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CHAPTER 2

LITERATURE REVIEW

2.1 INTRODUCTION

Development of a fully automated machine tool has been the goal of

modern manufacturing industries research for decades. This can be

accomplished until the fool proof and practical methods to sense the amount

of tool wear and the development of wear resistant cutting tools are

developed. These developments can improve the quality of components to be

manufactured by ensuring that the surface and dimensional specifications are

within the tolerance level. This allows the introduction of elevated cutting

speeds to minimal the cutting time, resulting in a substantial saving of the

total machining cost. In general, cutting application carbide tools are used at

higher cutting speeds. Tool wears generated at these cutting speeds are

affected by diffusion between a cutting tool and work material.

In order to decide the right time for tool change, during the

machining operation need to be continuously monitored. The regularly used

experimental method of examining the tool wear through microscopy

interrupts in the cutting process. However, an indirect way of monitoring the

tool wear (in which a measurable output might be used to indicate the extent

of tool wear without interrupting the machining process) would be more

suitable for practical applications. Such outputs may be the cutting and feed

forces that are dependent on tool wear (Cronjager et al 1992, Lin et al 1995)

The longevity of a cutting tool and its operating conditions largely

control the economics of the machining operations. Hence it is imperative that

19

the condition of the cutting tool (particularly some indication as to when it

requires changing) to be monitored.

Cutting tool users cannot afford to ignore the constant changes and

advancement in the field of tool material technology. The best tool is one that

gets the job done quickly, efficiently and economically. The pressing demand

for developing new cutting tools that does not require cutting fluids is largely

felt by cutting industries. This because cutting fluids pose many hurdles such

as a) increased pollution b) health hazards ( skin injuries and allergies) c) high

maintenance costs ( in terms of cleaning and disposal).Hence an a alternative

solution to the wet cutting process is dry cutting process. Dry cutting is one of

most popular method which growing substantially in manufacturing

industries, because of tangible benefits. Dry cutting is possible only when the

cutting tools are coated with some hard materials such as TiN, TiC, TiAlN,

etc and it has been used with great success. These hard coatings increase the

longevity of tool, limit the tool wear and increase overall performance of the

tool.

In general, the most noteworthy point in machining processes is

productivity, which is achieved by cutting the highest material removal rate in

the shortest period using tools which last long. Combining all the parameters

in the machining process to maximize productivity is, however, a very

complex task and becomes particularly difficult while working at high speed

cutting in hardened steels.

2.2 MODES OF TOOL WEAR OCCURRING DURING

MACHINING PROCESS

Cutting tools are subject to an extremely severe rubbing process.

They are in metal-to-metal contact, (between the chip and work piece) under

conditions of very high stress at high temperature. This situation is further

aggravated by the inducement of extreme stress and temperature gradients

20

near the surface of the tool. During cutting, cutting tools remove the material

from the component to achieve the required shape, dimension and finish.

However, wears continue to occur during the cutting action, which it will

result in the failure of the cutting tool. When the tool wear reaches certain

extent, the tool or edge change has to be replaced to guarantee the ordinary

cutting action.

2.2.1 Tool Wear Phenomena

Under high temperature, high pressure, high sliding velocity and

mechanical or thermal shock in cutting area, cutting tool has normally

complex wear appearance. This consists of some basic wear types such as

crater wear, flank wear, thermal crack, brittle crack, fatigue crack, insert

breakage, plastic deformation and build-up edge. The dominating basic wear

types vary with the change of cutting conditions.

Wear on a tool can be in any one of two areas:

Crater wear: In continuous cutting, for example, in the case of a turning

operation, crater wear normally forms on the rake face. It conforms to the

shape of the chip underside and reaches a maximum depth at a distance away

from the cutting edge where the highest temperature occurs. At high cutting

speed, crater wear is often the crucial factor that determines the life of the

cutting tool. This is because the tool edge is weakened by the severe cratering,

eventually leading to fractures. Crater wear is improved by selecting suitable

cutting parameters and by coated tool or ultra-hard material tool. A rapid

cratering on the rake face of the tool can result either from high temperatures

generated at cutting speeds (much higher than recommended ones) or from

high chemical reactivity between the tool material and the work material.

21

Flank wear: Flank wear is caused by the friction between the newly

machined work piece surface and the tool flank face. Flank wear results in

poor surface finish decreased dimension accuracy of the tool and an increased

cutting force, temperature and vibration. Hence the width of the flank wear

land “VB” is usually taken as a measure of the amount of wear. Also,

threshold value of the width is defined as tool reshape criterion and depth-of-

cut line (DCL) notch wear in the machining of certain difficult-to-machine

materials such as super alloys using ceramic tools (Figure 2.1). In addition, a

part of the tool, eg, the nose, may be deformed plastically owing to inadequate

strength at high operating temperatures. Moreover, cracks may be generated

on the tool owing to thermal or mechanical cyclic stresses induced during

interrupted cutting.

Figure 2.1Modes of tool wear on cutting tools (ISO 3685, 1993)

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2.3 TUNGSTEN CARBIDE TOOL MATERIALS

Tungsten carbide (WC) is one of the most widely used tool material

in manufacturing industries for machining of grades of stainless steel material

because of its exceptional tribological properties. Since WC was introduced

75 years ago as a cutting tool material, considerable amount of research has

been devoted to studying the machining theory and tool wear. Consequently,

the hard turning of stainless steels (45–65HRC), an application area continues

to experience rapid growth. The existing tool market trends aspire towards

higher cutting speeds, high surface finish, high depth of cut, and increased

material removal rates. In response, the number of commercially available

grades also increases with many of them being tailor - made for very specific

applications (Lahiff et al 2007).

Figure 2.2 Ishikawa cause-effect diagram of a turning process

(Hari Singh and Pradeep Kumar 2006)

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The definition of cutting tool performance is also important as there

are usually several different criteria to be achieved by a single process. This is

particularly true for finish hard turning operations and Figure 2.2 shows the

various parameters that are used to measure cutting tool performance and

surface quality of turned components. Other considerations include machine

downtime, material removal rates, and the number of parts manufactured

(Lahiff et al 2007).

2.4 COATED TOOLS

The complexity of machining has many advanced materials existing

challenges to the cutting tool industry, leading to the introduction of coated

cemented carbides in the late 1960s (66–71) and coated HSS in the late 1970s,

From the 1980s onwards, surface coating technology is important to achieve

amplified vigorous performance, allowing lower friction coefficients, higher

protection against surface failures and higher load capacity. Another

important objective to be accomplished by surface coatings in the near future

is the reduction/elimination of some toxic lubricant additives and consent the

use of environment friendly lubricants.

An efficient coating should be durable, refractory, chemically stable,

chemically inert to defend the constituents of the tool and the work-material

from interacting chemically under the conditions of cutting, binder free, of

fine grain size with no porosity, metallurgically bonded to the substrate with a

graded interface to match the properties of the coating and the substrate, thick

enough to prolong tool life but thin enough to prevent brittleness, free of the

tendency of metal chips to adhere to or seize to the tool face, able to provide

residual compressive stress, easy to deposit in bulk quantities, and

inexpensive(Komanduri 2000).

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Coating must adhere strongly to the substrate, several factors to be

considered. It includes mechanical, physical, and chemical compatibilities

between the coating and the substrate. While, since tools are subject to an

elevated stress of loading while machining, the substrate must have ample

hardness and deformation resistance to support coating without the

occurrence of deformation. Otherwise, the coating becomes delaminated from

the substrate due to the development of interfacial tensile stresses.

2.4.1 Effect of surface coating on cutting tools

In the recent decades the progression of coatings for cutting tools

followed tool materials development. Coatings represent an important part in

the present stage of development of cutting tool technology. The use of a

coated tool is essential for future metal cutting industries for many reasons.

The heat generated during dry machining, High Speed Cutting (HSC), and

hard turning demand cutting tools with an elevated heat resistance or the

presence of a heat insulating coating on the surface. This scenario promotes

the coating for cutting tools, and the result was the development of various

types of coatings for specific applications (Santos et al 2004).

Gokkaya and Muammer (2006) recorded that the best surface

roughness could be obtained by means of cutting tools coated with TiN using

the CVD technique. Gokkaya et al (2004) investigated the effect of cutting

tool coating material, cutting speed, and feed rate speed on the surface

roughness of AISI 1040 steel. In their study, the lowest average surface

roughness was obtained using cutting tool with coated TiN. A 176%

improvement in surface roughness was provided by reducing the feed rate by

80% and a 13% improvement in surface roughness was provided by

increasing the cutting speed by 200%. Dubar et al (2005) produced the better

results in terms of friction and lifetime, by using the CVD TiN coated tool

and CVD. This was found to the good bonding to the substrate.

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A tungsten carbide material with PVD TiN coating currently enjoys

wide metal cutting application. Surface coating is an effective method to

improve the durability of materials used in aggressive environments. The

PVD coatings featured TiN as the hard coating and were applied in cutting

processes. Hard coatings increase tool performance and longevity by arresting

or slowing down the tool wear. The metal cutting performance of PVD-coated

tool depends strongly on factors such as composition, microstructure, internal

stress, adhesion of the coating to the substrate, substrate composition and tool

geometry. TiN coated tool exhibited lower wear than the Al2O3 coated tool

(Sahin 2005). TiN was considered as a universal coating for cutting tools and

is indicated when different workpiece materials are machined with the same

cutting tool (Harris et al 2001). Ghani et al (2004) studied the performance of

TiN coated carbide inserts when machining of AISI H13 tool steel. The tool

life results indicated that the cutting speed did not have an effect was not

affected significantly by the cutting speed much contrary to the early findings.

Lim et al (2001) investigated the effects of work materials on the

wear improvement of coated tools by comparing uncoated and TiC coated

carbide tools. The experimental results revealed the effectiveness of TiC

coating in machining carbon 1045 grade, decreasing tool wear rates by half an

order magnitude.

Rogante (2008) conducted the comparative study on TiC–TiN

coated and uncoated inserts when machining of normalisied medium carbon

steel in dry cutting process. The results revealed that coated tool produced

approximately 50% longer machining time and lesser power consumption

when compared to the uncoated tool.

Adilson Jose de Oliveira et al (2009) performed hard turning

process in continuous and interrupted cut using PCBN tool inserts and

ceramic tools. The results indicated that the longevity of both the tools is

26

improved. Also, in terms of surface roughness, PCBN tool shows the better

results for continuous and interrupted cut.

Jindal et al (1999)found that TiAlN coated tools exhibited the best

cutting performance when turning Inconel 718, AISI 1045 steel and ductile

iron at low and high cutting speed conditions. Keunecke et al (2010)

investigated the performance of modified TiAlN coatings prepared by pulsed

D.C. magnetron sputtering process. Coating prepared with pulsed sputtering

process improves the hardness and also offers high wear resistance in turning

process.

Hovsepian et al (2006) conducted a comparative study on super

lattice structured TiAlN/VN, diamond-like carbon (DLC) coated, TiAlCrYN

coated and uncoated tools. These performance tests were conducted in dry

high-speed milling of aluminium alloys Al7010-T7651 and AlSi9Cu1. The

test results revealed that the TiAlN/VN high speed steel outperformed all

other tools by showing increased tool lifetime, reduced cutting forces,

elimination of BUE and reduced surface roughness value. TiAlCrYN coating

also indicated better performance by in increasing the wear resistance of

cutting tool and limited to increase in lifetime. Although it brought about

higher cutting forces than the TiAlCrYN and DLC coated tools, DLC coated

tools exhibited longer tool lifetime than the uncoated tool.

Kupczyk et al (2007) investigated the influence of post heat

treatment of coated on tools. For the purposes of the study, they coated

carbide tools with TiC (monolayer), TiC + TiN (two layer) and TiC +

Al2O3+TiN (tri layer) using the CVD technique. After coating, the tools were

treated with different laser power densities and various tests were conducted.

The test results they revealed that laser heating enhances the adhesion of CVD

coatings. Further, they also recommended that coatings not contain Al2O3 for

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laser heating. This is because resistance to heat impact and it poses high risk

to thermal cracking.

Deng Jianxin et al (2008) investigated the performance of PVD

MoS2/Zr composite coating on the surface of cemented carbide tools. After

coating they conducted sliding wear test and cutting tests. The result of the

study indicated good improvement of cutting tools. This is because of

MoS2/Zr composite coating gives higher hardness and a better adhesion on the

substrate when compared to the pure MoS2 coatings. Also it exhibits

decreased coefficient of friction when compared to the uncoated tool. In case

of low cutting speeds, MoS2/Zr composite coating performed better than the

uncoated tool. MoS2/Zr act as a lubricant on the rake face of the cutting tool

which in turn reduces the tool wear substantially.

Ronghua Wei et al (2002) studied certain aspects on plasma-

enhanced magnetron-sputtered deposition of hard coatings on cutting tools.

Their findings revealed that with respect to microstructural properties, TiN

deposited using the PMD process shows a very fine grain size and high

internal stress with excellent adhesion and cohesion properties. The cutting

tests revealed that tools coated with TiN using the PMD process improved

longevity when compared to those using arc-evaporation and unbalanced

magnetron sputtering processes.

Settineri et al (2008) investigated the performance evaluation of

newly developed AlSiTiN and AlSiCrN nanocomposite coatings for cutting

tools. Coating was performed with different layers such as gradient and

multiple layers. Cutting tests and wear test performed during these tests they

revealed that nanocomposite AlSiTiN both multi-layer and gradient layer

showed better wear resistance in elevated temperature and increased

functional and mechanical properties.

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Wang (2000) discussed the effect of multilayer coatings of carbide

tool inserts on cutting forces when machining mild carbon steel materials with

variant cutting velocities. Their performance was analysed both theoretically

and experimentally. During the experimentation process, he compared the

force variation between coated and uncoated cutting tools. The experimental

results revealed that multilayer TiC + Al2O3 + TiN coated tool exhibits higher

performance by reducing cutting forces while machining when compared to

uncoated tools. With the help of theoretical analysis he plotted cutting force

equations, which were used to optimize the machining conditions, selection of

cutting tools and fixture and the selection and design of machine tools.

Settineri et al (2007) investigated the effect of diamond coating on

carbide tools. Coatings were done using different techniques such as

Microwave Plasma Assisted Chemical Vapour Deposition (MWPACVD),

Hot Filament Chemical Vapour Deposition (HFCVD). Coated tools were

compared with the commercial CVD diamond coated during experimentation.

Cutting tests were performed using the metal matrix composite material as a

workpart. From cutting test results, the performance of MWPACVD coating

showed that similar or higher than the commercial CVD diamond coating. On

the other hand, HFCVD coating showed poor performance and occurrence of

an early failure.

Tsao Chung –Chen and Hocheng Hong (2002) studied the

comparative performance of carbide tools coated by multilayer TiCN and

TiAlCN for end mills. Multilayer coating was performed on tool using

multiarc PVD system. First tool coating consisted of TiN/TiCN/TiN/ TiCN/

TiN/ TiCN-surface, and the second tool coating layers consisted of

TiN/TiCN/TiN/ TiCN/ TiN/ TiAlCN-surface. Complete coating thicknesses

were maintained to a point of about three microns. To investigate the tool life

of coated tool, cutting tests were performed on quenched AISI 1045 carbon

29

steel. The experiments were conducted using taguchi technique. The

experimental results confirmed that hard coating deposition improves the

wear resistance of tool. Under the same cutting conditions TiCN coated tool

and K40 tool found to indicate a 188% improvement when compared to

TiAlCN coated tool and K10 tool material.

Holubar et al (1999) investigated the performance of nanocomposite

monolayer TiAlSiN, nanocomposite multilayer TiAlSiN and newly developed

TiN-BN. Ti-B-N layer coated on the indexable inserts were compared in

cutting tests. The performance of Ti-B-N was found to be worse at the high

cutting speed when compared to TiAlSiN due to lower chemical resistance at

high temperature. The hardness of the Ti-B-N coatings was found to remain

unchanged even if the grain size was significantly increased. During

annealing at the temperature of 1000oC the internal residual stress was found

to remain stable. Hardness of the TiN-BN coatings was found to decrease

after annealing at 900oC. Considering these limitations, this coating cannot be

used under excessive cutting conditions. Ti-B-N and TiN-BN coatings show

excellent results at low cutting speed.

Jawaid et al (2001) investigated the three ceramic-coated carbides

[CVD-Ti(C,N)/Al2O3 (T1), CVD-Ti(C,N)/TiC/Al2O3 (T2) and PVD-TiN

(T3)] using statistical regression analysis. Turning test were conducted on

CNC lathe without the use of a coolant. During experimentation, were

observed the common failure mode at higher speed conditions, with the help

of turning results. Statistical analysis they revealed that the contribution of the

cutting speed and feed rate influenced tool performance to of 80 per cent, with

the cutting speed exhibiting a superior degree of influence.

Hu et al (2008) evaluated the performance of nanocrystalline

diamond (NCD) coating tools when machining high-strength aluminum (Al)

alloy at various cutting conditions with tool wear and cutting forces.

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Conventional CVD microcrystalline diamond coating (MCD) tools and PCD

tools were also tested for performance comparisons. They also analysed stress

distributions in diamond coating tools after deposition and during machining

using the 2D finite element thermo mechanical model. The results of test they

revealed that NCD tool life is primarily affected by cutting speed. Further,

with an increase of feed rates, the coating delamination may also extend to the

rake face. The NCD tools showed better performance when compared to the

MCD tools. SEM observations indicated that coating failure boundaries

between substrate and coating. Moreover, the FE model revealed that

diamond coating tools can have a 4GPa in compression and higher stress level

at the cutting edge. Thus, the larger stress levels shorten tool life.

Prengel et al (2001) investigated the performance of Monolayer

TiN, TiAlN, TiB2 and different variants of TiAlN multilayer PVD coated

cutting inserts. Coatings were prepared by either cathodic arc process or a

high-ionization magnetron sputtering process .The thickness of coatings were

about to 4-5 m except TiB2 which had a thickness of 2.5 m. Coatings were

characterized by optical microscopy and scratch adhesion techniques. These

coated tools were tested in milling operations when cutting the ductile, gray

cast irons both with and without coolant and in turning of Inconel 718 and a

hypereutectic Al-Si alloy. The milling tests during cutting of ductile cast irons

revealed that the tool without coolant had a longer life when compared to the

tool with coolant. Further, they observed that TiAlN multilayer coating

produces around 70% longer tool life when compared to Monolayer TiAlN in

dry milling and in turn TiN/TiCN/TiAlN-multi-layer coated insert did not

show any advantage over other coatings in dry or wet milling. In same milling

process, cutting gray cast iron material under dry condition TiAlN multilayer

coating produces almost 50% improvement in tool life when compared to

other coatings. The same kind of performance also observed in turning of

Inconel 718 at higher cutting speeds. On the other hand turning hypereutectic

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Al-Si alloy PVD TiB2 coating gives better abrasion resistance when compared

to TiAlN or TiN coatings.

Ibrahim Ciftci (2006) investigated the influence of various

parameters such as work material grade, cutting tool coating, cutting speed on

cutting forces and machine surface. He conducted the machining tests by

continuous turning of AISI 304 and AISI 316 grade austenitic stainless steel

with variable spindle speed. The cutting tools used were commercial grade

CVD multi-layer TiC/TiCN/TiN and TiCN/TiC/Al2O3coated cemented

carbide inserts. The machining tests results revealed that cutting speed had a

considerable effect on the machined surface roughness values. Further with an

increase in cutting speed, the surface roughness value was found to decrease

until a minimum value was reached. Beyond this point the value of surface

roughness was found to increase. The TiC/TiCN/TiN coated cutting tools

gave lower cutting forces than TiCN/TiC/Al2O3 coated tools though the

difference was not significant. From workmaterial point of view, highest

cutting forces were recorded when cutting the AISI 316 at all cutting speeds

employed when compared to AISI 304.

Wenping Jiang et al (2005) investigated the development and

performance study of a new nanocomposite cBN–TiN coating. Cutting tool

was coated at different levels of thickness until an optimum thickness was

arrived. The tool was then selected for machining test. The coated chip-

breaker inserts were tested in finish turning of hardened steel AISI 4340. A

cutting condition with a surface speed (v) of 150 m/min, feed rate (f) of 0.15

mm/rev, and depth of cut (DoC) of 0.25 mm, which was typically for finish

turning, was selected for the tests. The machining test results demonstrated

that nanocomposite cBN–TiN coated inserts had a tool life of 20 min per

cutting edge at optimum cutting condition and workpiece surface roughness is

between the 5-7 m when compared that from the fine grinding process.

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Khrais and Lin (2006) studied wear mechanisms and tool

performances of TiAlN PVD coated inserts during machining of AISI 4140

steels at high speeds for both dry and wet machining. Dry cutting was

observed to be better than wet cutting at around 200–400m/min speed.

2.5 TOOL WEAR MONITORING TECHNIQUES BASED ON AI

APPROACHES

Choudhury and Appa Rao (2005) presented a new approach for

improving the cutting tool life by using optimal values of velocity and feed

throughout the cutting process. A tool life equation was established from

experimental data and the adhesion wear model. Choudhury and Ramesh

(1995) used an optoelectronic sensor in conjunction with a multilayered

neural network for predicting the flank wear on the cutting tool. Das et al

(1997) used back propagation algorithm for training the neural network. The

technique showed close matching of estimation of average flank wear and

directly measured wear value. Kuo and Cohen (1998) proposed an on-line

estimation system which could be to predict the amount of tool wear

accurately. Further, as a continuation, they combined ANN and fuzzy model

to improve each other’s performance. Purushothaman and Srinivasa (1994)

developed the back propagation algorithm providing a computationally

efficient method for training the multilayer perception. A multilayer

perception trained with the BPNN has been viewed as a practical way of

performing a non-linear input – output mapping of a general nature.

Scheffer et al (2003) showed that the best method for monitoring

tool wear during hard turning was the use of force based monitoring with an

Artificial Intelligence (AI) model. Zuperl and Cus (2003) proposed a neural

network-based approach to solve complex optimization of cutting parameters

and concluded that the approach is suitable for fast determination of optimum

cutting parameters during machining. Abdul (2004) developed a multilayer

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perception feed forward neural network to evaluate and compare the cutting

forces developed during the machining of Glass/epoxy, graphite/epoxy and

Kevlar/epoxy composites. Palanikumar et al (2005) proposed the

development of a predictive model for the determination of tool flank wear in

machining Glass fiber reinforced plastics (GFRP) composites. Back-

propagation neural network (BPNN) was employed to construct the model.

Choudhury and Bartarya (2003) attempted to predict tool wear by

employing DOE and the NN for analysis. The flank wear, surface finish and

cutting zone temperature were taken as response variables while cutting

speed, feed rate and depth of cut were considered as input factors. Predictions

for all the three response variables were obtained with the help of empirical

relation between different responses and input variables using DOE and also

ANN program. Ezugwu et al (2005) developed the ANN model for the

predicting the relationship between cutting and process parameters in metal

cutting operations. Through the proposed model, they achieved the good

performance with appreciable correlation coefficient between the model

prediction and experimental values. Muthukrishnan and Paulo Davim (2009)

utilized the ANN technique and ANOVA for the comparative study. The

results they revealed that ANN is the most effective method when compared

to ANOVA.

Umbrello et al (2007) used predictive model based on the ANN

approach for predicting subsurface residual stress and the required machining

condition for hard turning and observed that predicted errors ranged between

4 and 10 % for the whole data.

Zhou et al (1995) investigated the tool life criteria in raw turning. A

new tool-life criterion depending on a pattern-recognition technique was

proposed and neural network and wavelet techniques were used to realize the

34

new criterion. The experimental results showed that this criterion was

applicable to tool condition monitoring in a wide range of cutting conditions.

Lin et al (2003) adopted an abdicative network to construct a

prediction model for surface roughness and cutting force. Once the process

parameters (cutting speed, feed rate and depth of cut) were given, the surface

roughness and cutting force could be predicted by this network. Regression

analysis was also adopted as second prediction model for surface roughness

and cutting force. Comparative results of both models indicated that adductive

network was found to be more accurate than the regression analysis.

Feng and Wang (2002) investigated the prediction of surface

roughness in finish turning operation by developing an empirical model

through considering the following working parameters: work piece hardness

(material), feed, cutting tool point angle, depth of cut, spindle speed, and

cutting time. Data mining techniques, nonlinear regression analysis with

logarithmic data transformation were employed for developing the empirical

model to predict surface roughness.

Suresh et al (2002) focused on machining mild steel by TiN-coated

tungsten carbide (CNMG) cutting tools for developing a surface roughness

prediction model using Response Surface Methodology (RSM). Genetic

Algorithms (GA) were used to optimize the objective function and GA was

compared to the RSM results. It was observed that GA program provided

minimum and maximum values of surface roughness and their respective

optimal machining conditions.

Chien and Tsai (2003) developed a model for predicting tool flank

wear followed by an optimization model for the determining of optimal

cutting conditions in machining 17- 4PH stainless steel. The back-propagation

35

neural network (BPNN) was used to construct the predictive model. The

genetic algorithm (GA) was used for model optimization.

2.6 SURFACE ROUGHNESS AND TOOL WEAR PREDICTION

TECHNIQUES BASED ON EXPERIMENTAL STUDIES

Micheletti et al (1976) discussed the direct and indirect methods of

tool wear measurement using various tool wear sensors, radio isotopes as

tracers, chemical analysis of tool particles carried by chip, detection probe

microscope, and weighing of the tool before and after machining, etc. Koren

et al (1986) proposed a model-based approach to on-line tool wear and

breakage sensing. Algorithms and on-line training of the model-based

approach using artificial intelligence methods were suggested by them.

Choudhury and Ramesh (1995) have used an optical displacement sensor for

on-line tool wear monitoring. A feedback control system to provide

compensation for the tool wear and keep the dimensions of the workpiece

within the tolerance zone was also suggested. Rao (1986) developed a

microcomputer-based technique based on the real time computation of a wear

index (WI) for monitoring the flank wear on a single-point tool. Caprino et al

(1996), in their work on orthogonal milling of uni-directional glass fiber-

reinforced plastics using high speed tools, concluded that both the horizontal

and vertical forces undergo large variations with the tool wear.

Cuppini et al (1990) focused on the methods and devices for in-

process tool wear monitoring in turning operations. They presented an

approach to the tool decay monitoring based on cutting power measurement.

However, important parameters such as workpiece properties, cutting speed,

feed and depth of cut which influence the tool wear by a large extent, were

not taken into account. Elbestawi et al (1991) developed mathematical models

36

to describe wear-time and the wear-force relations. Though the relations were

well correlated, the wear level in the third stage of the flank wear growth

curve, at which very high tool wear rate occurs, was difficult to be estimated

precisely.

The model developed by Chryssolouris et al (1987) estimated some

constants, were employed for computation of flank and crater wear right from

cutting forces and cutting temperatures. However, this model cannot be

applied for estimating flank and crater wear in oblique cutting for tools having

three cutting regions (major, nose and minor cutting regions) normally used in

industry. Hence, in the present work focuses on developing a reliable tool

wear model as a function of cutting velocity, feed, and depth of cut. Surface

roughness and tool wear model have been estimated using this model and

verification experiments have been conducted to confirm the feasibility of the

proposed method.

Myung et al (2005) suggested that fractal analysis could be used as

an effective tool for in-process monitoring of tool wear. Experiments were

carried out on high-hardened die steel using uncoated and coated tools (TiN,

TiAlN), in high-speed cutting conditions. They concluded that a TiAlN

coating tool is the proper tool to analyze fractal dimension of machined

surface. In addition, they showed that fractal dimension and tool wear shows a

similar tendency associated with the increase in surface roughness.

Jurkovic et al (2005) stated that there are two predominant wear

mechanisms that limit a tool’s useful life are: flank wear and crater wear.

Flank wear occurs on the relief face of the tool and could be attributed to the

rubbing action of the tool on the machined surface. Crater wear occurs on the

rake face of the tool and changes the chip–tool interface, thus affecting the

37

cutting process. Traditionally, wear has been measured with a tool-maker’s

microscope under laboratory conditions.

Kirby et al (2004) developed the prediction model for surface

roughness in turning operation. The regression model was developed by a

single cutting parameter and vibrations along three axes were chosen for in-

process surface roughness prediction system. Using multiple regression and

Analysis of Variance (ANOVA), a strong linear relationship among the

parameters (feed rate and vibration measured in three axes) and the response

(surface roughness) was found. The authors demonstrated that spindle speed

and depth of cut need not necessarily have to be constant for an effective

surface roughness prediction model.

Ozel and Karpat (2005) studied the prediction of surface roughness

and tool flank wear using the neural network model. The data set from

measured surface roughness and tool flank wear were employed to train the

neural network models. Predictive neural network models were found to show

better predictions for surface roughness and tool flank wear within the range

in which they were trained.

Luo et al (2005) carried out theoretical and experimental studies to

investigate the intrinsic relationship between tool flank wear and operational

conditions in metal cutting processes using carbide cutting inserts. The

authors developed the model to predict tool flank wear land width which

combined cutting mechanics simulation and an empirical model. The study

revealed that cutting speed had a more dramatic effect on tool life than feed

rate.

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Kohli and Dixit (2005) proposed a neural-network-based

methodology with the acceleration of the radial vibration of the tool holder as

feedback. For the surface roughness prediction in turning process the back-

propagation algorithm was used for training the network model. The

methodology was validated for dry and wet turning of steel using high speed

steel and carbide tool. It was observed that the proposed methodology was

able to make accurate prediction of surface roughness by utilizing small sized

training and testing datasets.

Wang and Lan (2008) used Orthogonal Array of Taguchi method

coupled with grey relational analysis considering four parameters viz. speed,

cutting depth, feed rate, tool nose run off etc. for optimizing three responses:

surface roughness, tool wear and material removal rate in precision turning

on an ECOCA-3807 CNC Lathe. The MINITAB software was explored to

analyze the mean effect of Signal-to-Noise (S/N) ratio to achieve the multi-

objective features. This study not only proposed an optimization approaches

using Orthogonal Array and grey relational analysis, but also contributed a

satisfactory technique for improving the multiple machining performances in

precision CNC turning with profound insight.

2.7 FINITE ELEMENT ANALYSIS

Okubo et al (1982) succeeded in improving the dynamic rigidity of

machine tool structures. This was achieved by employing modal analysis.

This technique was successful in applied machines e.g. machining cell, an

arm of automatic assembling machine and a conventional cylindrical grinder.

Through this technique, they showed successfully reduce chatter and also

achieve improved surface finish of a vertical milling machine, an NC lathe

and a surface grinder.

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Zone – Ching Lin et al (2006) investigated the effect of flank wear

length on deformation of elastic cutting tool (P20 tungsten carbide tool) and

machined work piece (mild steel). They conducted the finite element

simulation under different length of tool flank wear (0.0, 0.2, 0.3, 0.4mm).

The highest temperatures on the tool rake were found to faces decrease (590,

560, 530, 510o c) while increasing the tool flank wear length. Based on the

FEA simulation results they determined that both cutting force and thrust

force increased with an increase in tool flank wear length. Also, normal stress

was found to decrease with an increase in the lengths of tool flank wear

increases. Finally they concluded that when the crater effect of normal stress

is greater than the expansion effect of temperature distribution, an elastic

crater deformation occurred on the tool rack face.

Yung – Chang Yen et al (2004) investigated the estimation of tool

wear in orthogonal cutting for AISI-1045 work piece with an uncoated

carbide tool using the FEA simulation. He conducted continuous cutting

simulation with the speed of 300m/min and the feed rate of 0.145mm/rev.

Several updates are taken with the small cutting time increments of 10sec to

20sec. Based on the estimation of tool wear rate, the model was implemented

into the FEM code (DEFORM-2D) which could lead to a further process

optimization. The tool life was compared with the measured data obtained at

the same condition.

Qin et al (2009) investigated the effects of coating thickness on

diamond coated cutting tools. The insert was modeled in Pro/Engineer

according to the actual geometry with the edge radius of 15µm and the

coating thickness was varied from 5µm to 30µm, extending to about 1.6 mm

substrate bottom. The CAD models of the tool with coating were imported

into FE software ANSYS for thermal stress simulation. The FEA simulation

results revealed that the radial normal stress increased from 1.0GPa for 5µm

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to 1.4GPa for 30µm coating thickness. Also, circumferential normal stress

was found to increase from 2.7GPa for 5µm to 3.7GPa for 30µm coating

thickness. Finally they concluded that thicker coatings have a greater

delaminating resistance and coating failure decreased with increasing coating

thickness.

Attanasio et al (2008) investigated the 3D analysis of an AISI 1045

specimen using an uncoated WC tool for a simple turning process. The 3D

ALE simulation was carried out for cylindrical bars with a diameter of

100mm. The test were conducted at several levels which were selected for

each parameter namely cutting speed (150, 160, 190m/min), feed rate

(0.17, 0.18, 0.25mm/rev), while the depth of cut was fixed to 1.5mm.

Calculated tool wear was compared with experimental method as the same

material data. The results indicated an overall good matching (the average

error is about 6%).

Li et al (2002) investigated the effects of crater wear on the chip

formation process using finite element simulation. They created a FE model

in ABAQUS consideration of assuming that the cutting tool was perfectly

rigid and also the cutting tool was perfectly sharp. Simulation was carried out

at cutting speed of 4.064m/s with 3.861mm width of cut and 50.8µm depth of

cut. The wear test was conducted in three conditions namely are flat tool,

cratered tool having KB=KM/2 and the tool with KB>KM/2. The simulation

result revealed the size of the crater has a significant influence on the

distributions of the tool-chip contact stress and the chip formation. Finally,

they concluded in the case with a flat tool, the simulated cutting and feed

forces are in good agreement with the experimentally obtained data.

Xiea et al (2005) investigated 2D FEM estimates the tool wear in

turning operation. They conducted simulation and wear model for the mild

carbon steel AISI 1045 versus uncoated tungsten carbide tool at a cutting

41

speed 300m/min, feed rate 0.145mm/rev and a depth of cut of 2mm.

ABAQUS/Explicit and ABAQUS/standard with Python user-program to

perform the 2D tool wear estimate in orthogonal cutting of turning operation

and ALE technology is applied for chip separation. The tests were conducted

at various cutting time from starting 0 second to 46 second. After 20 second

cuttings the flank wear exceeded 0.15mm and crater wear to 0.06mm. After

46 second the estimated flank wear was found to just arrive at 0.1mm and

crater wear, 0.03mm. Finally tool geometry was updated according to the

simulation results.

2.8 GAPS IDENTIFIED IN THE LITERATURE REVIEW

In early researches the TiN, TiAlN and DLC coated tools are

not tested, while machining hardened AISI410 martensitic

stainless steels.

In previous researches machining studies and effect of coated

tools are not giving elaborately for AISI410 material.

Tool life and comparative studies of uncoated and coated

tools are not well discussed.

Lacking in prediction of tool wear and surface roughness

models for coated cutting tools while machining AISI410

material.

2.9 SUMMARY OF LITERATURE REVIEW

Based on the literature studies, it was found that tool wear is a major

phenomenon that affects the cutting tool life and the surface roughness of the

workpiece. Many research studies were carried out to reduce the effect of tool

42

wear on surface roughness and to increase the tool life. The cutting tool life

can be improved by of coating given on tool surface. Early research studies

revealed that coated tool performed better than the uncoated tool. This

research work focuses on developing three new cost effective coatings on

cutting tools and studying the effect those newly developed tool by

conducting a turning experiments. The study further does a microstructure

analysis to compare the improvement in tool wear reduction, tool life and

surface roughness.

Literature depicts that a considerable amount of work has been

carried out by previous investigators modeling, simulation and parametric

optimization of surface properties of the product in turning operations. In this

study, an attempt is being made to develop a model for predicting of surface

roughness and crater wear during the machining of martensitic stainless steel

(AISI410). Experimental trials are performed and correspondingly, the RSM

and BPANN models have been developed. Taguchi method has been applied

to solve the optimization problem. The network is trained using suitable

scaling factor for the input variables. After attaining a certain degree of

convergence, the trained weights are fed in to the testing network model,

trained weights are same as that of the having network except that it has the

capacity to just determine the output for corresponding input variables.

Finally the neural network outputs have been compared with the desired

output values and the testing error has been estimated.

The study attempts to do the following: i) it demonstrates detailed

methodology of the proposed both Response surface methodology, BPNN and

optimization technique which integrates S/N ratio analysis based on extended

Taguchi method; ii) it further validates its effectiveness through case studies

43

in which correlated multiple surface roughness characteristics of a turned

product have been optimized.

Figure 2.3 Structure of literature review