1

EXPERIMENTAL STUDIES ON MECHANICAL

PROPERTIES OF ALUMINIUM / RED MUD METAL

MATRIX COMPOSITE FABRICATED BY STIR

CASTING METHOD

A PROJECT REPORT

Submitted by

PON SWARNA RAJA PANDIAN.S (9908009128)

RAGHUNATH.K (9908009138)

RAJKUMAR.D (9908009149)

In partial fulfillment for the award of the degree

Of

BACHELOR OF TECHNOLOGY

IN

MECHANICAL ENGINEERING

DEPARTMENT OF MECHANICAL ENGINEERING

KALASALINGAM UNIVERSITY (Kalasalingam Academy of Research and Education)

KRISHNANKOIL- 626 126 Academic Year (2011-2012)

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DEPARTMENT OF MECHANICAL ENGINEERING

KALASALINGAM UNIVERSITY

(Kalasalingam Academy of Research and Education)

Krishnankoil- 626 126.

DECLARATION

We hereby declare that the project work done in ―EXPERIMENTAL STUDIES ON

MECHANICAL PROPERTIES OF ALUMINIUM / RED MUD METAL MATRIX

COMPOSITE FABRICATED BY STIR CASTING METHOD‖ in partial fulfilment of

requirements for the award of Bachelor of Technology in Mechanical Engineering, under the

supervision of Mr.RAJESH.S, Assistant Professor-I, Department of Mechanical Engineering,

Kalasalingam University, Krishnankoil.

PON SWARNA RAJA

PANDIAN.S

RAGHUNATH.K RAJKUMAR.D

9908009128

9908009138 9908009149

B.Tech (Mech. Engg) B.Tech (Mech. Engg) B.Tech (Mech. Engg)

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DEPARTMENT OF MECHANICAL ENGINEERING

KALASALINGAM UNIVERSITY (Kalasalingam Academy of Research and Education)

Anand Nagar, Srivilliputhur

KRISHNANKOIL- 626 126

BONAFIDE CERTIFICATE

Certified that this project report ―EXPERIMENTAL STUDIES ON MECHANICAL

PROPERTIES OF ALUMINIUM / RED MUD METAL MATRIX COMPOSITE

FABRICATED BY STIR CASTING METHOD” is the bonafide work of ― PON

SWARNA RAJA PANDIAN.S (9908009128), RAGHUNATH.K (9908009138),

RAJKUMAR.D (9908009149) ” who carried out the project work under my supervision.

Dr.S.Rajakarunakaran Mr.Rajesh.S

HEAD OF THE DEPARTMENT SUPERVISOR,

Assistant Professor I

Department of Mechanical Engineering Department of Mechanical Engineering

Project Viva-voce held on _______________

Internal Examiner External Examiner

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ACKNOWLEDGEMENT

A project of this magnitude and nature requires kind cooperation and support for

successful completion. At the outset, we wish to express our sincere gratitude to our Vice-

chancellor Dr. S. Radhakrishnan for giving us kind permission to do this project.

We express our deep sense of gratitude and indebtedness to Mr. S. Rajesh, Assistant

Professor – I, Department of Mechanical Engineering, Kalasalingam University, for his kind

guidance and encouragement throughout this project work.

We also express our hearty gratitude to Dr. S. Rajakarunakaran, Senior Professor

and Head of the department, Department of Mechanical Engineering, Kalasalingam

University, for his valuable suggestion.

We express our deep sense of gratitude and indebtedness to Dr. J.T.Winowlin

Jappes, Professor & Head of CENTER FOR COMPOSITE MATERIALS, Department of

Mechanical Engineering, Kalasalingam University and Prof. N. Sureshkumar, Associate

Professor, Department of Civil Engineering, Kalasalingam University, for their valuable

suggestions and helping us in carrying out our experiments in the Tribometer and Brinell

hardness testing Machine respectively during the course of our project.

We also express our hearty gratitude to all the Faculty members of CENTER FOR

COMPOSITE MATERIALS, Department of Mechanical Engineering, and Kalasalingam

University, for their valuable advises in our progress.

We also extend our sincere thanks to Mr. A. Marimuthu, Lab Technician (Machine

Shop) Mr. R. Muthumani, Lab Technician (Machine Shop), Mr.B. Palmurugan, Lab

Technician (Fitting Shop), Mr. C. Pandimuneeshwaran, Lab Technician (Center For

Composite Materials) Mr. M. Suryakumar, Lab Technician (Strength of Materials Lab) for

providing us help throughout the project.

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Abstract

Red mud emerges as the major waste material during production of alumina from bauxite by

the Bayer‘s process. It comprises of oxides of iron, titanium, aluminium and silica along with

some other minor constituents. Based on economics as well as environmental related issues,

enormous efforts have been directed worldwide towards red mud management issues i.e. of

utilization, storage and disposal. Different avenues of red mud utilization are more or less

known but none of them have so far proved to be economically viable or commercially

feasible. It is generally agreed that resistance to wear of MMCs is created by reinforcement

and also the wear properties are improved remarkably by introducing hard inter metallic

compound into the aluminium matrix. The reinforcing materials are generally SiC, Al2O3,

TiB2 etc and are costly. The present research work has been undertaken with an objective to

explore the use of red mud as a reinforcing material as a low cost option. This is due to the

fact that red mud alone contains all these reinforcement elements and is plentifully available.

Experiments have been conducted under laboratory condition to assess the wear

characteristics of the aluminium red mud composite under different working conditions in

pure sliding mode on a pin-on-disc machine. This has been possible by fabricating the

samples through usual stir casting technique. The samples are fabricated with LM 25 matrix

material with different % of red mud material. Dispersion of red mud particles in aluminium

matrix improves the hardness of the matrix material and also the wear behaviour of the

composite. While increasing the % of reinforcements of the material there is decrease in wear

characteristic. Finally, Artificial Neural Network (ANN) was employed to develop

mathematical model for wear prediction using Decision Prediction Tool 5.7.1. The accuracy

of the developed model is 83%.

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TABLE OF CONTENTS

CHAPTER

NO

TITLE PAGE

NO

ABSTRACT

LIST OF TABLE

LIST OF FIGURE

LIST OF SYMBOL

i

ii

iii

iv

1 INTRODUCTION 1

1.1 Need of metal matrix composite 1

1.2 Application of metal matrix composite 1

1.3 Materials and structure 2

2 LITERATURE REVIEW 4

2.1. Objective of the Project 6

3 COMPOSITE MATERIALS 7

3.1 Classification of composite materials 8

4 METAL MATRIX COMPOSITE PROCESSING METHODS 13

4.1 Liquid state fabrication techniques 13

4.2 Solid state fabrication techniques 15

4.3 Vapour deposition 18

5 PROPERTIES OF COMPOSITE MATERIALS 19

5.1 Various mechanical properties 19

5.2 Physical properties 21

5.3 Effect of various parameter 23

5.4 Wear characteristics 25

6 ARTIFICIAL NEURAL NETWORK 31

6.1 Background 31

6.2 Mathematical model 32

6.3 Activation functions 33

6.4 Network functions 35

6.5 Learning 36

6.6. Supervised learning 36

6.7 Unsupervised learning 37

6.8 Applications 37

6.9 Types of neural networks 38

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7 LIST OF EQUIPMENTS USED 39

7.1 Stir casting setup 39

7.2 Hardness testing machine 40

7.3 Center lathe 41

7.4 Pin on disc Tribometer 42

7.5 scanning electron microscope 43

8 EXPERIMENTAL METHODOLOGY 44

8.1 Material selection 45

8.2 Dispersion phase – red mud 45

9 RAW MATERIAL PRE PROCESSING 48

9.1 Processing of raw material 48

9.2 Combination of raw materials 48

10 FABRICATION OF METAL MATRIX COMPOSITE 50

10.1 Preparation of mould 50

10.2 Melting and casting of specimen 51

10.3 Dispersion processing 52

10.4 Hardness test 53

10.5 Density of cast specimen 54

10.6 Wear test 54

10.7 composite fabricated by stir casting method on micro structure 55

11 RESULT AND DISCUSSION 56

12 REFERENCE 63

13 ANNEXURE 65

14 CONCLUSION 66

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LIST OF TABLES

Table Page

No

5.1

Symptoms of wear

No

30

8.1 Chemical composition of Al LM25 45

8.2 Mechanical properties of Aluminium LM 25 45

8.3 Chemical composition of Red mud 47

9.1 Combination of raw materials 49

11.1 Hardness values of casted specimens 59

11.2 Density values of casted specimens 59

11.3 Wear test on casted specimens 59

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LIST OF FIGURES

Figure Page

No

1.1

Types of composite materials

No

2

1.2 Structures of composites 3

3.1 Classification of composite materials with metal matrix 11

3.2 Types of Particles 11

4.1 Squeeze casting infiltration 14

4.2 Stir casting setup 15

5.1 Archimedes principle 22

6.1 Mathematical process of artificial neural network 33

6.2 Style of Neural computation 35

7.1 Stirrer setup 39

7.2 Brinell hardness testing machine 40

7.3 Impact testing machine 41

7.4 Centre lathe 42

7.5 Pin on disc Tribometer 43

8.1 Flow chart of experimental procedure 44

8.2 XRD Image of Red Mud 47

9.1 Stir casting 49

10.1 Green sand mould 51

10.3 Sample specimen for hardness test 53

10.7 SEM image of Specimen 56

11.1 Graph showing change in hardness 58

11.2 Graph showing change in density 58

iii

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LIST OF SYMBOLS

Symbol Explanation

Σ(sigma) Summation

Φ(phi) Activation function

ν(nu) Threshold function

€(euro) Computation

iv

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CHAPTER 1

1. INTRODUCTION

Material is anything made of matter, constituted of one or more substances. Wood, cement,

hydrogen, air and water are all examples of materials. Sometimes the term "material" is used

more narrowly to refer to substances or components with certain physical properties that are

used as inputs to production or manufacturing. In this sense, materials are the parts required

to make something else, from buildings and art to stars and computers.Metal–matrix

composites (MMCs) are known as the most useful and high-tech composite materials in our

world. MMCs are very important because of their high ratio of strength and weight, high

Young modulus and high abrasive properties.

1.1 NEED OF METAL MATRIX COMPOSITE

The need for composite materials has become a necessity for modern technology, due to the

improved physical and mechanical properties. Metal matrix composites (MMC) have been

developed in recent years. Metal Matrix Composites have emerged as a class of material

capable of advanced structural, aerospace, automotive, electronic, thermal management and

wear applications. A composite material is a material consisting of two or more physically

and/or chemically distinct phases. The composite generally has superior characteristics than

those of each of the individual components. Usually, the reinforcing component is distributed

in the continuous or matrix component. When the matrix is a metal, the composite is termed a

metal-matrix composite (MMC).

1.2 APPLICATION OF METAL MATRIX COMPOSITE

Metal composite materials have found application in many areas of daily life for quite some

time Metal Matrix Composites (MMC‘s) are increasingly found in the automotive industry

These materials are produced in situ from the conventional production and processing of

metals. Metal matrix composites (MMCs) are a class of materials with the ability to blend the

properties of ceramics (high strength and high modulus) with those of metals or alloys

(ductility and toughness) to produce significant improvements in the mechanical properties of

the composite over those of the monolithic metal or alloys. Among the various matrix

materials available, aluminium and its alloys are widely used in the fabrication of MMCs.

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Aluminium MMCs exhibit an excellent combination of high specific strength and stiffness,

high wear resistance, good seizure resistance, improved fatigue and creep strength as

compared to the base alloy. The MMC finds various applications in different fields as follows

MMCs represent the Next Generation of solutions for today‘s electronic requirements

Prototyping for the Space Shuttle,

Commercial airliners

Bicycles & automobiles

Electronic substrates and Aerospace

Comparable construction unit characteristics are attainable only with the application of

powder metallurgical aluminium alloys or when using heavy iron pistons. The reason for the

application of composite materials is, as already described the improved high temperature

properties. Potential applications are in the area of undercarriages, e.g. transverse control

arms and particle-strengthened brake disks, which can be also applied in the area of rail

mounted vehicles, e.g. for undergrounds and railway (ICE).

1.3 MATERIALS AND STRUCTURE

Fig 1.1 Types of Composite Materials

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Fig 1.2 Structures of composites

The difference between a material and a structure is not clearly defined. Many draw the lines

between what you understand as a homogeneous material when you see it with your bare

eyes, and the inhomogeneous material structure that you clearly see is made up of a fixed

geometry or mixing of materials. For instance an alloy is by this definition a material even

though it consists of two or more components, but a honeycomb core built up of two different

components is a structure. Materials are often classified into the six broad classes that are

shown in figure 1.1; metals, ceramics, glasses, elastomers, polymers and composites. But,

when we also include material structures, the number is bigger, and the classification of the

term ‖materials and structures‖, even though it is not a conventional way of making a

classification, may look like the one purposed in figure 1.2.

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CHAPTER 2

2.LITERATURE REVIEW

In recent scenario, there is an increasing trend towards using composite materials in order to

achieve better performance in engineering materials. Thus, production and application of

metal matrix composites (MMC) have increased in recent years (Kok M, 2005). MMCs are

very important because of their high strength to weight ratio, high Young modulus and wear

resistance properties, when compared to most conventional materials (Degischer HP, 1997).

It also possesses high thermal conductivity and corrosion resistance properties (Hossein

Abdizadeh et al 2011). Therefore, MMC are being used for wide variety of application such

as, connecting rod, automobile drive shafts, cylinder liner, cylinder block, rotors (Rasit Koker

et al 2005), heat sink (Dobrzanski LA et al 2006, Torralba et al, 2003) , crane bearing and

motor blocks (Liu HN et al 1999, Moustafa SF et al 1997).

To fabricate MMC, metallic matrix materials should be embedded with reinforced materials,

which is in the form of continuous fibers, short fibers, chopped fibers, whiskers or

particulates (Yusuf Sahin, 2010). In general, aluminium, copper, nickel, silver, zinc,

magnesium will be used as matrix material and Silicon carbide (Yusuf Sahin, 2010), Alumina

oxide (Sun Zhiqiang et al 2005, Arslan G et al 2001, Turan S et al 2001), boron nitride,

graphite, beryllium oxides, graphite (F. Akhlaghi et al 2009) silicon nitride (Sun Zhiqiang et

al 2005, Fujii Hidetoshi et al 1993, Jenfin Lin et al 2001) will be used as reinforcement

material. Among the different matrix material aluminium and its alloys are promising

materials in automobile and aerospace application owing to their excellent mechanical

properties (F. Akhlaghi et al 2009), and other major advantage is better corrosion resistance

properties, moreover aluminium cheaper than other light matrix materials. However, low

wear resistance of pure aluminium is a serious drawback in using many applications.

Addition of ceramic reinforcement materials in the aluminium matrix material would

improve the strength, hardness, wear resistance and corrosion resistance of the matrix

materials. (Mehdi Rehimian et al 2011, Toress B et al 2002, Sahin Y 1996). In order to

embedded the reinforcement material with matrix material, there are different manufacturing

methods are available.

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The manufacturing methods are classified as: liquid state processing, solid state processing

and deposition techniques. The liquid state processing includes, stir casting, semi solid

processing (Bekir Sadik Unlu 2008), spray casting, infiltration and in situ processing. Solid

state processing includes powder metallurgy (Bekir Sadik Unlu 2008,Liu B et al 1994),

diffusion bonding, pultrusion, and attriter milling. Deposition technique includes chemical

vapour deposition, and physical vapour deposition. In case of liquid state processing

methods, the ceramic material are added in to the melt and stirred, because of stirring ceramic

material with matrix material has some advantage ie better matrix and ceramic material

bonding and easier control of micro structure. (Bekir Sadik Unlu 2008, Bermudez MD et al

2001,Mazeen AA et al 1992,Sahin Y et al 2003, Gahr KH et al 2000).

However liquid state processing methods has two major drawbacks, firstly the ceramic

particles are not wetted with matrix material and secondly, the particles tend to sink or float

depending on their density relative to the liquid metal and so that dispersion of the particles

are not uniform, where as solid state process, especially powder metallurgy process offers

uniform distribution of reinforcement with matrix material.( Bekir Sadik Unlu 2008, Bai M et

al 1995, Nesarikar AR et al 1991, Soliman FA et al 1997).

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2.1 OBJECTIVE OF THE PROJECT

From the literature review it was found there is wide opportunity to reduce the research gap

in the field of metal matrix composites. Therefore, in this work attempt has been to fulfil the

research gaps. The objective of the proposed work is

1. To fabricate aluminium based red mud metal matrix composite with different

composition of red mud using stir casting process.

2. To investigate various mechanical properties of specimen material by conducting

various tests like hardness, density, and wear resistance.

3. To study the effect of red mud reinforcement on mechanical properties.

4. To compare the mechanical properties of various compositions of red mud material.

5. Based on the outcome of mechanical studies, mathematical modeling for wear will be

formulated and suitable decision making model using intelligent techniques like

Artificial Neural Network will be developed.

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CHAPTER 3

3. COMPOSITE MATERIALS

Composite materials, often shortened to composites or called composition materials, are

engineered or naturally occurring materials made from two or more constituent materials with

significantly different physical or chemical properties which remain separate and distinct at

the macroscopic or microscopic scale within the finished structure. Composite material is a

material composed of two or more distinct phases (matrix phase and dispersed phase) and

having bulk properties significantly different from those of any of the constituents.

Composite materials are materials that combine two or more materials (a selected filler or

reinforcing elements and compatible matrix binder) that have quite different properties that

when combined offer properties which are more desirable than the properties of the

individual materials. The different materials work together to give the composite unique

properties, but within the composite you can easily see the different materials; they do not

dissolve or blend into each other.

The key characteristics of composites is the

• Specific strength (the strength to weight ratio)

• Specific stiffness or specific modulus (the stiffness-to-weight ratio)

• Tailored material ( since composites are composed of 2 or more‖phases‖,

They can be formulated to meet the needs of a specific application with considerable ease)

Composites are not a single material but a family of materials whose stiffness, strength,

density, and thermal and electrical properties can be tailored. The matrix, the reinforcement

material, the volume and shape of the reinforcement, the location of the reinforcement, and

the fabrication method etc. can all be varied to achieve required properties

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3.1 CLASSIFICATION OF COMPOSITE MATERIALS

o MATRIX PHASE o DISPERSED PHASE

MATRIX PHASE

The matrix is the monolithic material into which the reinforcement is embedded, and is

completely continuous. This means that there is a path through the matrix to any point in the

material, unlike two materials sandwiched together. In structural applications, the matrix is

usually a lighter metal such as aluminium, magnesium, or titanium, and provides a compliant

support for the reinforcement. In high temperature applications, cobalt and cobalt-nickel alloy

matrices are common.

.

DISPERSED (REINFORCING) PHASE

The second phase (or phases) is embedded in the matrix in a discontinuous form. This

secondary phase is called dispersed phase. Dispersed phase is usually stronger than the

matrix, therefore it is sometimes called reinforcing phase. Many of common materials

(metal alloys, doped Ceramics and Polymers mixed with additives) also have a small amount

of dispersed phases in their structures, however they are not considered as composite

materials since their properties are similar to those of their base constituents (physical

properties of steel are similar to those of pure iron).

3.1.1CLASSIFICATION BASED ON MATRIX PHASE

There are two classification systems of composite materials. One of them is based on the

matrix material (metal, ceramic, and polymer) and the second is based on the material

structure:

POLYMER MATRIX COMPOSITE

Polymer Matrix Composite (PMC) is the material consisting of

a polymer (resin) matrix combined with a fibrous reinforcing dispersed phase.

Polymer Matrix Composites are very popular due to their low cost and simple fabrication

methods. Use of non-reinforced polymers as structure materials is limited by low level of

their mechanical properties: tensile strength of one of the strongest polymers - epoxy

resin is 20000 psi (140 MPa). In addition to relatively low strength, polymer materials

possess low impact resistance.

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CERAMIC MATRIX COMPOSITE

Ceramic matrix composites (CMCs) are a subgroup of composite materials as well as a

subgroup of technical ceramics. They consist of ceramic fibers embedded in a ceramic

matrix, thus forming a ceramic fiber reinforced ceramic (CFRC) material. The matrix and

fibers can consist of any ceramic material, whereby carbon and carbon fibers can also be

considered a ceramic material. Ceramic Matrix Composite (CMC) is a material consisting of

a ceramic matrix combined with a ceramic (oxides, carbides) dispersed phase. Ceramic

Matrix Composites are designed to improve toughness of conventional ceramics, the main

disadvantage of which is brittleness. Ceramic Matrix Composites are reinforced by

either continuous (long) fibers or discontinuous (short) fibers. Generally, CMC names

include a combination of type of fiber/type of matrix. For example, C/C stands for carbon-

fiber-reinforced carbon (carbon/carbon), or C/SiC for carbon-fiber-reinforced silicon carbide.

Sometimes the manufacturing process is included, and a C/SiC composite manufactured with

the liquid polymer infiltration (LPI) process (see below) is abbreviated as LPI-C/SiC.

METAL MATRIX COMPOSITE

Metal Matrix Composites (MMC‘s) are increasingly found in the automotive industry. They

consist of a metal such as aluminium as the matrix, and a reinforcement that could be

continuous fibres such as silicon carbide, graphite or alumina, wires such as tungsten,

beryllium, titanium and molybdenum, and discontinuous materials. Metals containing

ceramic particles, whiskers or (short or long) fibers are also gaining importance. MMC are

said to be materials for the demands of the future. When the demands for high thermal

conductivity, reduced weight, heat dissipation, and high strength are factors for design.

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3.1.2 BASED ON REINFORCEMENT

SILICON CARBIDE

Silicon carbide matrix composites are fabricated by chemical vapor infiltration or liquid

phase Infiltration methods of a matrix material into a preform prepared from silicon carbide

fibers.

Silicon carbide matrix composites are used for manufacturing combustion liners of gas

turbine engines, hot gas re-circulating fans, heat exchangers, rocket propulsion components,

filters for hot liquids, gas-fired burner parts, furnace pipe hangers, immersion burner tubes.

ALUMINA AND ALUMINA-SILICA

Alumina and alumina-silica (mullite) matrix composites are produced by sol-gel

method, direct metal oxidation or chemical bonding. Alumina and alumina-silica (mullite)

matrix composites are used for manufacturing heat exchangers, filters for hot liquids, thermo-

photovoltaic burners, burner stabilizers, combustion liners of gas turbine engines.

CARBON-CARBON

Carbon-Carbon Composites are fabricated by chemical vapour infiltration or infiltration

methods of a matrix material into a preform prepared from carbon fibers. Carbon-Carbon

Composites are used for manufacturing high performance braking systems, refractory

components, hot-pressed dies, heating elements, turbojet engine components.

3.1.2.1 BASED OF REINFORCEMENT GEOMETRY

PARTICULATE REINFORCED MMC (PRM):

Metal matrix composite with a particulate reinforcement occupying a volume fraction greater

than 5% in the material (otherwise, the particulates are generally considered to be inclusions).

DISPERSOID REINFORCED MMC:

Metal matrix composite with a dispersed reinforcement occupying a volume fraction greater

than 5% in the material (otherwise, the material is considered to be a dispersion strengthened

metal - which incidentally may form the matrix of any type of MMC, i.e., a MMC with

dispersion-strengthened matrix).

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CERMETS:

A metal matrix with a three-dimensionally percolating ceramic reinforcement, typically with

far more ceramic than metal (strictly speaking they contain less than 20% metal per volume

and are thus not considered as MMC). According to the percolating structure of both

constituents cermets could thus be considered as both a ceramic and a metal matrix

composite.

Fig 3.1 Classification of Composite materials with metal matrix

Fig 3.2 Types of particles

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Particulates are the most common and cheapest reinforcement materials. These

produce the isotropic property of MMCs, which shows a promising application in structural

and in automobile fields. Reinforcement materials are metallic, non- metallic and ceramic

materials such as;

Red mud,

Silicon carbide (SiC),

Aluminium oxide (Al2O3),

Boron nitride,

Tungsten carbide,

Titanium diboride,

Titanium carbide,

B4C,

Silicon nitrate.

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CHAPTER 4

4. METAL MATRIX COMPOSITE PROCESSING METHODS

The Metal matrix composites are fabricated by various techniques which are generally

classified in to two major methods such as

* Liquid State Fabrication

* Solid state fabrication

Here we have focused on the Liquid state fabrication techniques

4.1 LIQUID STATE FABRICATION TECHNIQUES

The methods of liquid state fabrication of Metal matrix composite

Infiltration

Gas Pressure Infiltration

Squeeze Casting Infiltration

Pressure Die Infiltration

Stir Casting

4.1.1 INFILTRATION

Infiltration is a liquid state method of composite materials fabrication, in which a preformed

dispersed phase (ceramic particles, fibers, woven) is soaked in a molten matrix metal, which

fills the space between the dispersed phase inclusions. The motive force of an infiltration

process may be either capillary force of the dispersed phase (spontaneous infiltration) or an

external pressure (gaseous, mechanical, electromagnetic, centrifugal or ultrasonic) applied to

the liquid matrix phase (forced infiltration).

4.1.2 GAS PRESSURE INFILTRATION

Gas Pressure Infiltration is a forced infiltration method of liquid phase fabrication of Metal

matrix composites, using a pressurized gas for applying pressure on the molten metal and

forcing it to penetrate into a preformed dispersed phase. Gas Pressure Infiltration method

is used for manufacturing large composite parts. The method allows using non-coated fibers

due to short contact time of the fibers with the hot metal. In contrast to the methods using

mechanical force, Gas Pressure Infiltration results in low damage of the fibers.

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4.1.3 SQUEEZE CASTING INFILTRATION

Squeeze Casting Infiltration is a forced infiltration method of liquid phase fabrication of

Metal matrix composites, using a movable mould part (ram) for applying pressure on the

molten metal and forcing it to penetrate into a performed dispersed phase, placed into the

lower fixed mold part.

Squeeze Casting Infiltration method is similar to the Squeeze casting technique used for

metal alloys casting.

Fig 4.1 Squeeze Casting Infiltration

PRESSURE DIE INFILTRATION

Pressure Die Infiltration is a forced infiltration method of liquid phase fabrication Metal

matrix, using a Die casting technology, when a preformed dispersed phase (particles, fibers)

is placed into a die (mould) which is then filled with a molten metal entering the die through

a sprue and penetrating into the preform under the pressure of a movable piston (plunger).

4.1.4 STIR CASTING

Stir Casting is a liquid state method of composite materials fabrication, in which a dispersed

phase (ceramic particles, short fibers) is mixed with a molten metal matrix by means of

mechanical stirring.

Stir Casting is the simplest and the most cost effective method of liquid state fabrication.

25

Stir Casting is the simplest and the most cost effective method of liquid state fabrication.

The liquid composite material is then cast by conventional casting methods and may also be

processed by conventional metal forming technologies.

Stir Casting is characterized by the following features:

Content of dispersed phase is limited (usually not more than 30 vol. %).

Distribution of dispersed phase throughout the matrix is not perfectly homogeneous:

1. There are local clouds (clusters) of the dispersed particles (fibers);

2. There may be gravity segregation of the dispersed phase due to a difference in the densities

of the dispersed and matrix phase.

The technology is relatively simple and low cost.

Fig 4.2 Stir casting setup

4.2 SOLID STATE FABRICATION TECHNIQUES

4.2.1 POWDER METALLURGY:

The majority of the structural components produced by fixed die pressing are iron

based. The powders are elemental, pre-alloyed, or partially alloyed. Elemental powders, such

as iron and copper, are easy to compress to relatively high densities, produce pressed

compacts with adequate strength for handling during sintering, but do not produce very high

strength sintered parts. Pre-alloyed powders are harder, less compressible and hence require

higher pressing loads to produce high density compacts. However, they are capable of

producing high strength sintered materials. Pre-alloying is also used when the production of a

homogeneous material from elemental powders requires very high temperatures and long

sintering times. The best examples are the stainless steels, whose chromium and nickel

contents have to be pre-alloyed to allow economic production by powder metallurgy. As a

general rule both mechanical and physical properties improve with increasing density.

26

Therefore the method selected for the fabrication of a component by powder metallurgy will

depend on the level of performance required from the part. Many components are adequate

when produced at 85-90% of theoretical full density (T.D.) whilst others require full density

for satisfactory performance. Sintering is the process whereby powder compacts are heated so

that adjacent particles fuse together, thus resulting in a solid article with improved

mechanical strength compared to the powder compact. This ―fusing‖ of particles results in an

increase in the density of the part and hence the process is sometimes called densification.

There are some processes such as hot isostatic pressing which combine the compaction and

sintering processes into a single step.

The density of the component can also change during sintering, depending on the

materials and the sintering temperature. These dimensional changes can be controlled by an

understanding and control of the pressing and sintering parameters, and components can be

produced with dimensions that need little or no rectification to meet the dimensional

tolerances. Note that in many cases all of the powder used is present in the finished product,

scrap losses will only occur when secondary machining operations are necessary.

4.2.1 HOT ISOSTATIC PRESSING:

Powders are usually encapsulated in a metallic container but sometimes in glass. The

container is evacuated; the powder out-gassed to avoid contamination of the materials by any

residual gas during the consolidation stage and sealed-off is shown in fig. 4.3. It is then

heated and subjected to isostatic pressure sufficient to plastically deform both the container

and the powder.

The rate of densification of the powder depends upon the yield strength of the powder

at the temperatures and pressures chosen. At moderate temperature the yield strength of the

powder can still be high and require high pressure to produce densification in an economic

time. Typical values might be 1120°C and 100 MPa for ferrous alloys. By pressing at very

much higher temperatures lower pressures are required as the yield strength of the material is

lower. Using a glass enclosure atmospheric pressure (15 psi) is used to consolidate bars and

larger billets.

The technique requires considerable financial investment as the pressure vessel has to

withstand the internal gas pressure and allow the powder to be heated to high temperatures.

27

As with cold isostatic pressing only semi finished products are produced, either for

subsequent working to smaller sizes, or for machining to finished dimensions.

4.2.3 HOT FORGING (POWDER FORGING):

Cold pressed and sintered components have the great advantage of being close to final

shape (near-nett shape), but are not fully dense. Where densification is essential to provide

adequate mechanical properties, the technique of hot forging, or powder forging, can be used.

In powder forging an as-pressed component is usually heated to a forging temperature

significantly below the usual sintering temperature of the material and then forged in a closed

die. This produces a fully dense component with the shape of the forging die and appropriate

mechanical properties.

Powder forged parts generally are not as close to final size or shape as cold pressed

and sintered parts. This result from the allowances made for thermal expansion effects and

the need for draft angles on the forging tools. Further, minimal, machining is required but

when all things are considered this route is often very cost effective.

4.2.4 METAL INJECTION MOULDING (MIM):

Injection moulding is very widely used to produce precisely shaped plastic

components in complex dies. As injection pressures are low it is possible to manufacture

complex components, even some with internal screw threads, by the use of side cores and

split tools.

By mixing fine, typically less than 20 mm diameter, spherical metal powders with

thermoplastic binders, metal filled plastic components can be produced with many of the

features available in injection moulded plastics. After injection moulding, the plastic binder

material is removed to leave a metal skeleton which is then sintered at high temperature.

Dimensional control can be exercised on the as-sintered component as the injected

density is sensibly uniform so shrinkage on sintering is also uniform. Shrinkage can be large,

due to both the fine particle size of the powders and the substantial proportion of polymer

binder used.

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4.2.5 DIFFUSION BONDING

Diffusion Bonding is a solid state fabrication method, in which a matrix in form of

foils and a dispersed phase in form of long fibres are stacked in a particular order and then

pressed at elevated temperature The finished laminate composite material has a multilayer

structure. Diffusion Bonding is used for fabrication of simple shape parts (plates, tubes). In

the Foil diffusion bonding Layers of metal foil are sandwiched with long fibres, and then

pressed through to form a matrix.

4.3 VAPOUR DEPOSITION:

There are two methods of solid state fabrication of Metal matrix composite;

4.3.1 PHYSICAL VAPOUR DEPOSITION:

The fibre is passed through a thick cloud of vaporized metal, coating it. In situ fabrication

technique. Controlled unidirectional solidification of a eutectic alloy can result in a two-phase

microstructure with one of the phases, present in lamellar or fiber form, distributed in the

matrix.

4.3.1 ELECTROPLATING / ELECTROFORMING:

A solution containing metal ions loaded with reinforcing particles is co-deposited forming a

composite material.

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CHAPTER 5

5. PROPERTIES OF MATERIALS

Material property may be a constant or may be a function of one or more independent

variables, such as temperature. Material's properties often vary to some degree according to

the direction in the material in which they are measured; a condition referred to as anisotropy.

Materials properties that relate two different physical phenomena often behave linearly (or

approximately so) in a given operating range, and may then be modeled as a constant for that

range. This linearization can significantly simplify the differential constitutive equations that

the property describes.

5.1 VARIOUS MECHANICAL PROPERTIES

Compressive strength

Density

Ductility

Fatigue limit

Flexural modulus

Flexural strength

Fracture toughness

Hardness

Plasticity (physics)

Poisson's ratio

Shear modulus

Shear strain

Shear strength

Softness

Specific modulus

Specific weight

Tensile strength

Yield strength

Young's modulus

TENSILE STRESSES:

Tension (or tensile) stresses develop when a material is subject to a pulling load; for

example, when using a wire rope to lift a load or when using it as a guy to anchor an antenna.

"Tensile strength" is defined as resistance to longitudinal stress or pulls and can be measured

in pounds per square inch of cross section. Shearing stresses occur within a material when

external forces are applied along parallel lines in opposite directions. Shearing forces can

separate material by sliding part of it in one direction and the rest in the opposite direction.

A material that is stressed repeatedly usually fails at a point considerably below its

maximum strength in tension, compression, or shear. For example, a thin steel rod can be

broken by hand by bending it back and forth several times in the same place; however, if the

same force is applied in a steady motion (not bent back and forth), the rod cannot be broken.

30

The tendency of a material to fail after repeated bending at the same point is known as

fatigue.

HARDNESS

Hardness is the measure of how resistant solid matter is to various kinds of permanent shape

change when a force is applied. Macroscopic hardness is generally characterized by strong

intermolecular bonds, but the behaviour of solid materials under force is complex; therefore

there are different measurements of hardness: scratch hardness, indentation hardness, and

rebound hardness. Hardness is dependent on ductility, elasticity, plasticity, strain, strength,

toughness, viscoelasticity, and viscosity.

IMPACT STRENGTH

The Charpy impact test, also known as the Charpy v-notch test, is a standardized high strain-

rate test which determines the amount of energy absorbed by a material during fracture. This

absorbed energy is a measure of a given material's toughness and acts as a tool to study

temperature-dependent brittle-ductile transition. It is widely applied in industry, since it is

easy to prepare and conduct and results can be obtained quickly and cheaply. But a major

disadvantage is that all results are only comparative.

TOUGHNESS:

Toughness is the property that enables a material to withstand shock and to be

deformed without rupturing. Toughness may be considered as a combination of strength and

plasticity.

ELASTICITY:

When a material has a load applied to it, the load causes the material to deform.

Elasticity is the ability of a material to return to its original shape after the load is removed.

Theoretically, the elastic limit of a material is the limit to which a material can be loaded and

still recover its original shape after the load is removed.

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PLASTICITY:

Plasticity is the ability of a material to deform permanently without breaking or

rupturing. This property is the opposite of strength. By careful alloying of metals, the

combination of plasticity and strength is used to manufacture large structural members. For

example, should a member of a bridge structure become overloaded, plasticity allows the

overloaded member to flow allowing the distribution of the load to other parts of the bridge

structure.

BRITTLENESS:

Brittleness is the opposite of the property of plasticity. A brittle metal is one that

breaks or shatters before it deforms. White cast iron and glass are good examples of brittle

material. Generally, brittle metals are high in compressive strength but low in tensile strength.

As an example, you would not choose cast iron for fabricating support beams in a bridge.

DUCTILITY AND MALLEABILITY:

Ductility is the property that enables a material to stretch, bend, or twist without

cracking or breaking. This property makes it possible for a material to be drawn out into a

thin wire. In comparison, malleability is the property that enables a material to deform by

compressive forces without developing defects. A malleable material is one that can be

stamped, hammered, forged, pressed, or rolled into thin sheets.

5.2 PHYSICAL PROPERTIY

Metals in general have high electrical conductivity which depends on their valency of

ions, thermal conductivity, lustre and density, and the ability to be deformed under stress

without cleaving.

ELECTRICAL CONDUCTIVITY:

Electrical conductivity or specific conductance is the reciprocal quantity, and

measures a material's ability to conduct an electric current.

32

THERMAL CONDUCTIVITY:

Thermal conductivity, k, is the property of a material's ability to conduct heat. It

appears primarily in Fourier's Law for heat conduction.

Heat transfer across materials of high thermal conductivity occurs at a faster rate than

across materials of low thermal conductivity. Correspondingly materials of high thermal

conductivity are widely used in heat sink applications and materials of low thermal

conductivity are used as thermal insulation.

Thermal conductivity of materials is temperature dependent. In general, materials

become more conductive to heat as the average temperature increases. The reciprocal of

thermal conductivity is thermal resistivity.

DENSITY

The density of a material is given by the ratio of mass per unit volume. The density of MMC

varies due to infiltration of Red mud in to the Aluminium alloy. The density of a material can

be found using Archimedes principle which states that the weight of the displaced fluid is

directly proportional to the volume of the displaced fluid (if the surrounding fluid is of

uniform density). In simple terms, the principle states that the buoyant force on an object is

going to be equal to the weight of the fluid displaced by the object, or the density of the fluid

multiplied by the submerged volume times the gravitational constant, g.

Thus, among completely submerged objects with equal masses, objects with greater volume

have greater buoyancy.

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Fig 5.1 Archimedes principle

5.3 EFFECT OF VARIOUS PARAMETERS

EFFECT OF REINFORCEMENT VOLUME FRACTION

It was predicted that there exists a critical reinforcement volume fraction above which the

composite strength can be improved relative to that of the unreinforced material and below

which the composite strength decreases, owing to the ineffective load transfer from matrix to

reinforcement in MMCs. For low volume fraction of reinforcement, the composite strength

was observed to be governed by the residual matrix strength, which decreases with increasing

reinforcing volume fraction.

EFFECT OF PARTICLE SIZE

The deformation and fracture behaviour of the composite revealed the importance of particle

size. A reduction in particle size is observed to increase the proportional limit, yield stress

and the ultimate tensile stress. It is well established that large particles are detrimental to

fracture toughness due to their tendency towards fracture. It would be highly desirable to

have a composite system where the reinforcing particles are relatively fine so as to get the

stiffness benefits of a composite without significantly lowering fracture toughness.

EFFECT OF REINFORCEMENT DISTRIBUTION

Apart from the reinforcement level, the reinforcement distribution also influences the

ductility and fracture toughness of the MMC and hence indirectly the strength. A uniform

reinforcement distribution is essential for effective utilization of the load carrying capacity of

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the reinforcement. Non-uniform distributions of reinforcement in the early stages of

processing was observed to persist to the final product in the forms of streaks or clusters of

uninfiltrated reinforcement with their attendant porosity, all of which lowered ductility,

strength and toughness of the material.

FRACTURE

The fracture behaviour of MMCs has been identified not only for extending their applications

but also for improving mechanical properties, especially strength and ductility. Better

understandings of the underlying mechanisms affecting composite properties are essential if

the properties of the composite material are to be improved. Tensile fracture of conventional

alloys is considered in terms of the micro void coalescence model (MVC). Void nucleation in

unreinforced alloys occurs at constituent particles, either through particle failure, through

interface decohesion. Decohesion is most common, but particle cracking occurs with

elongated particles. In composites, there are three possible mechanisms for void nucleation

particle cracking, interface decohesion, and matrix void nucleation is the same mechanism as

occurs in the unreinforced alloys

MICROSTRUCTURE

The most important aspects of the microstructure is the distribution of the reinforcing

particles, and this depends on the processing and fabrication routes involved. The oxides of

reinforcing particles used in the composites have a varying density. Density of the particles is

one of the important factors determining the distribution of the particles in molten metal.

Particles having higher density than molten metal can settle at the bottom of the bath slowly

and particles of lower density can segregate at the top. During subsequent pouring of the

composite melt, the particle content may vary from one casting to another or even it can vary

in the same casting from one region to another. Therefore uniform distribution of the particles

in the melt is a necessary condition for uniform distribution of particles in the castings. The

properties of composites are finally dependent on the distribution of the particles. Hence the

study of the distribution of the particles in the composite is of great significance. Several

investigators have examined the fracture samples of different metal matrix composites; it was

observed that the fracture occurred mainly through the matrix in a ductile manner.

35

5.4 WEAR CHARECTERISTICS

Wear can also be defined as a process where interaction between two surfaces or bounding

faces of solids within the working environment results in dimensional loss of one solid, with

or without any actual decoupling and loss of material. Aspects of the working environment

which affect wear include loads and features such as unidirectional sliding, reciprocating,

rolling, and impact loads, speed, temperature..Wear is related to interactions between surfaces

and more specifically the removal and deformation of material on a surface as a result of

mechanical action of the opposite surface. The need for relative motion between two surfaces

and initial mechanical contact between asperities is an important distinction between

mechanical wear compared to other processes with similar outcomes.

5.4.1 TYPES OF WEAR

The study of the processes of wear is part of the discipline of tribology. The complex nature

of wear has delayed its investigations and resulted in isolated studies towards specific wear

mechanisms or processes.[6]

Some commonly referred to wear mechanisms (or processes)

include:

1. Adhesive Wear

2. Abrasive Wear

3. Surface Fatigue

4. Fretting Wear

5. Erosive Wear

A number of different wear phenomena are also commonly encountered and presented in the

literature. Impact-, cavitations-, diffusive- and corrosive- wear are all such examples.

These wear mechanisms, however, do not necessarily act independently and wear

mechanisms are not mutually exclusive. "Industrial Wear" are commonly described as

incidence of multiple wear mechanisms occurring in unison. Another way to describe

"Industrial Wear" is to define clear distinctions in how different friction mechanisms operate,

for example distinguish between mechanisms with high or low energy density. Wear

mechanisms and/or sub-mechanisms frequently overlap and occur in a synergistic manner,

producing a greater rate of wear than the sum of the individual wear mechanisms.

36

ADHESIVE WEAR

Adhesive wear can be found between surfaces during frictional contact and generally refers

to unwanted displacement and attachment of wear debris and material compounds from one

surface to another. Two separate mechanisms operate between the surfaces.

1. Adhesive wear are caused by relative motion, "direct contact" and plastic deformation

which create wear debris and material transfer from one surface to another.

2. Cohesive adhesive forces, holds two surfaces together even though they are separated

by a measurable distance, with or without any actual transfer of material.

The above description and distinction between "adhesive wear" and its counterpart "cohesive

adhesive forces" are quite common. Usually cohesive surface forces and adhesive energy

potentials between surfaces are examined as a special field in physic departments. The

adhesive wear and material transfer due to direct contact and plastic deformation are

examined in engineering science and in industrial research.

Two aligned surfaces may always cause material transfer and due to overlaps and symbiotic

relations between relative motional ―wear‖ and ―chemical‖ cohesive attraction.

Generally, adhesive wear occurs when two bodies slide over or are pressed into each other,

which promote material transfer. This can be described as plastic deformation of very small

fragments within the surface layers. The asperities or microscopic high points or surface

roughness found on each surface, define the severity on how fragments of oxides are pulled

off and adds to the other surface, partly due to strong adhesive forces between atoms but also

due to accumulation of energy in the plastic zone between the asperities during relative

motion.

The outcome can be a growing roughening and creation of protrusions (i.e., lumps) above the

original surface, in industrial manufacturing referred to as galling , which eventually breaches

the oxidized surface layer and connects to the underlying bulk material which enhance the

possibility for a stronger adhesion and plastic flow around the lump. The geometry and the

nominal sliding velocity of the lump defines how the flowing material will be transported and

accelerated around the lump which is critical to define contact pressure and developed

temperature during sliding. The mathematical function for acceleration of flowing material is

thereby defined by the lumps surface contour.

37

It‘s clear, given these prerequisites, that contact pressure and developed temperature is highly

dependent on the lumps geometry. Flow of material exhibits an increase in energy density,

because initial phase transformation and displacement of material demand acceleration of

material and high pressure. Low pressure is not compatible with plastic flow; only after

deceleration may the flowing material be exposed to low pressure and quickly cooled. In

other words, you can‘t deform a solid material using direct contact without applying a high

pressure and somewhere along the process must acceleration and deceleration take place, i.e.,

high pressure must be applied on all sides of the deformed material. Flowing material will

immediately exhibit energy loss and reduced ability to flow due to phase transformation, if

ejected from high pressure into low pressure. This ability withholds the high pressure and

energy density in the contact zone and decreases the amount of energy or friction force

needed for further advancement when the sliding continues and partly explain the difference

between the static and sliding coefficient of friction (μ) if the main fracture mechanisms are

equal to the previous. Adhesive wear is a common fault factor in industrial applications such

as sheet metal forming (SMF) and commonly encountered in conjunction with lubricant

failures and are often referred to as welding wear or galling due to the exhibited surface

characteristics, phase transition and plastic flow followed by cooling. The type of mechanism

and the amplitude of surface attraction vary between different materials but are amplified by

an increase in the density of ―surface energy‖. Most solids will adhere on contact to some

extent. However, oxidation films, lubricants and contaminants naturally occurring generally

suppress adhesion and spontaneous exothermic chemical reactions between surfaces

generally produce a substance with low energy status in the absorbed species.

ABRASIVE WEAR

Abrasive wear occurs when a hard rough surface slides across a softer surface. ASTM

(American Society for Testing and Materials) defines it as the loss of material due to hard

particles or hard protuberances that are forced against and move along a solid surface.

Abrasive wear is commonly classified according to the type of contact and the contact

environment. The type of contact determines the mode of abrasive wear. The two modes of

abrasive wear are known as two-body and three-body abrasive wear. Two-body wear occurs

when the grits or hard particles remove material from the opposite surface. The common

analogy is that of material being removed or displaced by a cutting or plowing operation.

38

Three-body wear occurs when the particles are not constrained, and are free to roll and slide

down a surface. The contact environment determines whether the wear is classified as open

or closed. An open contact environment occurs when the surfaces are sufficiently displaced to

be independent of one another

There are a number of factors which influence abrasive wear and hence the manner of

material removal. Several different mechanisms have been proposed to describe the manner

in which the material is removed. Three commonly identified mechanisms of abrasive wear

are:

1. Plowing

2. Cutting

3. Fragmentation

Plowing occurs when material is displaced to the side, away from the wear particles, resulting

in the formation of grooves that do not involve direct material removal. The displaced

material forms ridges adjacent to grooves, which may be removed by subsequent passage of

abrasive particles. Cutting occurs when material is separated from the surface in the form of

primary debris, or microchips, with little or no material displaced to the sides of the grooves.

This mechanism closely resembles conventional machining. Fragmentation occurs when

material is separated from a surface by a cutting process and the indenting abrasive causes

localized fracture of the wear material. These cracks then freely propagate locally around the

wear groove, resulting in additional material removal by spalling.

SURFACE FATIGUE

Surface fatigue is a process by which the surface of a material is weakened by cyclic loading,

which is one type of general material fatigue. Fatigue wear is produced when the wear

particles are detached by cyclic crack growth of micro cracks on the surface. These micro

cracks are either superficial cracks or subsurface cracks.

FRETTING WEAR

Fretting wear is the repeated cyclical rubbing between two surfaces, which is known as

fretting, over a period of time which will remove material from one or both surfaces in

contact. It occurs typically in bearings, although most bearings have their surfaces hardened

to resist the problem. Another problem occurs when cracks in either surface are created,

known as fretting fatigue. It is the more serious of the two phenomena because it can lead to

39

catastrophic failure of the bearing. An associated problem occurs when the small particles

removed by wear are oxidised in air. The oxides are usually harder than the underlying metal,

so wear accelerates as the harder particles abrade the metal surfaces further. Fretting

corrosion acts in the same way, especially when water is present. Unprotected bearings on

large structures like bridges can suffer serious degradation in behaviour, especially when salt

is used during winter to deice the highways carried by the bridges.

EROSIVE WEAR

Erosive wear can be described as an extremely short sliding motion and is executed within a

short time interval. Erosive wear is caused by the impact of particles of solid or liquid against

the surface of an object. The impacting particles gradually remove material from the surface

through repeated deformations and cutting actions. It is a widely encountered mechanism in

industry. A common example is the erosive wear associated with the movement of slurries

through piping and pumping equipment. The rate of erosive wear is dependent upon a

number of factors. The material characteristics of the particles, such as their shape, hardness,

and impact velocity and impingement angle are primary factors along with the properties of

the surface being eroded. The impingement angle is one of the most important factors and is

widely recognized in literature. For ductile materials the maximum wear rate is found when

the impingement angle is approximately 30°, whilst for non ductile materials the maximum

wear rate occurs when the impingement angle is normal to the surface.

40

5.4.2 SYMPTOMS OF WEAR A summary of the appearance and symptoms of different wear mechanism is indicated in

Table 5.1 and the same is a systematic approach to diagnose the wear mechanisms.

Table 5.1 Symptoms of Wear

41

CHAPTER 6

6. ARTIFICIAL NEURAL NETWORK

An artificial neural network (ANN), usually called neural network (NN), is a mathematical

model or computational model that is inspired by the structure and/or functional aspects of

biological neural networks. A neural network consists of an interconnected group of artificial

neurons, and it processes information using a connectionist approach to computation. In most

cases an ANN is an adaptive system that changes its structure based on external or internal

information that flows through the network during the learning phase. Modern neural

networks are non-linear statistical data modeling tools. They are usually used to model

complex relationships between inputs and outputs or to find patterns in data.

6.1. BACKGROUND

The original inspiration for the term Artificial Neural Network came from examination of

central nervous systems and their neurons, axons, dendrites, and synapses, which constitute

the processing elements of biological neural networks investigated by neuroscience. In an

artificial neural network, simple artificial nodes, variously called "neurons", "neurodes",

"processing elements" (PEs) or "units", are connected together to form a network of nodes

mimicking the biological neural networks — hence the term "artificial neural network‖.

Because neuroscience is still full of unanswered questions, and since there are many levels of

abstraction and therefore many ways to take inspiration from the brain, there is no single

formal definition of what an artificial neural network is. Generally, it involves a network of

simple processing elements that exhibit complex global behaviour determined by connections

between processing elements and element parameters. While an artificial neural network does

not have to be adaptive per se, its practical use comes with algorithms designed to alter the

strength (weights) of the connections in the network to produce a desired signal flow. These

networks are also similar to the biological neural networks in the sense that functions are

performed collectively and in parallel by the units, rather than there being a clear delineation

of subtasks to which various units are assigned. Currently, the term Artificial Neural Network

(ANN) tends to refer mostly to neural network models employed in statistics, cognitive

psychology and artificial intelligence.

42

Neural network models designed with emulation of the central nervous system (CNS) in

mind are a subject of theoretical neuroscience and computational neuroscience.

In modern software implementations of artificial neural networks, the approach inspired by

biology has been largely abandoned for a more practical approach based on statistics and

signal processing. In some of these systems, neural networks or parts of neural networks

(such as artificial neurons) are used as components in larger systems that combine both

adaptive and non-adaptive elements. While the more general approach of such adaptive

systems is more suitable for real-world problem solving, it has far less to do with the

traditional artificial intelligence connectionist models. What they do have in common,

however, is the principle of non-linear, distributed, parallel and local processing and

adaptation.

6.2 MATHEMATICAL MODEL

Neural network models in artificial intelligence are usually referred to as artificial neural

networks (ANNs); these are essentially simple mathematical models defining a function

f:X→Y or a distribution over X or both X and Y, but sometimes models are also intimately

associated with a particular learning algorithm or learning rule. A common use of the phrase

ANN model really means the definition of a class of such functions.

When creating a functional model of the biological neuron, there are three basic components

of importance. First, the synapses of the neuron are modelled as weights. The strength of the

connection between an input and a neuron is noted by the value of the weight. Negative

weight values reflect inhibitory connections, while positive values designate excitatory

connections. The next two components model the actual activity within the neuron cell. An

adder sums up all the inputs modified by their respective weights. This activity is referred to

as linear combination. Finally, an activation function controls the amplitude of the output of

the neuron. An acceptable range of output is usually between 0 and 1, or -1 and 1.

Mathematically, this process is described in the figure 6.1

43

Fig 6.1 Mathematical process of artificial neural network

From this model the interval activity of the neuron can be shown to be:

The output of the neuron, yk, would therefore be the outcome of some activation function on

the value of vk.

44

6.3 ACTIVATION FUNCTIONS

As mentioned previously, the activation function acts as a squashing function, such that the

output of a neuron in a neural network is between certain values (usually 0 and 1, or -1 and

1). In general, there are three types of activation functions, denoted by Φ (.) . First, there is

the Threshold Function which takes on a value of 0 if the summed input is less than a certain

threshold value (v), and the value 1 if the summed input is greater than or equal to the

threshold value.

Secondly, there is the Piecewise-Linear function. This function again can take on the values

of 0 or 1, but can also take on values between that depending on the amplification factor in a

certain region of linear operation.

Thirdly, there is the sigmoid function. This function can range between 0 and 1, but it is also

sometimes useful to use the -1 to 1 range. An example of the sigmoid function is the

hyperbolic tangent function.

The artificial neural networks which we describe are all variations on the parallel distributed

processing (PDP) idea. The architecture of each neural network is based on very similar

building blocks which perform the processing and is shown in figure 6.2

45

Fig 6.2 Style of Neural Computation

6.4 NETWORK FUNCTION

The word network in the term 'artificial neural network' refers to the inter–connections

between the neurons in the different layers of each system. The most basic system has three

layers. The first layer has input neurons, which send data via synapses to the second layer of

neurons, and then via more synapses to the third layer of output neurons. More complex

systems will have more layers of neurons with some having increased layers of input neurons

and output neurons. The synapses store parameters called "weights" that manipulate the data

in the calculations. The layers network through the mathematics of the system algorithms.

The network function f(x) is defined as a composition of other functions gi(x), which can

further be defined as a composition of other functions. This can be conveniently represented

as a network structure, with arrows depicting the dependencies between variables. A widely

used type of composition is the nonlinear weighted sum,f(x)=K(∑iwigi(x)), where (commonly

referred to as the activation function is some predefined function), such as the hyperbolic

tangent. It will be convenient for the following to refer to a collection of functions as simply a

vector. g=(g1,g2,....,gn)

46

6.5 LEARNING

What has attracted the most interest in neural networks is the possibility of learning. Given a

specific task to solve, and a class of functions, learning means using a set of observations to

find f*€f which solves the task in some optimal sense. This entails defining a cost function C:

F→R such that, for the optimal solution f*, C (f*) ≤C (f) ¥f € F, (i.e., no solution has a cost

less than the cost of the optimal solution).The cost function is an important concept in

learning, as it is a measure of how far away a particular solution is from an optimal solution

to the problem to be solved. Learning algorithms search through the solution space to find a

function that has the smallest possible cost.

There are three major learning paradigms, each corresponding to a particular abstract learning

task. These are supervised learning, unsupervised learning and reinforcement learning.

6.6 SUPERVISED LEARNING

In supervised learning, we are given a set of example pairs(x,y),x€X,y€Y and the aim is to

find a function f: x→ y in the allowed class of functions that matches the examples. In other

words, we wish to infer the mapping implied by the data; the cost function is related to the

mismatch between our mapping and the data and it implicitly contains prior knowledge about

the problem domain. A commonly used cost is the mean-squared error, which tries to

minimize the average squared error between the network's output, f(x), and the target value y

over all the example pairs. When one tries to minimize this cost using gradient descent for the

class of neural networks called multilayer perceptrons, one obtains the common and well-

known back propagation algorithm for training neural networks. Tasks that fall within the

paradigm of supervised learning are pattern recognition (also known as classification) and

regression (also known as function approximation). The supervised learning paradigm is also

applicable to sequential data (e.g., for speech and gesture recognition). This can be thought of

as learning with a "teacher," in the form of a function that provides continuous feedback on

the quality of solutions obtained thus far. Basically supervised learning is classified in two

types. These are error connection gradient descent and stochastic. Error are also classified

into least mean square and back propagation.

47

6.7 UNSUPERVISED LEARNING

In unsupervised learning, some data x is given and the cost function to be minimized, that can

be any function of the data x and the network's output, f .The cost function is dependent on

the task (what we are trying to model) and our a priori assumptions (the implicit properties of

our model, its parameters and the observed variables).As a trivial example, consider the

model(x)=a, where a is a constant and the costC=E[(x-f(x))2]. Minimizing this cost will give

us a value of a that is equal to the mean of the data. The cost function can be much more

complicated. Its form depends on the application: for example, in compression it could be

related to the mutual information between x and y, whereas in statistical modeling, it could be

related to the posterior probability of the model given the data. (Note that in both of those

examples those quantities would be maximized rather than minimized).Tasks that fall within

the paradigm of unsupervised learning are in general estimation problems; the applications

include clustering, the estimation of statistical distributions, compression and filtering.

6.8 APPLICATIONS

The utility of artificial neural network models lies in the fact that they can be used to infer a

function from observations. This is particularly useful in applications where the complexity

of the data or task makes the design of such a function by hand impractical. The tasks

artificial neural networks are applied to tend to fall within the following broad categories:

Function, or analysis, including time series prediction, fitness approximation and modeling.

Classification, including pattern and sequence recognition, novelty detection and sequential

decision making. Application areas include system identification and control (vehicle control,

process control), quantum chemistry, game-playing and decision making (backgammon,

chess, racing), pattern recognition (radar systems, face identification, object recognition and

more), sequence recognition (gesture, speech, handwritten text recognition), medical

diagnosis, financial applications (automated trading systems), data mining (or knowledge

discovery in databases, "KDD"), visualization and e-mail spam filtering.

48

6.9 TYPES OF ARTIFICIAL NEURAL NETWORKS

An artificial neural network is a computational simulation of a biological neural network.

These models mimic the real life behaviour of neurons and the electrical messages they

produce between input, processing by the brain and the final output from the brain. The

systems can be hardware and software based specifically built systems or purely software

based and run in computer models.

o Feed forward neural network

o Radial basis function (RBF) network

o Kohonen self-organizing network

o Learning Vector Quantization

o Recurrent neural network

49

CHAPTER 7

7. LIST OF EQUIPMENTS USED

7.1 STIR CASTING SETUP

A Self fabricated mechanical stirrer was used to perform stir casting. The equipment was

fabricated by keeping the major factors as variable speed, temperature resistance, load

resistance. Portability and cost.

Fig 7.1 Stirrer Setup

MAJOR COMPONENTS

DC Motor

Speed controller (VARIAC)

Stirrer blade

50

SPECIFICATION

DC Motor

Make : Crompton Greaves Commercial Manufacturer

Model : JLG52586

Speed : 1400 rpm

Speed Controller – VARIAC

Type : 4AMP- 1PH

Maximum Load : 4 AMP

Maximum kVA : 1.08

7.2 HARDNESS TESTING MACHINE

The hardness of the casted specimen was tested using Brinell Hardness Tester. The Brinell

hardness is found by identifying the amount of indentation of the indenter ball in the material

when a constant amount of load is applied. The result is given in HB or BHN unit.

Fig 7.2 Brinell Hardness testing machine

51

SPECIFICATIONS

Make : SE Udyog Private Ltd.,

Model : B/3000/8

Maximum Load : 3000 kgf

7.3 CENTER LATHE

The sample specimens for wear test were machined to the required standard dimensions and

surface finish was machined using a manual center lathe.

Fig 7.4 Center lathe

SPECIFICATIONS

Make : Sona Industries

Model : PL4 – Lathe

Bed length : 41

2 ‖

52

7.4 PIN ON DISC TRIBOMETER

The High Temperature Pin on Disc Tribometer designed and developed

by magnum engineers is primarily intended for determining the Tribological characteristics

of wide range of materials under conditions of various normal loads & temperatures. A

stationary pin mounted on a pin holder is brought into contact against a rotating disc at a

specified speed as the pin is sliding, resulting frictional force acting between the pin and disc

are measured by arresting the deflecting pin holder against a load cell. Both normal load and

speed can be set as desired.

Fig 7.5 Pin on Disc Tribometer

SPECIFIACTION

Make : Magnum engineers

Normal load range : up to 200N

Frictional force range : up to 200N with a resolution of 1N with tare facility

Wear measurement range : 0-4mm with tare facility

Pin length : 25-30mm

Wear Disc material : EN32 Steel

53

7.5 SCANNING ELECTRON MICROSCOPE

SPECIFICATION

Resolution 3.0nm

Magnification X5 to 300,000

Display 20 inch, high resolution FPD

Filament Pre-centered W hairpin filament

Accelerating voltage 0.5 to 30 kv

54

CHAPTER 8

EXPERIMENTAL METHODOLOGY

The processing of Aluminium Red mud metal matrix composite involves various step by step

processes. Each and every step was planned in the aspect of safety, accuracy and cost. The

steps to be carried out are shown in the flow chart below.

Fig 8.1 Flow chart of Experimental Procedure

EXPERIMENTAL PROCEDURE

COKE FEEDING

MELTING OF ALUMINIUM

PRE HEATING OF RED MUD

SOLIDIFICATION IN AIR PROCESS

DIMENSIONING THE SPECIMEN

•MATRIX PHASE

•REINFOCRCEMENT PHASE

MATERIAL SELECTION

•WEIGHING OF MATERIALS

•SURFACE CLEANING

RAW MATERIAL PRE

PROCESSING•COKE

FEEDING

•SPEED SETTING

•DIE PREPARATION

FURNACE AND

STIRRER INITIATION

•MELTING OF AL

•ADDING DEGASSIFIER

•SLAG REMOVAL

•STIR CASTING

•MOULDING

FABRICATION

•SIZING FOR HARDNESS,IMPACT, TENSILE

SIZING OF SPECIMENS

• Wear charecteristics of Al RM Composite is optimized using Artficial Neural Network tool in MATLab

OPTIMIZING UNSING ANN

55

8.1. MATERIAL SELECTION

LM 25 finds its application in many areas like automobile, aerospace, food and beverage

machine making industries, because of its light weight, and good mechanical properties.

Though it has many advantages it is also having a major drawback that it has low wear

resistance property. To overcome this problem, material like Alumina, SiC, and Tio2 can be

added to increase the resistance property.

The following are the chemical, mechanical and physical properties of Al LM 25

Table 8.1 CHEMICAL COMPOSITION OF Al LM25

Al Si Fe Mg Mn Cu Ti Ni Zn Pb Sn

98.45 0.7 0.5 0.40 0.3 0.2 0.2 0.1 0.1 0.1 0.05

Table 8.2 MECHANICAL PROPERTIES OF ALUMINIUM LM25

Density 2.7 g/cc

0.2% Proof Stress (N/mm2) 80-100

Tensile stress (N/mm2) 130-150

Elongation (0%) 2

Brinell Hardness Number 55-65

Endurance Limit (5 X 108 Cycles +

N/mm2)

70-100

Modulus of elasticity ( X 103 N/mm2) 71

8.2 DISPERSION PHASE – Red Mud (RM)

Reinforcement increases the strength, stiffness and the temperature resistance capacity

and lowers the density of MMC. In order to achieve these properties the selection depends on

the type of reinforcement, its method of production and chemical compatibility with the

matrix. MMC reinforcements can be metallic (such as tungsten and cobalt), non-metallic

(most often carbon, graphite, or boron), or ceramic (for example, silicon carbide

(SiC),aluminium oxide (Al2O3), boron nitride, tungsten carbide, titanium diboride, titanium

56

carbide). Here selected reinforcement material is Red Mud which posses very heavy/ dense

having low porosity.

It is beyond doubt that activity of primary industries often yields substantial amounts

of by-products. The disposal in the original industrial site is favoured by economic reasons

though traditional storage in nearby dumps can be impractical owing to the considerable

masses involved and environmental restrictions. The local exploitation of these by-products is

therefore a growing technological aspect of basic industries and one tenable option is their re-

use as starting materials for other productions.

This huge amount of industrial by-products / wastes which is becoming a client for

increasing environmental pollution & generation of a huge amount of unutilized resources.

An emblematic case is the ‗red mud‘ discharged by industry producing alumina from bauxite:

alkaline digestion of 2.5 t of bauxite affords alumina and ≈1.5 t of red mud.

The chosen Red Mud was in the size of 150 microns, and was bought from Madras

Aluminium Company Ltd., (MALCO)

The red mud finds good properties to be used as the reinforcement material. Some of the

advantages are

Mechanical compatibility (a thermal expansion coefficient which is low but

adapted to the matrix),

Chemical compatibility,

Thermal stability,

High Young‘s modulus,

High compression and tensile strength,

Good process ability, economic efficiency.

57

CHEMICAL COMPOSITION OF RED MUD

The X-Ray diffraction image of the selected Red Mud is studied and the composition of the

RM were listed out

Fig 8.2 XRD Image of Red mud

Table 8.3: Chemical Composition of Red Mud

Constituents % Weight Constituents % Weight

Al2O3 15.0 Fe2O3 54.8

TiO2 3.7 SiO2 8.44

Na2O 4.8 CaO 2.5

P2O5 0.67 V2O5 0.38

Ga2O3 0.096 Mn 1.1

Zn 0.018 Mg 0.056

Organic C 0.088 L.O.I Balance

58

CHAPTER 9

8. RAW MATERIAL PRE PROCESSING

The fabrication of Al RM metal matrix composite requires certain pre processing in order to

make the process more effective and legible. The processes involved are explained briefly.

9.1 PROCESSING OF MATRIX AND REINFORCEMENT MATERIAL

The aluminum pieces were sized to the requirement i.e. to full fill the weight combination

criteria. After sizing and weighing the raw material it is need to be cleaned for impurities.

Aluminium pieces were washed in the bath of Sodium Hydroxide solution (NaOH) for 10

minutes. The quantity of the bath was 20ml in a glass beaker.

The Red mud was crushed in Ball mill for about two hours in order to get the even sizing of

the material. Then the milled red mud was sieved using three different sieves such as 150

microns, 90 microns and 75 microns. The sieved red mud were taken and the RM with 150

microns were taken for further processing

9.2 COMBINATION OF RAW MATERIALS

The fabrication of Al Red Mud composite was planned to done in different compositions

such as 0%, 5%, 10%, 15%, 20%, 25%, 30% of Red mud and remaining parts of Aluminium

respectively. Initially two combinations were fabricated for pre studies. The combinations

were tabulated in Table

59

Table 9.1 Combination of Raw materials

S

No.

Combination In Terms of Percentage Combination In terms of Weight (gm)

Al RED MUD Al RED MUD

1 100 0 1000 0

2 95 5 950 50

3 90 10 900 100

4 85 15 850 150

5 80 20 800 200

9.3 INITIATION OF FURNACE AND STIRRER

The furnace needs to initiate before the beginning of the melting process. To do so, the

furnace was fed with coke in different layers and then it is fired using char coal. The furnace

needs to attain certain temperature of range 800 to 1000 degree Celsius in order to melt the

aluminum. For stir casting process, the stirrer should be set to a speed of 600 rpm. Then the

to and fro motion of the stirrer is checked and oiled for free movement.

Fig 9.1 Stir casting setup

60

CHAPTER 10

10. FABRICATION OF METAL MATRIX COMPOSITE

The method chosen for fabricating Al / RM Metal Matrix Composite (MMC) is Stir casting.

This is because the processing expenses are low and also a better method to achieve

dispersion in a low time and cost. Since the DC motor is used to stir there is no problem of

clustering and uneven dispersion. The process of fabrication also includes die preparation.

Here for different studies, three different moulds were prepared on Green sand mould using

specified patterns. The different patterns used were a cylindrical rod of diameter 30mm and

length of 300mm, a square of size 10X10 depth of 50mm, and a rectangle of size 10X50 and

depth of 10mm

10.1 PREPARATION OF MOULD

The part to be made and its pattern must be designed to accommodate each stage of the

process, as it must be possible to remove the pattern without disturbing the molding sand and

to have proper locations to receive and position the cores. A slight taper, known as draft,

must be used on surfaces perpendicular to the parting line, in order to be able to remove the

pattern from the mold. This requirement also applies to cores, as they must be removed from

the core box in which they are formed. The sprue and risers must be arranged to allow a

proper flow of metal and gasses within the mold in order to avoid an incomplete casting.

Should a piece of core or mold become dislodged it may be embedded in the final casting,

forming a sand pit, which may render the casting unusable. Gas pockets can cause internal

voids. These may be immediately visible or may only be revealed after extensive machining

has been performed. For critical applications, or where the cost of wasted effort is a factor,

non-destructive testing methods may be applied before further work is performed. The green

sand mould was selected as die because it is the simple and cheapest way to get castings in

different dimensions. The green sand was made wet to the required consistency by adding

water to it in a slower manner. Then the pre shaped wooden patterns of three different

dimensions were made. They were a cylindrical rod of diameter 35mm and another rod of

diameter 15mm and a rectangular pattern of size 100x100x50. The green sand is rammed

well and vent holes were made at required places

61

Fig 10.1 Green sand mould

10.2 MELTING AND CASTING OF TEST SPECIMEN

The weighted quantities of aluminium were melted to desired superheating temperature of

800 degree Celsius in graphite crucible. The coke fed furnace was used for melting. After

melting was over, the required quantity of red mud particulates, preheated to around 400

degree Celsius were then added to the molten metal and stirred continuously by using

mechanical stirrer. The stirring time was maintained between 60-80 seconds at an impeller

speed of 550 rpm. After the aluminium is melted, Hexa chloro ethane was added as

degasifier. The slag formed was removed periodically to avoid impurities in the casting.

During stirring to enhance the wet ability small quantities of Magnesium was added to the

melt.. The melt with the reinforced particulates were then poured to a prepared moulds. After

pouring is over the melt was allowed to cool and solidify in the mould. The casted specimens

are displayed in the Fig 7.1

Fig 10.2 Fabricated Specimens

62

10.3 DISPERSSION PROCESSING

In dispersion processes, schematically represented in Figure 8.1, the reinforcement is

incorporated in loose form into the metal matrix. Because most metal reinforcement systems

exhibit poor wetting, mechanical force is required to combine the phases, generally through

stirring. This method is currently the most inexpensive manner in which to produce MMCs,

and lends itself to production of large quantities of material, which can be further processed

via casting or extrusion. The simplest dispersion process in current use is the Vortex method,

which consists of vigorous stirring of the liquid metal and the addition of particles in the

vortex. Stirring with a specially designed impeller has the advantage of limiting the

incorporation of impurities, oxides, or gases reduced vortexing. Ingots of such composites are

now commercially produced in large quantities. Other methods being investigated include the

bottom-mixing process, where a rotating blade is progressively lowered into an evacuated

bed of particles covered with molten aluminium, and the injection of particles below the

surface of the melt using a carrier gas.

Compared with the unreinforced metals and alloys, the particle reinforced metal matrix

composites (MMC) exhibit markedly higher stiffness and strength. So the composites are

attracting more attention of automotive, aircraft and aerospace constructions. The production

techniques have been well advanced in recent years, such as powder metallurgy, extrusion

process and liquid infiltration. However in practice, it is often difficult to obtain a

homogeneous distribution of reinforced particles. Further, it has been found that the

mechanical properties of MMC are greatly influenced by the spatial distribution of the

particles. Existing experimental and theoretical evidences suggest that the homogeneity of

particle spatial arrangement plays a key role in controlling the yield strength, ductility,

fatigue and fracture behaviour of MMC]. Although these behaviours are still quite poorly

understood, there is general agreement that the microstructures with particle clustering tend

to result in poorer mechanical properties. Therefore further understanding of the relationship

between particle distribution and deformation mechanisms in MMC is of major importance

for their engineering applications. At present the numerical analysis has been employed by a

number of researchers to predict the effects of particles on the MMC. By and large, these

analyses approached the problem by considering the unit cell model, where one particle was

embedded in matrix. In addition, the shape of the particle was assumed to be cylindrical,

spherical, rectangular or cubical]. The simplification aims at computations but fails capture

the morphology such as particle size, shape and distribution. As a result, it fails to predict the

63

overall mechanical properties of MMC. Also, when more than one particle is considered, the

particles are generally assumed to be the uniform random spatial arrangement and identical

shape. In reality, the particle microstructure is quite complex.

TESTING OF SPECIMEN

10.4 HARDNESS TEST

Hardness is the property of a material to resist permanent indentation. Because there are

several methods of measuring hardness, the hardness of a material is always specified in

terms of the particular test that was used to measure this property. Rockwell, Vickers, or

Brinell are some of the methods of testing. Brinell hardness testing is the most common

method for hardness testing. In Brinell tests, a hard, spherical indenter is forced into the

surface of the metal to be tested. The diameter of the hardened steel (or tungsten carbide)

indenter is ranges from 5-10mm. Standard loads range between 500 and 3000 Kg; during a

test, the load is maintained constant for a specified time (between 10 and 30 seconds). Here

we used 5mm indenter ball diameter of the hardened steel, the 750 Kg load is maintained

constant for a 10 seconds. Then indentation on the specimen is measured by hand microscope

Fig. 10.3

Fig 10.3 Sample specimen for Hardness test

64

10.5 DENSITY OF CAST SPECIMEN

A material's density is defined as its mass per unit volume. It is, essentially, a measurement of

how tightly matter is crammed together. The principle of density was discovered by the

Greek scientist Archimedes. The SI unit of density is kilogram per cubic meter (kg/m3). It is

also frequently represented in the cgs unit of grams per cubic centimetre (g/cm3).Archimedes‘

principle:

An object weighs less in water than it does in the air. This loss of weight is due to the

up thrust of the water acting upon it and is equal to the weight of the liquid displaced.

The weight of the performs were taken in a digital balance that is weight of the

perform in water. The readings are noted and tabulated

The density was calculated using the formula

= Wa/ (Wa-Wb) ( b) where Wa is the weight in air, Wb the weight in water and

b is the density of water.

65

10.6 WEAR TEST

Experiments have been conducted in the Pin-on-disc type Friction and Wear monitor Pin On

Disc Friction & Wear Testing Machine (19238622)with data acquisition system, which was

used to evaluate the wear behaviour of the composite, against hardened ground steel disc (En-

32) having hardness 65 HRC and surface roughness (Ra) 0.5 μm. It is versatile equipment

designed to study wear under sliding condition only. Sliding generally occurs between a

stationary Pin and a rotating disc. The disc rotates with the help of a D.C. motor; having

speed range 0-2000 rev/min with wear track diameter 10-140 mm which could yield sliding

speed 0.26 to 10m/s. Load is to be applied on pin (specimen) by dead weight through pulley

string arrangement. The system has a maximum loading capacity of 200N.

The tests have been carried out under the following conditions:

• The specimens under tests were fixed to the collect. The collect along with the

specimen (Pin) is positioned at a particular track diameter 90mm. This track diameter is to be

changed after each tests i.e. a fresh track is to be selected for each specimen. During

experiment the specimens remains fixed and disc rotates.

• Load is applied through a dead weight loading system to press the pin against the

disc.

• Frictional force arises at the contact can be read out from the controller.

• The speed of the disc or motor rpm can be varied through the controller.

• For a particular type of composite 27 sets of test pieces were tested.

• Each set of test was carried out for a period of 6 hrs run. After each one hour run the

test pieces were removed from the machine and weighted accurately to determine the loss in

weight.

66

CHAPTER 11

11. RESULTS AND DISCUSSION A detailed study was undertaken to pool-up the existing literature on Aluminium based

MMCs and efforts were put to understand the basic needs of the growing Composite industry.

This includes various aspects such as Characterization, fabrication, testing, analysis and

correlation between microstructure and the properties obtained.

The conclusions drawn from this study are

• Pure aluminium matrix is preferred to various alloy matrices due to the high

temperature stability of the aluminium as compared with aluminium alloys. Lower working

temperature‘s in case of alloy matrices is attributed to lower stability of the alloy matrix and

coarsening of the grains. In addition, the load transfer in case of pure aluminium matrix is

more effective due to the clean interface.

• There exists a wide range of database in the literature for different types of

reinforcements in Aluminium Metal Matrix Composites.

• In particle reinforced composites, the fracture mode was observed to depend on

reinforcement purity, reinforcement particle size, and nature of interface, volume fraction of

reinforcement, fabrication route adopted, and extent of hot working, presence of any

intermetallic precipitates and extent of coherency of second phase with the matrix.

• There are varieties of techniques available for production of metal matrix composite.

Each having its own merits and demerits.. In particular, some are far more expensive than

others. The manufacturer generally prefers the lowest cost route. Therefore, stir-casting

technique represents a substantial proportion of the MMCs in commercial sectors today.

Thus the priority of this work will be to prepare MMC using red mud (an industrial waste

from Bayer‘s process) as reinforcement material and to study its wear characteristics. The

effect of different dependant factors primarily sliding velocity, normal load, effect of heat

treatment temperature and cooling media are also to be studied.

67

Table 11.1 Hardness values of Casted specimens

Load: 750 kgf Indenter Ball diameter : 5 mm Indentation Time : 10 Sec

S.No SPECIMEN HARDNESS

(BHN)

1 0 116.854

2 5 136.657

3 10 139.0031

4 15 162.854

5 20 169.261

6 25 172.072

7 30 175.300

Table 11.2 Density values of Casted Specimens

S.No SPECIMEN DENSITY (g/cc)

1 0 2.68

2 5 2.96

3 10 2.98

4 15 2.99

5 20 2.96

6 25 2.95

7 30 2.97

Table 11.3 Wear test on casted Specimens

S.No SPECIMEN

LOAD

(N)

VELOCITY

(m/s)

WEAR

(microns)

WEIGHT

LOSS (g)

Frictional

force(N)

1 Pure 30 2 163 0.0133 2.1

2 5 50 3 180 0.0268 6

3 10 70 4 434 0.0596 6.2

4 15 30 2 69 0.0054 5.3

5 20 50 3 257 0.0671 17.8

6 25 70 4 414 0.0627 27.4

7 30 30 2 98 0.0110 3.7

68

Fig 11.1 Graph showing change in hardness

Fig 11.2 Graph showing change in density

0

20

40

60

80

100

120

140

160

180

200

0 5 10 15 20 25 30

Har

dn

esss

in B

HN

% of Red Mud

BHN

BHN

2.5

2.55

2.6

2.65

2.7

2.75

2.8

2.85

2.9

2.95

3

3.05

0 5 10 15 20 25 30

De

nsi

ty in

g/c

c

% of Red Mud

Density

69

Artificial Neural Network (ANN) was employed to develop mathematical model for wear

prediction using Decision Prediction Tool 5.7.1. The accuracy of the developed model is

83%.

The image of output obtained during the operation of Neural Network tool were given below

70

71

CHAPTER-12

12 .REFERENCE

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composite materials based on EN AW-2124 aluminium alloy reinforced with the BN or

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Material Processing Technology 2003-133:203–6.

6. Liu HN, Ogi K. Dry sliding wear on Al2O3 continuous fibre reinforced Al–Cu alloy

against steel counterface. J Mater Sci 1999-34:5593–9.

7. Moustafa SF, Soliman FA. Wear resistance of d-type alumina fibre reinforced Al–4% Cu

matrix composite. Tribol Lett 1997-3-311–5.

8. Hossein Abdizadeh , Maziar Ashuri , Pooyan Tavakoli Moghadam , Arshia

Nouribahadory , Hamid Reza Baharvandi, Improvement in physical and mechanical

properties of aluminium/zircon composites fabricated by powder metallurgy method,

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73

CHAPTER-13

ANNEXURE

List of Publications:

This project work was presented in the National level student‘s conference on

―DESIGN, MATERIAL & CONSTRUCTION‖ on 25th & 26

th August 2011 conducted by

VEL TECH DR.RR & DR.SR TECHNICAL UNIVERSITY, Avadi, Chennai. We were

awarded with the First best paper award, under the stream MECHANICAL.

74

CHAPTER 14

CONCLUSION

Form the experimentation; it was found that while using low particle size

reinforcement material the possibility of float or tend to sink will be more depends upon

their density liquid metal and so that dispersion of the particles are not uniform. Therefore

it is decided to use different stirrer model with varying speed and timing. Finally it is

decided to use four blades with 90 degree angle, stirring speed 550 rpm and time is 60 sec

to get proper distribution of the reinforcement material.

Red mud, the waste generated from alumina plant can be successfully used as a

reinforcing material to produce Metal-Matrix Composite (MMC) component in aluminum

matrix to be used in wear environment. It can be successfully used in place of

conventional aluminum intensive material.

Increase in % of reinforcement of the material increases the hardness of the work piece,

since reinforcement material harder than the matrix material. The density of the

composite will obviously increases since increase in reinforcement increases the density

of the material as per the rule of mixture.

The wear rate of the composite decrease with increases in % of reinforcement materials.

Finally, the wear property of the composite depends on many factors, such as sliding

velocity, sliding distance and load. Computation through neural networks is one of the

recently growing areas of artificial intelligence. Neural networks are promising due to

their ability to learn highly non-liner relationship. It can also be gainfully employed to

simulate property-parameters correlation ship in a space larger than the experimental

domain. It is evident from the present study that the artificial neural technique has the

potential to predict and analyze the wear behavior of metal matrix composites if it is

properly trained.