1

VIKRAM SARABHAI SPACE CENTRE (VSSC)

PROFILE

VSSC is the lead centre for development of satellite launch vehicles and

associated technologies. The centre pursues active research and development in a host

of distinct technology domains like aeronautic, avionics, composites etc with a view

to achieve self-reliance in the high tech realm of launch vehicle technology.

VSSC has its origin in the Thumba Equatorial Rocket Launching Station

(TERLS). TERLS became operational on November 21, 1963 with the successful

launching of a two-stage sounding rocket, Nike-Apache. After the death of

Dr Vikram Sarabhai, on December 30, 1971, the whole complex at

Thiruvananthapuram was renamed as Vikram Sarabhai Space Centre.

Major programmes of VSSC include Polar Satellite Launch Vehicle (PSLV),

Geosynchronous Satellite Launch Vehicle (GSLV), Rohini Sounding Rocket, Space

Capsule Recovery Experiment, Reusable Launch Vehicles and Air Breathing

Propulsion.

VSSC made significant contribution to Indias maiden mission to the Moon.

Chandrayaan-1. VSSC R&D efforts have included solid propellant formulations.

Another focus area has been navigation systems, the ISRO Inertial Systems Unit (IISU)

established at Vattiyoorkavu is a part of VSSC. VSSC involved in the development of

air-breathing vehicles. A reusable launch vehicle technology demonstrator is under

development, which will be tested soon.

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CHAPTER 1

INTRODUCTION

INCONEL 625 is a nickel based super alloy which is widely used in aerospace

industry. Inconel 625 is a nickel chromium molybdenum solid solution strengthened,

high strength alloy, which retains strength at high temperatures. It is used from

cryogenic temperatures to 980C. Fatigue strength is outstanding, particularly as the

bellows grade, Inconel 625 LCF, where carbon, silicon and nitrogen are controlled to

low levels. The alloys have good oxidation resistance and resist corrosion in any

corrosive media. When exposed to high temperature for long periods, Inconel 625 will

age hardened due to the niobium, titanium and aluminium additions. When aged there is

an increase in strength and some loss of ductility and toughness. These materials are

referred to as difficult to machine since they possess rapid work hardening during

machining which will reduce further metal cutting. Machining of these materials in the

optimum range is required so as to have maximum material removal rate at minimum

surface roughness.

At present ISRO is diversifying its research activities and re-usable launch

vehicle technology is one of them. This diversification equally effects in product

realisation also which demands for realisation of products in super alloy materials like

INCONEL 625. The project is on the theme on optimisation of machining parameters

on Inconel component by addressing the machining difficulties discussed above. For

this attempt Taguchi method, grey relational analysis are used for better result. Hence a

set of optimised parameters is aimed to obtain for immediate application in the

component for better result.

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CHAPTER 2

LITERATURE SURVEY

Lalit Kumar, R Venkataramani, M.Sundararaman, P. Mukhopadhyay and

S.P.Garg [1] investigated the oxidation behaviour of Inconel 625 in 2000 during the

early stages been studied at oxygen pressure of 0.12kPa and 101.3kPa in the

temperature range of 1323K to 1523K by using TGA and between 873 and 1523K by

using XPS,AES and EDS. The results of XPS and AES analysis suggested that two

distinctly different oxidation mechanisms operate, depending on the temperature of

oxidisation.

Kamran Mumtaz, Neil Hopkinson [2] investigated about the top surface and side

roughness of Inconel 625 in 2000 parts processed using selective laser melting and

showed that higher peak powers tended to reduce top surface roughness and reduce side

roughness as recoil pressures flatten out the melt pool and reduce balling formation by

increasing wettability of the melt.

Chen Hong, Donghua Dai, Moritz Alkhayat [3] conducted the study on High-

temperature oxidation performance and its mechanism of TiC/Inconel 625 composites

in 2001 prepared by laser metal deposition additive manufacturing and revealed that

The incorporation of TiC reinforcement in Inconel 625 matrix improved the oxidation

resistance of the LMD-processed parts. For the LMD-processed TiC/Inconel 625

composites, the oxidized layers on the surface were composed of Cr2O 3 and TiO2.

T.E. Abioye, J. Folkes, A.T. Clare [4] Conducted a parametric study of Inconel 625

wire laser deposition in 2003 and found out that Energy per unit length of track and

wire deposition volume per unit length of track significantly influence both the

deposition process characteristics and the track geometrical characteristics. Excessively

low and high wire deposition volume per unit of track for a given energy per unit length

of track resulted in wire dripping and wire stubbing respectively.

Taiwo Ebenezer Abioye [5] conducted an experiment on Laser Deposition of Inconel

625/Tungsten Carbide Composite Coatings by Powder and Wire Feedstock in 2005 and

revealed the fact that the life span of stainless steel components can be extended in

chloride ion rich corrosive environment (e.g. oil and gas environments) by coating them

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with Inconel 625 laser coatings. However, using Inconel 625 wire coatings is more

advantageous because of better process economy and improved corrosion resistance.

Rodge M.K, Sarpate S.S, Sharma S.B [6] investigated on process response and

parameters in wire electrical discharge machining of Inconel 625 in 2007 and concluded

that pulse-on time has the highest rank 1. Therefore, it has the most significant effect

on kerf width. As pulse-on time increase the kerf width increases significantly.

Guru Prasad Dinda, Ashish Dasgupta, Jyoti Mazunder [7] investigated about

Microstructural studies on Inconel 625 components fabricated by laser aid metal

deposition in 2008 and concluded that a variety of different phases can be produced in

Inconel 625 during solidification and during thermal processing.

Abhishek Jivrag, Shashikant Pople [8] studied Erosion Wear Behaviour of Inconel

625 Plasma Transferred Arc Weld (PTAW) Deposits using Air Jet Erosion Tester in

2008 and revealed that the wear rate is maximum at 30, sharply decreases at 60 and is

minimum at 90. Thus rate of wear goes on decreasing from 30 to 90. This provides

the evidence that Inconel 625 despite having hardness value around 350 VHN follows

the wear trend of ductile material and not of hard material as expected from its hardness

value.

E.Pavithran, V.S.Senthil Kumar [9] conducted experimental investigation and

performance evaluation of hydro formed tubular bellows in Inconel 625 alloy in 2010

and summarized that the Inconel 625 bellows exhibits better performance as a material

that can be suitable to construct the bellows.

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CHAPTER 3

PROBLEM DESCRIPTION

Inconel 625 is a nickel based super alloy. These alloys have very important

advantages at the same time it has the drawback of difficult to machine. These have

very high strength to weight ratio. They are highly heat resistant and corrosion resistant.

So it has very useful application in different industrial sectors, aircraft, marine systems

etc... So want to reduce the difficulties involved in the machining of these alloy.

In this project we try to improve the machinability of Inconel 625 alloy by

taking three machining parameters cutting velocity, feed rate and depth of cut. Any

metal can be machined in any values of feed, velocity and depth of cut. But maximum

output is obtained only when optimum ranges of cutting velocity, feed and depth of cut

are used. In this project we aims to find out the optimum value of machining parameters

for machining Inconel 625 by using Taguchi method of optimisation along with grey

relational analysis and ANOVA.

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CHAPTER 4

THEORETICAL STUDY

4.1 SUPER ALLOYS

Super alloys are unique high temperature materials used in gas turbine engines,

which display excellent resistance to mechanical and chemical degradation. Single

crystal super alloys are commonly used as blade materials for aircraft turbines. These

alloys are also called high performance alloys. They are high temperature heat resistant

alloys that can retain their strength at high temperature. Alloying increases the strength

and temperature capabilities but decreases the processability. These alloys exhibits

excellent mechanical strength and creep resistance at high temperature, good surface

stability, corrosion and oxidation resistance. It have a matrix with austenitic face

centred cubic crystal structure. A super alloys base alloying elements are Nickel,

Cobalt and Nickel-iron. These also contains lesser amounts of Tungsten, Molybdenum,

Tantalum, Niobium, Titanium, and Aluminium. Examples of super alloys are Hastelloy,

Inconel, Waspaloy, Rene alloys, Haynes alloys, Incoloy, MP98T, TMS alloy and

CMSX single crystal alloys. Effect of different alloying elements are shown below

Fig 4.1 Effects of different alloying elements

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4.2 CLASSIFICATION OF SUPER ALLOYS

a) Iron-base super alloys:

Iron-base super alloys are those alloys that have iron as the major

constituents, with significant amounts of chromium and nickel and lesser

amounts of molybdenum or tungsten. They are also strengthened by a carbide or

inter metallic precipitate and solid solution. The inter metallic precipitate is

usually of the Ni (Al,Ti) type. They differ from stainless steel in their

chromium-nickel ratios and strengthening mechanisms

.

b) Cobalt-base super alloys:

Cobalt-base super alloys are those alloys that have cobalt as the major

constituent, with significant amount of nickel, chromium and tungsten and lesser

amount of molybdenum, niobium, tantalum, titanium, lanthanum and Iron on

occasion. They are strengthened by solid solution and carbide phases. Cobalt

solid solution alloys can be classified into three groups on the basis of use

a) Alloys for use primarily at temperatures from 650 to 1150 C including

Haynes 25, Haynes 188, Umco-50 and S-816.

b) Fastener alloys MP-35N and MP-159 for use about 650C.

c) Wear resistant stellite-6B.

c) Nickel-base super alloys:

Nickel-base super alloys are defined as those alloys that have nickel as

the major constituent, with significant amounts of chromium. They may contain

cobalt, iron, tungsten, molybdenum and tantalum as major alloying elements.

They are strengthened by solid solution and second phase inter metallic

precipitation. Many nickel base alloys contain small amounts of aluminium,

titanium, niobium, molybdenum and tungsten to enhance either strength or

corrosion resistance. The combination of nickel and chromium gives these alloys

outstanding corrosion resistance.

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4.3 APPLICATIONS

Aircraft and industrial turbines: Disks, bolts, shafts, cases, blades, vanes,

burner cans, afterburners, and thrust reverses.

Steam turbine power plants: Bolts, blades and stack gas reheaters.

Space vehicles: Aerodynamically heated skins and rocket engine parts.

Reciprocating engines: Turbochargers exhaust valve, hot plugs, pre combustion

cups and valve seat inserts.

Metal processing: Hot work tool and dies.

Heat treating equipment: Trays, fixtures and conveyer belts.

Nuclear power systems: Control-rod drive mechanism, valve stems, springs and

ducting.

Chemical and petrochemical industries: Bolts, reaction vessels, valves, piping

and pumps.

4.4 NICKEL-BASE SUPER ALLOYS

Nickel is the fifth most abundant element on earth. The atomic number is 28,

and it in the first row of the d block of transition metals, alongside iron and cobalt. The

atomic weight is 58.71, the weighted average of the five stable isotopes 58, 60, 61, 62

and 64, which are found with probabilities 67.7%, 26.2%, 1.25%, 3.66% and 1.16%,

respectively. The crystal structure is face-centred cubic from ambient conditions to the

melting point, 1455 C, which represents an absolute limit for the temperature capability

of the nickel-based super alloys. The density under ambient conditions is 8907 kg/m.

Thus, compared with other metals used for aerospace applications, for example, Ti

(4508 kg/m) and Al (2698 kg/m), Ni is rather dense. This is a consequence of a small

interatomic distance, arising from the strong cohesion provided by the outer d electrons

a characteristic of the transition metals.

Nickel based super alloys are austenitic and derive their strength from

precipitation hardening during heat treatment (solution treatment and ageing). Most of

the alloys contain significant amounts of chromium, cobalt, aluminium and titanium.

Small amounts of boron, zirconium and carbon are often included. Other elements that

are added, but not to all alloys, include rhenium, tungsten, tantalum and hafnium, from

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the 5d block of transition metals, and ruthenium, molybdenum, niobium and zirconium

from the 4d block. Certain super alloys, such as IN718 and IN706, contain significant

proportions of iron, and should be referred to as nickeliron super alloys. Thus, most of

the alloying elements of nickel are taken from the d block of transition metals. To avoid

possible crucible contamination and to obtain clean alloy, these are melted in vacuum

induction or arc furnace. Boron and iridium are added to increase rupture life. These

alloys are very important in industries because of their wide varieties of severe

operating conditions and corroding environments, high temperature, high stress and

combination of these cases.

4.4.1 PROPERTIES

I. Physical properties:

a) FCC lattice structure till the melting point lattice constant= 0.31567nm at

20C.

b) Density at 25C 8.902gm/cc and at melting point= 7099gm/cc.

c) Boiling point= 2730C.

II. Thermal properties:

a) Co-efficient of thermal expansion= 13.3 m/Mk at 0 to 100C.

b) Recrystallization temperature= 370C.

c) Thermal conductivity= 82.9w/m at 100C.

III. Electrical properties:

a) Electrical resistance of pure nickel is negligible at extremely low

temperature but increases with increase in temperature, = 68.4.

IV. Magnetic properties:

a) It is one of the three metals that are highly ferromagnetic.

b) max= 1240 at B= 1900G.

c) corelic force 167A/m at H= 4.

d) Saturation magnetisation= 0.616T at 20C.

e) Residual induction= 0.0300T.

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V. Mechanical properties:

a) Tensile strength= 317Mpa.

b) O.2% offset yield strength= 53Mpa.

c) Elongation in 50mm= 30%.

d) Hardness value= 64HV for annealed high purity nickel.

4.5 INCONEL-625

INCONEL nickel-chromium alloy 625 (UNSN06625/W.Nr. 2.4856) is used

for its high strength, excellent fabricability (including joining), and outstanding

corrosion resistance. Strength of INCONEL alloy 625 is derived from the stiffening

effect of molybdenum and niobium on its nickel-chromium matrix; thus precipitation

hardening treatments are not required. This combination of elements also is responsible

for superior resistance to a wide range of corrosive environments of unusual severity as

well as to high-temperature effects such as oxidation and carburization.

Alloy 625 is a nonmagnetic, corrosion and oxidation resistant alloy. Its

outstanding strength and toughness in the temperature range cryogenic to 2000F are

derived primarily from the solid solution effects of the refractory metals, columbium

and molybdenum, in a nickel chromium matrix. The alloy has excellent fatigue strength

and stress corrosion cracking resistance to chloride iron.

The outstanding and versatile corrosion resistance of INCONEL alloy 625 under

a wide range of temperatures and pressures is a primary reason for its wide acceptance

in the chemical processing field. Because of its ease of fabrication, it is made into a

variety of components for plant equipment. Its high strength enables it to be used, for

example, in thinner-walled vessels or tubing than possible with other materials, thus

improving heat transfer and saving weight. Some applications requiring the combination

of strength and corrosion resistance offered by INCONEL alloy 625 are bubble caps,

tubing, reaction vessels, distillation columns, heat exchangers, transfer piping, and

valves.

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4.5.1 Chemical composition

TABLE 4.1 Chemical composition of INCONEL 625

COMPOSITION WEIGHT% COMPOSITION WEIGHT%

Nickel 58 min carbon 0.10

Chromium 20 min- 23 max manganese 0.50

Molybdenum 8 min- 10 max silicon 0.50

Iron 5 phosphorous 0.015

Niobium+ tantalum 3.15 min- 4.15max sulphur 0.40

Titanium 0.40 cobalt 1.0

4.5.2 Properties of Inconel 625

a) Physical constants and thermal properties

TABLE 4.2 Physical constants and thermal properties of INCONEL 625

Density 8.44g/cm

Melting range 1290C to 1350C

Coefficient of expansion(20-100C) 12.8m/mC

Thermal conductivity(at 38C) 10.1w/mC

Electrical resistivity (at 38C) 130-cm

Specific heat(at 21C) 410 J/kgC

Permeability at 200 oersted 1.0006

Curie temperature -196C

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b) Mechanical properties of annealed Inconel 625

TABLE 4.3 Mechanical properties of INCONEL 625

Tensile strength 827-1034Mpa

Yield strength 414-655Mpa

Elongation 60-30%

Reduction of area 60-40%

Hardness brinell 145-220

Modulus of elasticity 205.8kN/mm

Modulus of rigidity 79kN/mm

c) Aqueous Corrosion

The high alloy content enables it to withstand a wide variety of severe

corrosive environments like the atmosphere, fresh and sea water, neutral salts,

and alkaline media. Combination of nickel and chromium provides resistance to

oxidizing chemicals, whereas the high nickel and molybdenum contents supply

resistance to non-oxidizing environments, pitting and crevice corrosion, and

niobium prevents intergranular cracking.

d) High temperature oxidation resistance

It has good resistance to oxidation and scaling at high temperature. It has

the ability to retain a protective oxide coating under drastic cyclic conditions.

e) Workability

i. Hot working:

It may be done at 1149C maximum furnace temperature. It

becomes very stiff below 1010C so that it may be reheated. Uniform

reductions are recommended to avoid the formation of a duplex grain

structure.

ii. Cold forming:

Alloy 625 can be cold formed by standard methods. When the

material becomes too stiff annealing can be done for retaining ductility.

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iii. Machinability:

Low cutting speeds. Rigid tool and workpiece, heavy equipment,

ample coolant and positive feeds are general recommendations.

iv. Weldability:

Welding can be done by gas shielded processes using a tungsten

electrode or a consumable electrode. Post weld heat treatment of the

weld are not necessary to maintain corrosion resistance.

4.5.3 Motives behind the use in aerospace

INCONEL 625 super alloy provides higher strength to width ratio compared to

steels. The use of Inconel 625 in such aggressive environments hinges on the face that it

maintains high resistance to corrosion, mechanical & thermal fatique, thermal shock and

creep at elevated temperature. Most of the aerospace parts requires high temperature

resistant metals to withstand high temperature as used in reusable launch vehicle. This

property makes it most preferable in aerospace industry.

4.5.4 Applications

Aerospace Components: bellows and expansion joints, ducting systems, jet

engine exhaust systems, engine thrust-reversers, turbine shroud rings, aircraft

ducting systems, resistance-welded honeycomb structures for housing engine

controls, fuel and hydraulic line tubing, spray bars, heat exchanger tubing in

environmental control systems, combustion system transition liners, turbine

seals, compressor vanes, and thrust-chamber tubing for rocket motors.

Air Pollution Control: chimney liners, dampers, flue gas desulfurization (FGD)

components.

Chemical Processing: equipment handling both oxidizing and reducing acids,

super-phosphoric acid production.

Sea water applications (Marine Service): steam line bellows, Navy ship

exhaust systems, submarine auxiliary propulsion systems, wire rope for mooring

cables, propeller blades for motor patrol gunboats, submarine quick-disconnect

fittings, sheathing for undersea communication cables, submarine transducer

controls.

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Nuclear Industry: reactor core and control rod components, waste reprocessing

equipment.

Offshore Oil and Gas Production: waste flare gas stacks, piping systems, riser

sheathing, sour gas piping and tubing.

Petroleum Refining: waste flare gas stacks.

Waste Treatment: waste incineration components.

4.5.5 Advantages

High strength to width ratio.

Excellent fabricability (including joining), and outstanding corrosion resistance.

Resistance to chloride-ion stress-corrosion cracking.

High tensile, creep, and rupture strength; outstanding fatigue and thermal-fatigue

strength and excellent weldability and brazeability.

Resistance to post weld age cracking.

High temperature resistance.

Age hardening with unique properties of slow aging response that permits

heating and cooling during annealing without danger of cracking.

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CHAPTER 5

MACHINING AND ITS ASPECTS IN HRSA

5.1 MACHINABILITY

Machinability is defined as the ease with which material can be removed from a

metal. The most machinable metal is the one which will permit the fastest removal of

the largest amount of material per grind of tool with satisfactory finish. Machining is

any of the various processes in which a piece of raw material is cut into a desired final

shape and size by a controlled material removal process. Machining is influence by

machine variables, tool variables, cutting conditions, work material variables.

Different factors affecting the machinability of metals are the type of the work

piece, type of tool material, size and shape of tool, type of machining operation, size,

shape and velocity of cut, type and quality of machine used, quality of lubricant used

during machining operation, coefficient of friction between chip and tool.

Machinability index gives a quantitative measurement of machinability. It is

used to compare the machinability of different material. Machinability index of free

cutting steel is taken as 100. It is expressed as ratio of cutting speed of material for 20

min tool life to cutting speed of standard steel for 20 min tool life.

5.2 MACHINABILITY ASSESSMENT

Machinability of a material may be assessed by one or more of the following

criteria:

1) Tool life for a given cutting speed and tool geometry.

2) Ratio of material removal.

3) Magnitude of cutting forces.

4) Quality of surface finish.

5) Dimensional stability of finished work.

6) Heat generated during cutting.

7) Ease of chip disposal.

8) Chip hardness.

9) Shape and size of chip.

10) Power consumption per unit volume of material removed.

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5.3 MACHINING DIFFICULTY OF INCONEL 625

INCONEL 625 is often referred to as difficult to cut material. These materials

now a days causing greater challenges for manufacturing engineers. The high pressure

produced during machining causes a hardening effect which prevents further machining.

The main challenges in machining Inconel 625 are as follows

The high strength of Inconel 625 at cutting temperatures causes high cutting forces,

generates more heat at the tool tip and limits their speed capability.

The presence of hard, abrasive intermetallic compounds and carbides in these alloys

causes severe abrasive wear on the tool tip.

The high capacity for work hardening in Inconel 625 causes depth-of-cut notching

on the tool, which can lead to burr formation on the work piece.

The chip produced during machining is tough and continuous, therefore requiring

acceptable chip breaker geometry.

High-Temperature Alloys have a low thermal conductivity, meaning heat generated

during machining is neither transferred to the chip nor the work piece, but is heavily

concentrated in the cutting edge area.

These temperatures can be as high as 1100C to 1300C, and can cause crater wear

and severe plastic deformation of the cutting tool edge, thereby increasing the

cutting forces.

The chemical reactivity of these alloys facilitates formation of Built Up Edge

(BUE) and coating delamination, leading to poor tool life.

Heat generated during machining can alter the alloy microstructure, potentially

inducing residual stress that can degrade the fatigue life of the component.

Difficulty of machining will shortens tool life and reduces surface finish of the

metal. Extreme care must be taken to ensure the surface integrity of the component

during machining. Most of the major parameters includes the choice of tool life and

coating materials, tool geometry, machining methods, cutting speed, feed rate, depth of

cut, lubrication must be controlled in order to achieve better surface finish.

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CHAPTER 6

MILLING AND ITS ASPECTS IN HRSA

6.1 MILLING

Milling is the most important form of machining, a material removal process,

which can create a variety of features on a part by cutting away the unwanted material.

It is the process of cutting away material by feeding a work piece past a rotating

multiple tooth cutter. The cutting action of many teeth around the milling cutter

provides the fastest method of cutting. The milling process requires a milling machine,

work piece, fixture and cutter. The work piece is a piece of pre-shaped material that is

secured to the fixture, which itself is attached to the platform inside the milling

machine. The cutter is a cutting tool with sharp teeth that is also secured in the milling

machine and rotates at high speeds. By feeding the work piece into the rotating cutter,

material is cut away from the work piece in the form of small chips to create the desired

shape.

Slab milling is one of the most widely used material cutting operation. In slot

milling we will get 100% tool engagement so it can be used as a method of optimisation

of machining parameters.

6.2 TYPES OF MILLING OPERATIONS

A. On the basis of rotational direction of cutter

Table 6.1 Classification based on direction of rotation of cutter

TYPES DESCRIPTION

Up milling In this case movement of cutter teeth is

opposite to the direction of feed motion.

Down milling In this case direction of cutter motion is

the same as that of direction of feed

motion.

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B. On the basis of application

Table 6.2 Classification based on application

TYPES DESCRIPTION

Slab milling In this the cutter width extends beyond

the work piece on both the sides

Slot milling It is used to make slot in the work piece.

Straddle milling In this cutting takes place simultaneously

on both sides of the work piece.

Conventional Face milling In this milling cutter remains overhanging

on both sides of the work piece.

Partial face milling In this case the milling cutter overhangs

only to one side of the work piece.

End milling In this thin cutter are used as compared to

work piece width.

Profile milling It cover multi-axis milling of convex and

concave shapes in two and three

dimensions.

Pocket milling This is a selective portion milling on the

flat surface of work piece used to make

shallow packets there.

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6.3 GENERAL ASPECTS IN HRSA MILLING

Milling of high temperature alloys often requires more rigid and powerful

equipment than the milling of carbon steel.

Cutter accuracy in both radial and axial direction is essential to maintain a constant

tooth load and a smooth operation and to prevent premature failure of individual

cutting teeth.

Cutting edge must be sharp with an optimised edge-rounding, to prevent chip

adherence at the point where the edge exits the cut.

The number of cutting teeth actually in cut during the milling cycle must be as high

as possible. This will give good productivity provided that the stability is good

enough.

Cutting speeds for super alloys are generally low. Common practice is to employ a

fairly low cutting speed in combination with a moderately high feed per tooth, to

produce a chip thickness not less than 0.1mm which prevents work hardening of the

material.

Coolant should be applied in generous quantities around the cutting edge when the

cutting speeds are low, inorder to reduce chip adhesion. Coolant supplied through

the machine tool spindle is recommended for HRSA materials. High pressure

coolant (HPC) will give better tool life.

Down milling (climb milling) should be used, to obtain the smallest chip thickness

where the edge exits cut and reduce any chip adherence.

6.4 CUTTING TOOL MATERIALS USED FOR MACHINING

In machining Ni-based super alloys tooling related technologies are treated

seriously. The appropriate consideration for these technologies can lead to optimum

production output, consistency of machined product and value added activities. Inorder

to produce good quality and economic parts a cutting tool must have

Good wear resistance & High hot hardness

High strength and toughness

Good thermal shock properties.

Adequate chemical stability at elevated temperatures.

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1. Cemented carbide tool :

Carbide tools are the oldest amongst the hard cutting tool materials.

These tools are used to machine Ni based super alloys in the range of 10-

30m/min. these materials are composed of carbide of tungsten, titanium,

tantalum, or some combination of these sintered or cemented in a matrix binder

usually cobalt. The carbide tools can be of two types:

a) Uncoated carbide tools :

The uncoated cemented carbides are commonly used at lower cutting

speeds in the range of 10-30m/min and it gives better performance than that

of coated carbide tools in the lower speed range

b) Coated carbide tools:

Coatings improves the performance of the carbide tools. Coatings are

hard materials and therefore provides a good abrasion resistance. The good

lubricating properties of coating minimize the friction at the tool-chip and

tool-work piece interfaces, thus lowering the cutting temperatures. By using

these cutting tools high speeds can be achieved. Both PVD and CVD coated

carbides are employed. Typical coating materials used includes TiC, TiN,

TiAlN, TiCN, TiZrN and diamond coatings. Multi coated carbide perform

better, in terms of tool life than that of single layer coated carbides. TiAlN

coating is the best for machining Inconel 625.

2. Ceramic tools:

Ceramics are non-metallic materials. The application of ceramic cutting

tool is limited because of their extreme brittleness. The transverse rupture

strength is very low. This means that they will fracture easily when making

heavy interrupted cuts. However the strength of ceramics under compression is

much higher than HSS and carbide tools. Proper tool geometry and edge

preparation play an important role in the application of ceramic tools and help to

overcome their weakness. Some of the advantages of ceramic tools are

High strength for light cuts on very hard work materials.

Extremely high resistance to abrasive wear and crater wear.

Capability of running at high speeds.

Extremely high hot hardness and Low thermal conductivity.

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3. CUBIC BORON NITRIDE

CBN is the hardest material available after diamond, and doesnt occur in

nature. The synthesis of polycrystalline CBN is composed of about 50-90% of

CBN and ceramic binders such as titanium carbide and titanium nitride. A high

CBN content is better in cutting super alloy. Higher CBN content was better

because of their hardness. The hardness increases almost linearly with the CBN

content. Compared to ceramics, CBN has a better hardness and resistance to

fracture but poor chemical resistance. These are recommended to machine

Inconel 625 in a speed range of 120-240m/min.

6.5 MILLING PARAMETERS

There are three major cutting parameters to be controlled in any milling operation.

These three parameters are cutting speed, feed rate and depth of cut. By optimising

these parameters better results can be obtained in milling Inconel 625. These parameters

are described below:

1. Cutting velocity

Cutting speed of a milling cutter is its peripheral linear speed resulting from

operation. It is expressed in m/min. The cutting speed can be derived from the

below formula. Spindle speed of the milling machine is selected to give the desired

peripheral speed of the cutter.

V= 1000 (6.1)

Where, V= linear cutting speed in m/min

d= diameter of milling cutter in mm

n= cutter speed in rev/min

2. Feed rate

It is the rate with which the work piece under process advances under the

revolving milling cutter. It is known that revolving cutter remains stationary and

feed is given to the work piece through worktable. Generally feed is expressed in

three ways:

22

a Feed per tooth(t)

It is the distance travelled by the work piece between engagements by the

two successive teeth expressed as mm/tooth.

b Feed per revolution(rev)

Travel of work piece during one revolution of milling cutter expressed as

mm/rev.

c Feed per unit of time(m)

It is the distance advances by the work piece in unit time expressed as

feed/min or feed/sec.

Above described three feed rates are mutually convertible:

m=n*rev=z*n*t (6.2)

Where, n= rpm of the cutter

z= number of teeth in the milling cutter

3. Depth of cut

Depth of cut in milling operation is the measure of penetration of cutter into the

work piece. It is the thickness of the material removed in one pairs of the cutter

under process. One pairs of cutter means when the cutter completes the milling

operation from one end of the work piece to the other end. In other words it is the

perpendicular distance measured between the original and final surface of work

piece measure in mm.

4. Material removal rate(MRR)

It is the volume of the metal removed in unit time.

MRR= ()

(min) (6.3)

23

CHAPTER 7

METHODOLOGY

7.1 PROJECT DESCRIPTION

RPFF (rocket payload fabrication facility) is a section of VSSC where machining

of different aerospace parts are done. Presently machining is carried out on parts for

reusable launching vehicle. Inconel 625 is widely used in different parts in many

aerospace application. Inconel 625 has wide application in reusable launching vehicles

because of the property to withstand high temperature. Inconel 625 is very difficult to

machine and as all aerospace parts should have high surface quality, better machining

possibilities should be investigated. This project investigates in optimising the

machining parameters of slot milling of Inconel 625 super alloy to have better surface

quality and less production time which could be benefited for milling operations.

24

7.2 SCOPE OF THE PROJECT

LITERATURE SURVEY

SELECTION OF MATERIAL

SELECTION OF TOOL INSERT

MACHINING

PROCESS

OPTIMISATION

TECHNIQUE

SELECTION OF

SPEED, FEED &

DEPTH OF CUT

TAGUCHI BASED

GREY

RELATIONAL

ANALYSIS

CNC MILLING OPTIMISATION

ANOVA

CONCLUSION

RESULT

25

7.3 WORK PIECE MATERIAL

The work piece material used in the machining test was Inconel 625. Three

samples of Inconel 625 each of length 160mm, width 53mm, and thickness 40mm were

taken for the experiment.

7.4 CUTTING CONDITIONS

Cutting condition is created by appropriate selection of cutting parameter values

corresponding to cutting speed, feed, axial and radial depth of cut. The ranges of cutting

parameters are determined using Sandvik coromant tool catalogue. In this study slot

milling operation is carried out. In slot milling operation 100% cutter engagement is

possible. Therefore we can assess the conditions on any engagement from the result

obtained from the experiment. The milling operation is carried out in a wet condition. A

6% soluble oil through coolant system at 1 bar pressure and 12 litre/minute flow rate.

7.5 CUTTING TOOL

The cutting tool used in the machining test was Sandvik bull nose end mill cutter

(25mm diameter, 2 flute) with a PVD coated cemented carbide insert. The insert used

was PVD coated cemented carbide round insert (S30T grade). It has high edge strength

and bulk toughness. It has well resistant to micro chipping and keeps the cutting edge

line intact longer. The grade focuses on high performance at elevated cutting speed.

26

Specification of Cutting tool and tool insert

Table 7.1 Specification of cutting tool and tool insert

Cutting tool Bull nose end mill cutter

Insert holder Seco tools

Insert RCKT10T3MO-PM

Insert engagement 100%

Insert grade YBG302

Chip breaker Through type

Insert grade description nc-TiAlN nano PVD

coating on high

toughness carbide, a

Nano Coating grade

Insert work piece

material

P25-P40, M25-M40

Specification of tool and tool holder

Table 7.2 Specification of tool and tool holder

Tool diameter 25mm

Tool holder KENAMETAL ISOBT50

Holder taper BT50

Made Kennel metal

7.6 MACHINE TOOL

The machine tool used in the cutting test was Jyoti EXF 1680 which is a three

axis CNC machine. The machine configuration is of fixed bed moving column and its

spindle is delivering a maximum torque of 472-712Nm depending upon the load

condition. With its high torque motor and gearbox the table size of machine is

2000mm*800mm and its working volume is 1600mm*800mm*800mm. the machine is

installed with Siemens 840D-SL controller with updated machining cycles. This

machine complies with VDI/DGQ 3447 standard and maintain its positional uncertainty

27

within 0.001mm and repeatability within 0.005mm. shopmill software is installed in the

machine.

7.7 PROCEDURE

The experiment was conducted as per the details in Jyoti CNC machine. Nine

experiments are done according to taguchi method in three sample (three experiments

on each sample). The samples were fixed properly by suitable mechanical clamping.

Correct values of spindle speed, feed and depth of cut was provided on the program

software in the CNC machine. After attaining all the precautions experiment was

started. Time for cutting each slot was noted by using a stop watch. The machined

surface of nine samples were inspected for surface roughnes (Ra) using Talysurf

measuring instrument. Material removal rate is used as another performance parameter

to evaluate the machining performance. Material removal rate is expressed as the

amount of material removed under a period of machining time and is expressed as

mm/min. experimental setup is shown in the figure.

Fig 7.1 Experimental setup

28

CHAPTER 8

DESIGN OF EXPERIMENT

8.1 PLAN OF EXPERIMENT

Dr Genichi Taguchi is a Japanese quality management consultant who has

developed and promoted a philosophy and methodology for continuous quality

improvement in product and process. The methodology of Taguchi which combine the

experiment design theory and the quality loss function concept have been used in

developing robust designs of products and processes.

The degrees of freedom for three parameters in each of three levels were

calculated as follows:

Degree of Freedom (DOF) = number of levels -1

For each factor, DOF equal to:

For (Vc); DOF = 3 1 = 2

For (f); DOF = 3 1 = 2

For (d); DOF = 3 1 = 2

In this project nine experiments were conducted at different parameters. For this

Taguchi L9 orthogonal array was used, which has nine rows corresponding to the

number of tests, with three columns at three levels. L9 orthogonal array has eight DOF,

in which 6 were assigned to three factors (each one 2 DOF) and 2 DOF was assigned to

the error. For the purpose of observing the degree of influence of the process parameters

in machining. The process parameters and their levels are given in the table below:

Table 8.1 Process parameters and their levels

PARAMETERS UNIT LEVEL1 LEVEL 2 LEVEL3

Cutting velocity m/min 30 35 40

Feed rate Mm/tooth 0.1 0.15 0.2

Depth of cut mm 1 2 3

29

8.2 TAGUCHI EXPERIMENTAL RESULT

By using Taguchi plan of experiment and by using the procedures explained in

the previous chapters 9 experiments were conducted 3 on each samples (total 3

samples). The figure showing the slots prepared is shown below:

Fig 8.1 Slots prepared on the samples

30

In this work, L9 Orthogonal Array design matrix is used to set the control

parameters to evaluate the process performance. The design matrix used in this work

and the corresponding results of surface roughness and material removal rate are shown

in the table below.

Table 8.2 Results obtained from the experiment

EXP NO PARAMETER COMBINATIONS SURFACE

ROUGHNESS

(microns)

MRR

(mm/s) V f d

1 1 1 1 0.3084 17.09

2 1 2 2 0.4161 55.06

3 1 3 3 1.5312 42.97

4 2 1 2 0.4290 35.33

5 2 2 3 0.5277 96.36

6 2 3 1 0.5110 42.4

7 3 1 3 0.2659 49.68

8 3 2 1 0.4773 27.17

9 3 3 2 0.7504 84.8

8.3 OPTIMISATION OF MACHINING PARAMETERS

In this project optimisation of machining parameters are done by using two

statistical tools. They are Grey relational analysis and Analysis of variance. Each

methods are discussed in detail in the following sections.

8.3.1 GREY RELATIONAL ANALYSIS (GRA)

The grey relational analysis (GRA) associated with the Taguchi method

represents a rather new approach to optimisation developed by Deng in 1989. The grey

theory is based on the random uncertainty of small samples which develop into an

evaluation technique to solve certain problems of system that are complex and having

incomplete information. The grey relational analysis (GRA) is one of the powerful and

effective soft-tool to analyse various processes having multiple performance

characteristics.

31

8.3.1.1 Steps in GRA

1. Normalization of experimental results in GRA

Data pre-processing is normally required, since the range and unit in one data

sequence may differ from others. It is also necessary when the directions of the

target in the sequences are different. Normalization is the process in which

transformation of input data takes place to an evenly distributed data in a scale

range between 0 and 1. In this project a linear normalization of the raw data for

surface roughness and MRR were performed in the range between 0 and 1 which is

also called grey relational generation.

Normalization of Ra

Surface roughness values should be minimised to 0. So we take smaller

the better equation for normalising the Ra values.

x(k) = max ()()

max ()min () (8.1)

where, yi(k) value after grey relational generation

min yi(k) smallest value of yi(k) for the kth response

max yi(k) largest value of yi(k) for the kth response

Normalization of MRR

Normalization of MRR is based on larger the better criterion because

MRR should be maximised.

xj(k)= ()min ()

max ()min () (8.2)

Where yi(k) value after grey relational generation

min yi(k) smallest value of yi(k) for the kth response

max yi(k) largest value of yi(k) for the kth response

32

2. Grey relational coefficient

Based on normalized experimental data, grey relational coefficient is

calculated to represent the correlation between the desired and actual

experimental data.

(k)= min + max

+ (8.3)

Where i difference between absolute value x(k)and xi(k)

distinguishing coefficient 0

33

The below table shows the normalized value, grey relational coefficient

and grey relational grade for each experiment. Higher grey relational

coefficient better the product quality.

Table 8.3 Table for calculating grey relational grade

EXP

NO

NORMALIZED

VALUES

GREY

COEFFICIENT

GREY GRADE

SR MRR SR MRR GREY

GRADE

RANK

1 0.9665 0.0000 0.9372 0.3333 0.6352 5

2 0.8813 0.4790 0.8081 0.4897 0.6489 4

3 0.0000 0.3265 0.3333 0.4261 0.3797 9

4 0.8711 0.2301 0.7950 0.3937 0.5944 6

5 0.7931 1.0000 0.7073 1.0000 0.8537 1

6 0.8063 0.3193 0.7208 0.4235 0.5722 7

7 1.0000 0.4111 1.0000 0.4592 0.7296 2

8 0.8329 0.1272 0.7495 0.3642 0.5569 8

9 0.6171 0.8542 0.5663 0.7742 0.6703 3

4. Find out the response table for grey relational grade

The mean of the grey relational grade for each level of parameter and the total

mean of the grey relational grade for the 9 experiments were calculated and

tabulated as shown below:

Table 8.4 Response table for grey relational grade

PROCESS

PARAMETERS

GREY RELATIONAL GRADE

LEVEL 1 LEVEL 2 LEVEL 3 MAX-

MIN

RANK

Cutting velocity 0.5546 0.6734* 0.6523 0.1188 2

Feed rate 0.6531 0.6865* 0.5407 0.1458 1

Depth of cut 0.5881 0.6379 0.6543* 0.0662 3

Total mean value of grey grade = 0.6268

*Optimum levels

34

8.3.2 ANALYSIS OF VARIANCE (ANOVA)

The purpose of analysis of variance (ANOVA) is to investigate which of the

process parameters significantly affect the performance characteristics. This is

accomplished by separating the total variability of the grey relational grades, which is

measured by the sum of the squared deviation from the total mean of the grey relational

grade into contributions by each machining parameter and the error. The analysis of

variance (ANOVA) test establishes the relative significance of the individual factors

and their interaction effects.

The total sum of squared deviation SSt= total sum of squared deviation by each

parameters (SSf) + sum of squared deviation by error (SSe)

8.3.2.1 Steps for ANOVA calculations

1. Calculate degrees of freedom of each parameters (DF)

It is a measure of the amount of information that can be uniquely determined

from a given set of data. DOF for data concerning a factor equals one less than the

number of levels .The degrees of freedom for three parameters in each of three

levels were calculated as follows:

Degree of Freedom (DOF) = number of levels-1 (8.5)

2. Calculate the sum of squares of each parameters (SS)

Sum of squares of each parameters is given by

Sum of squares due to factor A= [(no: of experiments at level A)*(mA-m) ] +

[(no: of experiments at level A2)*(mA2-m) ] +

[(no: of experiments at level A)*(mA-m) ](8.6)

Sum of squares of error SSe= SSt-SSf (8.7)

35

3. Variance for each factors (MS)

It measures the distribution of the data about the mean of the data .Variance of

each factor is given by

Variance for each factor=

(8.8)

4. F ratio of each factor (F)

It is the ratio of variance due to the effect of a factor and variance due to the

error term. This ratio is used to measure the significance of the factor under

investigation on the performance characteristics with respect to the variance of all

the factors included in the error term.

F ratio for each factor=

(8.9)

5. Contribution of each factors (C)

It is obtained by dividing the sum of square of the factor by total sum of square

and multiplied by 100. It is denoted by C and can be calculated using the following

equation:

Contribution of each parameters=

*100. (8.10)

Table 8.5 Results of ANOVA

Source DOF SS MS F % C

Vc 2 0.0241 0.01205 0.3532 17.93

f 2 0.0350 0.0175 0.513 26.03

d 2 0.007131 0.003566 0.1045 5.30

Error 2 0.06821 0.03411 50.736

Total 2 0.13444 100

36

8.4 CONFIRMATION EXPERIMENT

After evaluating the optimal parameter settings, the next step is to predict and verify

enhancement of the quality characteristics using optimal parametric combination. The

estimated grey relational grade

=m+ (i-m) (8.11)

Where m= total mean grey relational grade

i=mean grey relational grade at the optimum level

Fig 8.2 Specimen with confirmation slot

37

Table 8.6 Results of confirmation experiment

Initial machining

parameter

Optimal machining parameters

prediction Experiment

Setting level Vfd Vfd Vfd

Surface roughness 0.5277 0.562

MRR 96.36 100.64

Grey grade 0.8537 0.7606

Improvement in

grey grade

0.0931

38

CHAPTER 9

CALCULATIONS

9.1 CALCULATION FOR TABLE 8.1

All the values in the table 8.1 are chosen from the catalogue book of Sandvick

coromant.

9.2 CALCULATION FOR TABLE 8.2(SET NO:1)

Average response values

1. Surface roughness

Surface roughness values are obtained from talysurf measuring instrument.

For set no: 1 Ra= 0.3044/0.3123

Average Ra= 0.3044+0.3123

2 = 0.3084microns (9.1)

2. Material removal rate

Material removal rate is obtained by calculating the volume of metal removed

from the specimen and the time taken for preparing the slot.

Length of the slot=53mm

Breadth of the slot=25mm

Height of the slot=1mm

Time taken=77.53s

Volume= length of the slot*breadth of the slot*height

= 53*25*1

=1325mm

MRR= 1325

77.53 = 17.09mm/s (9.2)

39

9.3 CALCULATION FOR TABLE 8.3(SET NO: 1)

1. Normalized values

a Surface roughness

x(k) = max ()()

max ()min () (9.3)

max yi(k)=1.5312microns

min yi(k)=0.2652microns

yi(k)=0.30835microns

x1=1.53120.30835

1.53120.2652=0.9665

b Material removal rate

x(k)= ()min ()

max ()min () (9.4)

min yi(k)=17.09mm/s

max yi(k)=96.36mm/s

yi(k)=17.09

x1=17.0917.09

96.3617.09=0.0000

2. Grey relational coefficients

a Surface roughness

(k)= min + max

+ (9.5)

40

Consider the following table

Table 9.1 Table for calculating values

SLNO 1- NORMALIZED Ra 1-NORMALIZED MRR

1 1-0.9665=0.0335 1-0.0000=1.0000

2 0.1187 0.5210

3 1.0000 0.6735

4 0.1289 0.7699

5 0.2069 0.0000

6 0.1937 0.6807

7 0.0000 0.5889

8 0.1671 0.8728

9 0.3829 0.1458

From above table,

min=0.0000

max=1.0000

=0.5 (assume)

i=0.0335 (respective values from the above table)

1=0+(0.51)

0.0335+(0.51)=0.9372

b Material removal rate

Considering the same above equation and table

min=0.0000

max=1.0000

=0.5

i=1.0000

1=0+(0.51)

1.0000+(0.51)=0.3333

3. Grey relational grade

a Grey grade

1=0.9372

2=0.3333

41

n=2

=1

() (9.6)

=0.9372+0.3333

2

=0.6353

b Rank

Ranks are provided according to the decreasing order of grey grades for

all experiments. 1st rank corresponds to highest value of grey grade among 9

values.

9.4 CALCULATIONS FOR TABLE 8.4 (PARAMETER: Vc)

a Level 1

Consider Taguchis parameter combination, in that level 1 of cutting speed is

used in 1, 2 and 3rd experiment. Take the average value of grey grades of the 3

experiment.

Level 1=0.6353+0.6489+0.3797

3=0.5546

b Level 2

Level 2 of cutting speed is used in 4, 5 and 6th experiment. Take the average

value of grey grades of the 3 experiment.

Level 2=0.5944+0.8537+0.5722

3=0.6734

c Level 3

Level 3 of cutting speed is used in 7, 8 and 9th experiment. Take the average

value of grey grades of the 3 experiment.

Level 3=0.7296+0.5569+0.6703

3=0.6523

42

d Max-Min

Max=0.6734

Min=0.5546

Max-Min=0.6734-0.5546=0.1188

e Rank

Ranks are provided according to the decreasing order of Max-Min values for each

parameter.

f Mean value of grey relational grade

Mean=0.6353+0.6489+0.3797+0.5944+0.8537+0.5722+0.7296+0.5569+0.6703

9=0.6268

9.5 CALCULATIONS FOR TABLE 8.5 (SOURCE: Vc)

a Degree of freedom (DOF)

Degree of Freedom (DOF) = number of levels -1 (9.7)

= 3 1 = 2.

b Sum of squares (SS)

Sum of squares due to factor A= [(no: of experiments at level A)*(mA-m) ] +

[(no: of experiments at level A2)*(mA2-m) ]+

[(no: of experiments at level A)*(mA-m) ]. (9.8)

= [3*(0.5546-0.6268)2] + [3*(0.6734-0.6268)2] +

[3*(0.6523-0.6268)

=0.0241

Where mA1= respective values of Vc from response table

m= mean value of grey grade

no: of experiments at each level=3

c Variance of each factor (MS)

Variance for each factor=

(9.9)

=0.0241

2 =0.01205

43

d F ratio

F ratio for each factor=

. (9.10)

=0.01205

0.03411

=0.35

e % contribution

Contribution of each parameters=

*100. (9.11)

=0.0241100

0.13444

=17.93%

9.6 CALCULATIONS FOR TABLE 8.6

Optimum value of grey relational grade

= m+ (i-m) (9.12)

=0.6268+ [(0.6734-0.6268) + (0.6865-0.6268) + (0.6543-0.6268)]

=0.7606.

Improvement in grey grade=0.8537-0.7606

=0.0931.

44

CHAPTER 10

RESULT

The nine experiments were conducted on 3 samples (3 experiments on each sample)

according to Taguchi L9 combination set.

The minimum surface roughness was 0.2659microns and corresponding material

removal rate was 49.68mm/min.

The maximum surface roughness was 1.5312microns and the corresponding

material removal rate was 42.97mm/min.

According to grey relational analysis, the optimum value of machining parameter is

found out to be set 223. i.e. Vc=35m/min, f=0.15mm/tooth and d=3mm.

From analysis of variance, most significant parameter is feed rate with highest

contribution on performance characteristics followed by cutting velocity and depth

of cut.

The confirmation experiment was done after optimising the parameters using

Taguchi based grey relational analysis.

Optimised result gave a surface roughness value of 0.562microns and corresponding

material removal rate was 100.64mm/min.

45

CHAPTER 10

CONCLUSION

It has been established that Taguchi based grey relational analysis is an effective

optimisation tool for determining the optimum machining parameters for machining of

Inconel 625 super alloy in slot milling . It has been found that according to grey

relational analysis, the optimum value of machining parameter are Vc=35m/min,

f=0.15mm/tooth and d=3mm. After comparing the confirmation result it has been found

that there is an increase in material removal rate. Analysis of variance shows that feed

rate is the most significant machining parameters followed by cutting velocity and depth

of cut.

46

REFERENCE

1. Basim A. Khidhir, Bashir Mohamed Machining of nickel based alloys using

different cemented carbide tools.

2. I.A Choudhury, M.A El-Baradie Machinability of nickel-base super alloys:

general review.

3. Lohithaksha M. Maiyar, R. Ramanujam Dr, K. Venkatesan, J. Jerald, Optimization

of Machining Parameters for end Milling of Inconel 718 Super Alloy Using Taguchi

based Grey Relational Analysis

4. Vani Shankar, K Bhanu Sankara Rao, S.L Mannan Microstructure and mechanical

properties of Inconel 625 superalloy

5. Yigit Kazancoglu, Ugur Esme, Melih Bayramo glu, Onur Guven, Sueda Ozgun

Multi-objective optimisation of the cutting forces in turning operation using grey-

based taguchi method.