flank

wear and the chamfer micro-geometry provides higher localized stress

concentration. The FEA simulations were sensitive to the work material

model and the friction factor.

2.7 ON LINE TOOL WEAR MONITORING

To monitor the condition of cutting tools in the machining

environments, numerous sensor types are used. Among those sensors,

Acoustic Emission (AE) sensor is widely used. Acoustic emission (AE) is the

class of phenomena whereby transient elastic waves are generated by the

rapid release of energy from a localized source or sources within a material,

or the transient elastic wave(s) so generated’ (ANSI/ASTM E 610-77). These

elastic waves can be detected by transducers attached to the surface of the

specimen.

Ichiro Inasaki (1998) dealt with the application of the acoustic

emission (AE) sensor for monitoring the cutting process with single-point as

well as multi point cutting tools and the grinding process. They conducted

some trials to take advantage of the AE sensor for tool condition monitoring.

They used coolant stream successfully as a medium for transmitting the AE

wave in the case of milling process monitoring and for grinding process

monitoring, the sensor was mounted in the grinding wheel with other

necessary devices.

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Mclntire (1987) stated that the major advantage of using AE to

monitor tool condition is that the frequency range of the raw AE signal is

much higher than machine vibrations and environmental noises and does not

interfere with the cutting operation. In addition to ability to ‘capture’ tool

malfunctions, it can also provide useful information, if properly interpreted,

on the occurrence of workpiece surface anomalies occurring during the

cutting process.

Xiaoli Li (2002) discussed the application of acoustic emission

(AE)-based sensing methodologies for online tool wear condition monitoring

in turning operation. They stated that, there are several AE signal processing

with various methodologies, including time series analysis, Fast Fourier

Transform (FFT), wave let transform etc., Among them, spectral analysis

such as Fast Fourier Transform (FFT) has been found to be one of the most

informative for monitoring tool wear.

Chen and Li (2009) attempted to develop online tool wear

monitoring system which predicts the actual state of the tool wear in real time

by measuring the cutting forces during milling of nickel based super alloy

Inconel 718. Further, they stated that the metal machining, particularly cutting

of suprealloys, is a complex physical process involving many deterministic

and non-deterministic factors, such as mon-homogeneous materials

properties, machine vibration and process variations.

Bhuiyan et al (2012) presented Acoustic Emission (AE) technique

to independently monitor the chip formation effect on the tool state. This has

been done by separating the chip formation events from the rest of the

frequencies of occurrences. The signals taken by acoustic emission (AE)

sensor represent the effect of chip formation on the tool state. They used the

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time domain signal and corresponding frequency response, raw AE signals

and their RMS values to predict the tool wear during turning operation. They

found that the tool wear decrease at higher cutting speed and feed rate and it

has been verified by measuring the tool wear.

Chang Liu et al (2011) carried out on-line monitoring of surface

quality of workpieces made of nickel based super alloy using Acoustic

Emission (AE) technique.They reported that the Acoustic Emission is simple

and intuitive to achieve the on-line monitoring of surface quality based on

spectrum analysis of AE signal and they proposed the method for on-line

monitoring of nickel alloy surface quality under different condition of tool

wear based on AE time-frequency spectrum.

Jemielniak et al (2011) presented an application of the wavelet

packet transform (WPT) for extracting useful tool condition monitoring

(TCM) features from cutting forces and acoustic emission (AE) signals during

rough turning of niclkel based super alloy Inconel 625. Further, they proposed

new, improved methods of signal feature (SF) relevance evaluation based on

determination and correlation coefficients. Among, the several signal features

calculated from bandpass signals, the useful for tool condition monitoring

were automatically selected.

Thakur et al (2009 A) used acoustic emission technique to

understand the effect of cutting parameters online during high speed turning

of Inconel 718. They monitored status of the tool by sensing the acoustic

emission emitted from the workpiece interms of AE raw signals during

machining. They reported that peaks over the range of 100-200 KHZ and 300-

400 KHZ and few on higher frequency range. The presence of higher power

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in this range can be attributed to occurrence of severe plastic deformation and

tool wear.

Krzysztof et al (2010) presented the method for the evaluation of

relevancy of signal features extracted from the wavelet coefficients of raw AE

signal while roughning turning of nickel based super alloy Inconel 625. They

used 22 different wavelets for extraction of signal features from band pass

signals and used for tool condition monitoring (TCM). Further, they reported

that the selection of the most indicative wavelets and decomposition level,

based on accuracy of used up portion of tool life evaluation proven superiority

of Wavelet Packet Transform over Discreet Wavelet Transform.

Iulian Marinescu and Dragos Axinte (2009) conducted machining

investigation in the milling of Inconel 718. Their research showed that

identification of milling conditions (i.e. cutting with one/two/three teeth) is

possible using AE signal in time-frequency domain. Further, they reported

that the detection of surface anomalies, such as folded laps that are generated

by damaged cutting edges has also been successfully identified in various

milling conditions.

2.8 OPTIMIZATION OF THE MACHINING PARAMETERS

In order to obtain good surface quality and dimensional properties,

optimized cutting conditions have to be employed, which also need a suitable

modelling technique for better prediction. The optimization is one of the

important activities for the economy of manufacture, and to predict the

performance characteristics of machining.

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Aman Aggarwal et al (2008) conducted turning experiments based

on Face centered central composite design on AISI P-20 tool steel using

liquid nitrogen as a coolant. They modelled the responses such as cutting

force, tool life, surface roughness and power consumption using Response

Surface Methodology (RSM). Further, they carried out multi response

optimization using desirability function.

Navin sait et al (2009) conducted turning experiments on glass-

fibre reinforced plastic (GFRP) pipes based on Taguchi’s L18 orthogonal array

to determine the influence of the machining parameters on the responses such

as surface roughness, flank wear, crater wear and machining force. Also, they

optimized the machining parameters using desirability function analysis. They

stated that the desirability function in the Taguchi method for the optimization

of multi-response problems is a very useful tool for predicting the surface

roughness, machining force and tool wear in turning of GFRP.

Senthilkumaar et al (2012) described the genetic algorithm coupled

with artificial neural network (ANN) as an intelligent optimization technique

for machining parameters optimization of Inconel 718. They conducted the

experiments based on the design of experiments full-factorial typeby varying

the cutting speed, feed rate and depth of cut as machining parameters for the

responses such as flank wear and surface roughness. Further, they

investigated the effects of the machining parameters on the flank wear and

surface roughness using analysis of variance (ANOVA).

Asokan et al (2008) stated that optimization of the operating

parameters is an important step in machining, particularly for unconventional

machining procedures like Electro Chemical Machining (ECM). They

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developed multiple regression model and ANN model to determine the

optimal machining parameters in ECM.

Nilrudra Mandal et al (2011) applied the Taguchi method and

regression analysis to assess machinability of AISI 4340 steel with newly

developed Zirconia Toughened Alumina (ZTA) ceramic inserts and they

conducted turning experiments based on L9 orthogonal array. Further, they

optimized the machining parameters based on the mean response and signal to

noise ratio (SNR). Analysis of Variance (ANOVA) was applied to find out

the significance and percentage contribution of each parameter on the

responses. The confirmation run has also been carried out with 95%

confidence level to verify the optimized result.

Ahmet and Ulas Caydas (2008) investigated the effect of the

machining parameters on surface roughness and tool life in turning of Ti-6Al-

4V alloy using CNMG 120408-883 insert. They optimized the machining

parameters based on the Taguchi method. They employed the signal-to-noise

ratio and the analysis of variance (ANOVA) to study the performance

characteristics.The results revealed that the feed rate and cutting speed were

the most influential factors on the surface roughness and tool life.

Ahmad Hamdan et al (2012) optimized the machining parameters

using Taguchi method in high speed machining of stainless steel with coated

carbide insert. The employed L9 (34) orthogonal array for the conduction of

the experiments. They study the effect of the machining parameters on the

responses such as surface roughness and cutting force using signal-to-noise

ratio and analysis of variance (ANOVA) to identify the most significant

parameters affecting the cutting force and surface roughness.

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Prakash et al (2009) presented the systematic experimental

investigation, analysis in drilling of medium density fibreboards (MDF) and

they developed an empirical model for the prediction of the responses. They

used desirability function based approach for the optimization of machining

parameters for minimizing the delamination factor at entry and exit.

2.9 STRATEGY ON TURNING OF NIMONIC C-263 ALLOY

As has already been stated elsewhere in this thesis, for aerospace

applications, the surface condition of the machined work piece is of concern

because of the role it plays in the useful life of the component under cyclic

loading. It is obvious that in order to maintain and/or improve reliability of

aerospace components, it is first essential to be aware of the possible damage

or surface alterations that can be imparted to a material when it is machined.

Although it is possible to apply post machining operations such as heat

treating or shot peening to impart the conditions which will provide a

predetermined desirable surface that may provide consistent desirable

mechanical and physical properties. Hence, it is also necessary to control the

machining operation to ensure the integrity specifications.

Much of the valuable data has been published mostly on the

machinability of Inconel 718. However, the comprehensive study on the

machinability of the nimonic C-263 alloy was not reported. Further, it was

reported that among the several parameters that affect the machinability of

machined parts, cutting speed, feed rate, depth of cut, tool geometry, tool

wear, and properties of work material are among the most important ones that

are worth investigating.

Therefore this work aims on the following:

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To design a predictive model for cutting force components,

surface roughness, flank wear and the generation of

temperature at the tool tip in machining this alloy using

different cutting tool materials under different levels of

machining parameters.

To perform a detailed investigations on the surface integrity of

the nimonic 263 alloy for evaluating the effect of the cutting

parameters on the surface integrity during turning, using PVD

coated carbide insert and whisker reinforced ceramic cutting

tool inserts, in terms of the formation of the surface and

subsurface residual stresses, micro hardness variation at

different depths beneath the machined surface, and the surface

finish generated.

To perform online tool wear monitoring using Acoustic

emission technique.

To model 3D finite element modelling in machining nimonic

C-263 alloy using DEFORM 3D software.

2.10 NEED FOR THE PRESENT STUDY

The nickel based super alloy of nimonic C-263 used in aerospace

components continually suffer from extremes of temperature, pressure and

velocity, and are in service for many decades now. It is also critical that the

most stringent quality controls are need, when the parts are machined.

Reliability is an important criterion in the manufacture of aerospace

components, and therefore, these component manufacturers need to maintain

high-quality on a consistent basis. The exacting standards of aerospace

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machining make it mandatory that each part be machined with absoluteprecision, no matter how challenging the task is.

However, the machining of nimonic C-263 alloy is difficult due to

poor thermal conductivity, high work hardening rate, high shear strength, high

temperature oxidation at elevated temperatures environment, resistance to tool

penetration during machining. Since this alloy possesses high temperature

characteristics, and it places the cutting tools under tremendous heat, pressure

and abrasion etc during turning. It creates rapid flank wear, crater wear and

tool notching at the tool nose etc. Furtheer, it causes highly difficult to

machine the alloy, which in turn affects the dimensional accuracy and surface

integrity during machining. It is also important to know the mechanical and

thermal load acting on the cutting insert while changing the cutting

parameters during the machining of this alloy.

This research work focuses on modelling the machining parameters

using Response Surface Methodology, Artificial Neural Network (ANN) and

Finite Element Method (FEM). The optimization of machining parameters on

turning nimonic C-263 alloy using Response Surface Methodology (RSM)

based desirability approach was also carried out. Apart from modelling and

optimization of machining parameters, the investigation on the surface integrity

and on line tool wear monitoring using acoustic emission technique in machining

nimonic C-263 under different cutting tool inserts were also done.

The effects of machining parameters (cutting speed, feed rate and

depth of cut) on different responses such as cutting force components, surface

roughness, temperature at the tool end and tool wear (flank wear) were

studied. The modelling of machining parameters is carried out using response

surface methodology. The effectiveness of the response surface model was

evaluated with design of experiments. The optimizations of machining

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parameters with respect to the responses were carried out using response

surface methodology based desirability approach. The machined surface and

worn out inserts were assessed by using scanning electron microscopy (SEM)

analysis and micro structural analysis.

2.11 SCOPE OF THE PRESENT STUDY

Great advances are taking place in the development and application

of newer materials, more specifically in aero engines, to enhance the thrust-

to-weight ratio and to meet the requirement of sustaining the corresponding

increase in temperature in the combustion area. To meet this demand, the

nimonic C-263 super alloy is currently being applied in the combustion area

of gas turbines, due to its unique resistance to thermal fatigue and creep

characteristics, by the presence of higher cobalt content. From the available

literature, the systematic and comprehensive analysis has not been carried out

in the turning of nickel based Nimonic C-263 alloy and hence, there is a need

for carrying out systematic turning studies on nimonic C-263 alloy with

different cutting tools and machining parameters.

Turning experiments were carried out on nimonic C-263 alloy to

investigate the interaction effect of machining parameters (cutting speed, feed

rate, and depth of cut) on the responses like cutting force components, surface

roughness, cutting temperature, tool wear and surface integrity. It is necessary

to model and optimize the machining parameters in order to improve the

surface quality, reduce cutting force components, reduce tool wear and cutting

temperature in turning nimonic C-263 alloy. The literature available in

modelling and optimization of machining parameters in turning nimonic C-

263 alloy is limited. For modelling the machining parameters, the response

surface methodology (RSM) is used.

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The multi performance optimizations are carried out using response

surface method based desirability approach. In order to understand the turning

process in turning of nimonic C-263 alloy, analysis of process parameters is

carried out using Analysis of variance (ANOVA).

2.12 OBJECTIVES OF THE STUDY

The important objectives of this research work are listed below:

To machine the nimonic C-263 alloy under different levels ofmachining parameters on turning operation and evaluate themachining attributes such as cutting force, temperature at tooltip, surface roughness and flank wear using three differentinserts such as PVD coated carbide , whisker reinforcedceramic and cubic boron nitride inserts.

To develop an empirical relation for the prediction of cuttingforce, temperature at tool tip, surface roughness and flankwear in turning nimonic C-263 alloy using Response SurfaceMethodology (RSM) with the three different inserts.

To develop an Artificial Neural Network (ANN) model for theprediction of cutting force, temperature at tool tip, surfaceroughness and flank wear in turning nimonic C-263 alloy withthe three inserts.

To compare the effectiveness of Response Surface Model(RSM) and Artificial Neural Network (ANN) model with theexperimental results of responses such as cutting force,temperature at tool tip, surface roughness and flank wear inturning nimonic C-263 alloy using three different inserts.

To optimise the multi responses such as cutting force,temperature at tool tip, surface roughness and flank wear

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using response surface method based on desirability approachin machining nimonic C-263 alloy using the three inserts.

To evaluate on-line tool wear monitoring using AcousticEmission (AE) technique during the turning of nimonic C-263alloy using PVD coated carbide and whisker reinforcedceramic inserts.

To develop Finite Element Model for the prediction of cuttingforce, temperature at tool tip, effective stress and effectivestrain using PVD coated carbide insert and to validate theexperimental results of cutting force, and temperature at tooltip with predicted values of Finite Element Analysis.

To investigate experimentally the influence of machiningparameters on the surface integrity in terms of microhardness,residual stresses in machining nimonic C-263 alloy usingPVD coated carbide and whisker reinforced ceramic inserts.

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2.13 METHODOLOGY

The methodology used in this research work is shown in the Figure 2.1.

Experimental Investigation on thefollowing machining attributes

with different tool inserts

1. Cutting force2. Temperature at tool tip3. Effective Stress and Strain

FEM analysis onmachining attributes

using PVD coated carbide

1. PVD coated carbide insert2. Whisker reinforced ceramic insert3. Cubic boron nitride (CBN)

Conclusions

1. Cutting force2. Surface roughness3. Flank wear4. Temperature at tool tip5. Surface Integrity - Microhardness - Residual stresses 6. On-line tool wear Monitoring

1. To determine the significant machiningparameters on responses such as Fz, Ra,VB & Temp using ANOVA.

2. To develop an empirical model forevaluating the responses such as Fz, Ra,VB & Temp using RSM and ANNtechniques.

3. To evaluate the effect of machiningparameters on machining performances byRSM method.

4. To determine the optimized machiningparameters using RSM based desirabilityapproach.

5. To validate the theoretically predictedvalues with the experimental results for theresponses such as Fz, Ra, VB & Temp

Result and discussion

Theoretical Prediction and Modellingof machining performances with three

different inserts

Study of Machining attributes

Nimonic C-263Turning Experiments(Nagmati 175 Lathe)

Selection of Workpiece Selection of machining

methods

Selection ofCutting tools

Experimental Investigation, Modelling and analysis on machiningcharacteristics of Nickel based super alloy Nimonic C-263

Figure 2.1 Scheme of research

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2.14 SUMMARY

This review of literature brings out the problems encountered

in the machining of the nimonic C-263 alloy. Despite the

availability of good amount of literature for the machining of

Inconel 718 super alloy, only very few and inconclusive data

are available on machining the nimonic C-263 super alloy.

From the existence researcher’s literature the following

limitations have been identified in machinng of Nimonic C-

263 alloy:

The effect machinng parameters on machining

attributes such as cutting force, cutting temperature,

surface roughness, tool life and tool wear in maching

the supre alloy were carried out to some extent only,

no comprehensive and systematic modelling approach

with respect to nimonic C-263 alloy is identified.

There is no a comprehensive study on microhardness

and residual stresses in machining Nimonic C-263

alloy which is still missing.

The on-line tool wear monitoring using acoustic

emission (AE) and Finite Element Analysis (FEA) in

machining Nimonic C-263 alloy is also still missing.

The published literatures emphasize the need for more

comprehensive scientific work on turning the nimonic C-263

alloy. It also emphasizes the investigation on the

machinability of nimonic C-263 alloy by observing the cutting

force, tool temperature at tool tip, surface finish, tool wear and

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surface integrity and the subsequent data analysis and

modelling and monitoring the on-line tool wear using

Acoustic Emission.

The published literatures revealed that the Response Surface

Methodology, Artificial neural network (ANN), Finite

Element Model (FEM) and Acoustic Emission (AE) for

monitoring the machining process are important modelling

technique and can be used for turning nimonic C-263 alloy.

Also, the literatures revealed the importance of multi response

optimization such as the cutting force, tool temperature at tool

tip, surface roughness and flank wear etc., for the economy of

manufacture.

.