Pre Synopsis Presentation

1. M. Tech. Pre-Submission
Proposed Topic
MULTI-RESPONSE
OPTIMIZATION OFAA1100 MMC
THROUGH
MIXTURE DoE
Presented by
GOURAV KALRA
Under Supervision of
Dr. Bikram Jit Singh

2. CONTENTS
• Need of the Study
• Introduction
• Literature Review
• Research Gap
• Objectives
• Methodology Proposed
• Resources Required
• References

3. NEED ???

4. CURRENT PROBLEM...
• The issue of CO2 emission has become more
and more critical during the last decades.
• One of the main sources of CO2 emission is
transportation.
• One litre of petrol consumption induces 2.34
kg CO2 and the petrol consumption is directly
connected to the average weight of a car.
• European Commission has proposed to
reduce the average CO2 emission from new
cars to 130g/km by 2018.

5. WEIGHT IS A PROBLEM??
• To fulfil these regulations, the grass root
solution is to reduce the weight of a car.
• An average weight for a hatchback car
should be less than 800kg to meet above
regulations.
• Therefore, the use of light metals or its
composites for car-bodies or chassis are
erupting as a logical SOLUTION for this
nuisance.

6. CAR CRASHING TEST
But…
Car Crashing test is must to ensure
safety….so to clear this mandatory
test:
• Compressive Strength of body
material should at least be 170MPa
to 310MPa
and the corresponding
• Hardness of car body material must
lie in the range of 150BHN to
190BHN

7. PROPOSED SOLUTION
• Metal matrix composites (MMCs) should be engineered on
combination of the metal/alloy (as a Matrix) and hard
particles/ceramics (as reinforcements) to tailored desired
mechanical and metallurgical properties.
• In present case, rarely used AA1100 alloy reinforced with different
percentages of Si, Cu and Mg particles has been selected to make
an AA1100 MMC, having sufficient Mechanical and Micro-structural
Properties (or Responses).

8. INTRODUCTION

9. COMPOSITES
• Composite materials are engineered or naturally occurring materials made
from two or more constituent materials with significantly different physical
or chemical properties.
• Individual materials that make up composites are called Constituents.
• Mostly composites have two constituent materials:
- Binder or Matrix (like polymers, metals or ceramics) and
- Reinforcement (in the form of fibers, particles or fillers)
• The matrix holds the reinforcements in an orderly pattern because the
reinforcements are usually discontinuous.
• The matrix also helps to transfer load among the reinforcements

10. CLASSIFICATION OF COMP.
Composites are classified in two parts:
• Natural
• Manmade or Synthetic
Synthetic composites are further classified in two ways:
• On the basis of matrix used
• on the basis of the geometry of the reinforcement
Based on the matrix phase used, multiphase composites are divided into three
categories:
• Polymer-matrix composites (PMCs).
• Ceramic-matrix composites (CMCs).
• Metal matrix composites (MMCs)

11. STRUCTURE OF MMCs
Metal Matrix + Reinforcements

12. FABRICATION OF AA1100 MMC
STIR CASTING PROCESS
• Mechanical stirring is used in stir
casting liquid state method of
composites materials fabrication,
in which a dispersed phase
(ceramic particles) is mixed with
a molten matrix metal.

13. SCHIEMATIC DIAGRAM

14. STIR CASTING
Several factors are considered in preparing
metal matrix composites by stir casting
method, LIKE:
1. Maintaining a uniform distributed
reinforced material.
2. Wet ability of the substance.
3. Porosity of the composites.
4. Chemical reaction between the
reinforcement material and the matrix
alloy.

15. PROCESS PARAMETRS
Process parameters are:
• Stirring Speed (300rpm to 600rpm) Stirring speed directly influence the
Hardness and Compressive Strength of the composite
• Stirring time (5mins to 20mins ) Stirring time directly influence the
Hardness of the composite
• Stirring Temperature (650°C to 800°C ) it also have impact on Hardness.

16. COMPOSITIONAL PARAMETERS
Compositional Parameters are:
• Aluminum Alloy AA1100 As a Base Metal
• Silicon (up 2% to 14%) the hardness of the alloy is
increased with Si content but ductility and machinability
are reduced. However it improves the strength.
• Magnesium (1% to 8%) improves the Wettability in the
liquid solutions
• Copper (3% to 10% ) increases strength and hardness and
decreases the percent elongation

17. RESPONSES
Two types of responses have been decided to be taken care of…. as far as
MMCs for car bodies are in question.
• Mechanical Responses (or Properties)
(Hardness, Compressive strength)
• Metallurgical Responses (or Properties)
(Particle Size, Micro-structure and Morphology)

18. OPTIMIZATION TECHNIQUE
Mixture Design of Experiment:
• Mixture experiments are a special class of response surface
experiments in which the product under investigation is made up of
several components or ingredients.
• Designs for these experiments are useful because many product
design and development activities in industrial situations involve
formulations or mixtures.
• In these situations, the response is a function of the proportions of
the different ingredients in the mixture.
• It is used to do optimization of mixtures (or composites) without
ignoring variations in interested responses due to process
parameters also.
• MINITAB (a Windows based statistical software) can create designs
and analyze data to bring necessary optimizations.

19. LITERATURE REVIEW

25. RESEARCH GAPS

26. • Although Stir Casting Process has been used for fabrication of Al/Si/Cu/Mg
composites, but little work has been done to fabricate AA1100 MMCs with
varying percentage of reinforcements having minimum porosity.
• Compressive Strength of AA1100 (fabricated through Stir Casting) had been
rarely considered and calculated. Behavioral analyses of strengths are completely
missing.
• Parametric Optimization through ‘Mixture Design of Experiments’ of Al-Si-Mg-
Cu MMCs is quite hard to find in existing literature.
• Micro-structural Properties like Particle Size, Structure and its Morphology
directly impacts the Mechanical Properties but still few researchers had
monitored both Mechanical & Micro-structural properties together, while making
AA1100 MMCs specifically.

27. • Mostly researcher used the 2000, 5000, 6000 and 7000 series of alloys and
less work has been contributed on AA1100 for fabricating MMCs.
• Literature investigated that mostly researchers had used one factor at a time
(OFAT) technique while fabricating MMCs which required more time, cost
and effort in conducting experiments and reaching at some logical
conclusions.
• In OFAT, researcher generally varies only one factor to see its impact on
response while maintaining all other factors at some constant values. Same
procedure is repeated number of time by taking one factor as a variable
each time.
• Suggested technique of DoE is based on Multi Factor at a Time (MFAT)
which can vary more than two factors at a time and assess the
corresponding affect on concerned responses, effectively

28. OBJECTIVES

29. • To prepare the cost-effective MMC material by taking AA1100 alloy
as a matrix and Silicon, Copper and Magnesium as reinforcements
by applying Mixture DoE technique on Stir Casting Process.
• To analyze the Micro Structural Characteristics
(like; Grain Structure, Particle Size etc.) of the as prepared MMCs.
• To measure and monitor Mechanical Properties
(like; Compressive Strength & Hardness) of the as prepared MMCs.

30. • Qualitative & Quantitative Analysis of these Mechanical
Properties through Mixture DoE (applied further with the help of
MINITAB software).
• Optimization of Process Parameter (like; Stirring Speed, Stirring
Time and Temperature of Molten Bath) along with Compositional
Parameters (like; Percentage of AA1100 alloy, Si, Cu and Mg) for
achieving Compressive Strength and Hardness in required
permissible limits.
• Result Verification and Validation through 2 sample t–test.

31. PROPOSED METHODOLOGY

32. MAJOR PHASES
• First phase (Preparation of samples)
• Second phase (Testing of composites)
• Third phase (Optimization of parameters, analysis etc.)

34. Multi-Response Optimization of
AA1100 MMHC
through
Mixture DoE

35. Factors Lower Level Upper Level
AA1100 (%) 70% 90%
Si (%) 5% 16%
Cu (%) 4% 10%
Mg (%)
Stirring Time (Mins) 10 Mins 25 Mins
Stirring Speed
Temperature
Replicate is taken as 2 (it means each run is executed twice)
Factors with Levels
2% (Fixed)
400 RPM (Fixed)
700-710 Degree Celcius (Fixed)

36. Extreme Vertices Design
Components: 3 Design points: 36
Process variables: 1 Design degree: 1
Mixture total: 0.98000
Number of Boundaries for Each Dimension
Point Type 1 2 0
Dimension 0 1 2
Number 4 4 1
Number of Design Points for Each Type
Point Type 1 2 3 0 -1
Distinct 8 0 0 2 8
Replicates 2 0 0 2 2
Total number 16 0 0 4 16
Bounds of Mixture Components
Amount Proportion Pseudo component
Comp Lower Upper Lower Upper Lower Upper
A 0.720000 0.890000 0.734694 0.908163 0.000000 1.000000
B 0.050000 0.160000 0.051020 0.163265 0.000000 0.647059
C 0.040000 0.100000 0.040816 0.102041 0.000000 0.352941
* NOTE * Bounds were adjusted to accommodate specified constraints.

38. Process Factors
AA1100 (%) Si (%) Cu (%) Mg (%) Stirring Time (Mins) Compressive Strength (MPa) Hardness (VH)
1 0.83 0.05 0.10 0.02 10 334 85
2 0.72 0.16 0.10 0.02 5 0 0
3 0.79 0.13 0.06 0.02 5 210 50
4 0.89 0.05 0.04 0.02 10 256 60
5 0.81 0.11 0.07 0.02 5 242 64
6 0.78 0.16 0.04 0.02 10 325 88
7 0.76 0.13 0.08 0.02 10 0 0
8 0.82 0.08 0.09 0.02 5 326 79
9 0.79 0.13 0.06 0.02 10 215 56
10 0.83 0.05 0.10 0.02 5 328 81
11 0.81 0.11 0.07 0.02 10 250 72
12 0.72 0.16 0.10 0.02 10 0 0
13 0.76 0.13 0.08 0.02 10 0 0
14 0.78 0.16 0.04 0.02 10 321 85
15 0.89 0.05 0.04 0.02 5 253 58
16 0.85 0.08 0.06 0.02 5 237 56
17 0.82 0.08 0.09 0.02 10 333 88
18 0.85 0.08 0.06 0.02 5 236 56
19 0.89 0.05 0.04 0.02 5 251 56
20 0.83 0.05 0.10 0.02 5 327 80
21 0.89 0.05 0.04 0.02 10 258 63
22 0.76 0.13 0.08 0.02 5 0 0
23 0.78 0.16 0.04 0.02 5 313 80
24 0.72 0.16 0.10 0.02 10 0 0
25 0.82 0.08 0.09 0.02 5 322 76
26 0.82 0.08 0.09 0.02 10 330 83
27 0.79 0.13 0.06 0.02 10 217 55
28 0.76 0.13 0.08 0.02 5 0 0
29 0.72 0.16 0.10 0.02 5 0 0
30 0.78 0.16 0.04 0.02 5 310 76
31 0.81 0.11 0.07 0.02 10 252 71
32 0.81 0.11 0.07 0.02 5 244 68
33 0.83 0.05 0.10 0.02 10 336 86
34 0.79 0.13 0.06 0.02 5 209 48
35 0.85 0.08 0.06 0.02 10 245 62
36 0.85 0.08 0.06 0.02 10 247 65
Runs
Compositional Factors Mechanical Responses
Designed Experimental Matrix (by Mixture DoE)

40. Regression for Mixtures:
Compressive Strength Versus Parameters
Estimated Regression Coefficients for Compressive Strength (component proportions)
Term Coef SE Coef T P VIF
AA1100 (%) -79 103.5 * * 83.3
Si (%) 30371 8821.1 * * 11813.0
Cu (%) -80168 12569.4 * * 10193.9
AA1100 (%)*Si (%) -34943 10955.8 -3.19 0.003 11491.0
AA1100 (%)*Cu (%) 99149 15346.2 6.46 0.000 9959.1
AA1100 (%)*Stirring Time (Mins) 7 38.9 0.19 0.851 11.8
Si (%)*Stirring Time (Mins) -4 201.6 -0.02 0.985 6.2
Cu (%)*Stirring Time (Mins) -36 380.8 -0.09 0.926 9.4
* NOTE * Coefficients are calculated for coded process variables.
S = 56.0101 PRESS = 125265
R-Sq = 83.43% R-Sq(pred) = 76.37% R-Sq(adj) = 79.29%

41. Analysis of Variance for Compressive Strength
Source DF Seq SS Adj SS Adj MS F P
Regression 7 442303 442303 63186 20.14 0.000
Component Only
Linear 2 233330 242424 121212 38.64 0.000
Quadratic 2 208588 208588 104294 33.25 0.000
AA1100(%)*Si (%) 1 77638 31912 31912 10.17 0.003
AA1100(%)*Cu(%) 1 130950 130950 130950 41.74 0.000
Component* Stirring Time (Mins)
Linear 3 385 385 128 0.04 0.989
AA1100(%)*Stirring Time (Mins) 1 353 113 113 0.04 0.851
Si (%)*Stirring Time (Mins) 1 5 1 1 0.00 0.985
Cu (%)*Stirring Time (Mins) 1 28 28 28 0.01 0.926
Residual Error 28 87840 87840 3137
Lack-of-Fit 10 87799 87799 8780 3902.18 0.000
Pure Error 18 40 40 2
Total 35 530142
Estimated Regression Coefficients for Compressive Strength
(component amounts)
Term Coef
AA1100 (%) -80.3845
Si (%) 30990.5
Cu (%) -81804.2
AA1100 (%)*Si (%) -36383.4
AA1100 (%)*Cu (%) 103237
AA1100 (%)*Stirring Time (Mins) 7.51855
Si (%)*Stirring Time (Mins) -3.84508
Cu (%)*Stirring Time (Mins) -36.6481

42. Compressive Strength = -80.4 AA1100(%) + 30990.5 Si(%)-
(MPa) 81804.2 Cu(%)-36383.4
AA1100(%)*Si(%) + 103237 AA1100(%)*
Cu(%) + 7.51855 AA1100(%)* Stirring
Time(Mins) - 3.84508 Si(%)*Stirring
Time(Mins) - 36.6481 Cu(%)*Stirring
Time (Mins)
Regression Equation

44. Regression for Mixtures:
Hardness Versus Parameters
Estimated Regression Coefficients for Hardness (component proportions)
Term Coef SE Coef T P VIF
AA1100 (%) -39 28.04 * * 83.3
Si (%) 7073 2389.25 * * 11813.0
Cu (%) -20146 3404.48 * * 10193.9
AA1100 (%)*Si (%) -7976 2967.43 -2.69 0.012 11491.0
AA1100 (%)*Cu (%) 25027 4156.61 6.02 0.000 9959.1
AA1100 (%)*Stirring Time (Mins) 6 10.53 0.58 0.564 11.8
Si (%)*Stirring Time (Mins) -4 54.60 -0.07 0.947 6.2
Cu (%)*Stirring Time (Mins) -30 103.13 -0.29 0.775 9.4
* NOTE * Coefficients are calculated for coded process variables.
S = 15.1706 PRESS = 9157.66
R-Sq = 81.27% R-Sq(pred) = 73.38% R-Sq(adj) = 76.58%

45. Analysis of Variance for Hardness (component proportions)
Source DF Seq SS Adj SS Adj MS F P
Regression 7 27952.6 27952.6 3993.23 17.35 0.000
Component Only
Linear 2 13087.5 16804.9 8402.43 36.51 0.000
Quadratic 2 14604.9 14604.9 7302.45 31.73 0.000
AA1100(%)*Si (%) 1 6261.3 1662.8 1662.82 7.23 0.012
AA1100(%)*Cu (%) 1 8343.6 8343.6 8343.59 36.25 0.000
Component* Stirring Time (Mins)
Linear 3 260.3 260.3 86.76 0.38 0.770
AA1100(%)*Stirring Time (Mins) 1 237.2 78.3 78.29 0.34 0.564
Si (%)*Stirring Time (Mins) 1 3.8 1.0 1.03 0.00 0.947
Cu (%)*Stirring Time (Mins) 1 19.2 19.2 19.20 0.08 0.775
Residual Error 28 6444.1 6444.1 230.15
Lack-of-Fit 10 6391.6 6391.6 639.16 219.14 0.000
Pure Error 18 52.5 52.5 2.92
Total 35 34396.8
Estimated Regression Coefficients for Hardness (component amounts)
Term Coef
AA1100 (%) -39.9442
Si (%) 7217.79
Cu (%) -20557.1
AA1100 (%)*Si (%) -8305.14
AA1100 (%)*Cu (%) 26059.1
AA1100 (%)*Stirring Time (Mins) 6.26984
Si (%)*Stirring Time (Mins) -3.73016
Cu (%)*Stirring Time (Mins) -30.3968

46. Regression Equation
Hardness (VH) = -39.9442 AA1100(%) + 7217.79 Si(%) –
20557.1 Cu(%)- 8305.14
AA1100(%)*Si(%)+26059.1 AA1100(%)*Cu(%) +
6.26984 AA1100(%)*Stirring Time(Mins) –
3.73016 Si(%)*Stirring Time(Mins)
-30.3968 Cu(%)*Stirring Time(Mins)

49. Si (%)
AA1
1
00
(%)
0.1 50
0.1 25
0.1 00
0.075
0.050
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
>
–
–
–
–
–
–
< 0
0 50
50 1 00
1 00 1 50
1 50 200
200 250
250 300
300
Strength
Compressive
Contour Plot of Compressive Strength vs AA1100 (%), Si (%)

50. Cu (%)
AA1
1
00
(%)
0.1 0
0.09
0.08
0.07
0.06
0.05
0.04
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
>
–
–
–
–
–
–
< 0
0 50
50 1 00
1 00 1 50
1 50 200
200 250
250 300
300
Strength
Compressive
Contour Plot of Compressive Strength vs AA1100 (%), Cu (%)

51. Si (%)
AA1
1
00
(%)
0.150
0.125
0.100
0.075
0.050
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
>
–
–
–
–
< 0
0 20
20 40
40 60
60 80
80
Hardness
Contour Plot of Hardness vs AA1100 (%), Si (%)

52. Cu (%)
AA1
1
00
(%)
0.1 0
0.09
0.08
0.07
0.06
0.05
0.04
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
>
–
–
–
–
< 0
0 20
20 40
40 60
60 80
80
Hardness
Contour Plot of Hardness vs AA1100 (%), Cu (%)

53. Stirring Time (Mins) 5
Hold Values
1
0.2
Cu (%)
i
S (%)
-1 000
2
2
.
0
7
.
0 2
0.04 A 1100 (%)
A
9
8
.
0
.
0 05
s
e
r
p
m
o
C S h
t
g
n
e
r
t
e
v
i
s h
t
0
0
0
0
1 0
0
0
1
ixture Surface Plot of Compressive Strength
(component amounts
M
)

55. Stirring Time (Mins) 5
Hold Values
S (
i )
% 0
0
4
-
0. 2
2
0.72
21
0.
Cu (%)
4
0
0.
%
(
0
0
1
1
A
A
0 9
8
.
.05
0
s
s
e
n
d
r
a
H
0
2
- 0
0
0
0
2
ixture Surfa
M e Plot of Hardness
(component amounts)
c

58. Response Optimization
Parameters
Goal Lower Target Upper Weight Import
Compressive Target 300 315 320 1 1
Hardness Target 70 80 90 1 1
Global Solution
Components
AA1100 (%) = 0.8355
Si (%) = 0.0662
Cu (%) = 0.0783
Process Variables
Stirring Time = 8.5
Predicted Responses
Compressive = 321.8025 ,
Hardness = 81.2928 ,
Composite Desirability = 0.87072

60. Optimized Compositional & Process Parameters
(Optimized Settings)
Optimized Components
AA1100 (%) = 0.8355
Si (%) = 0.0662
Cu (%) = 0.0783
Fixed Components
Mg (%) = 0.02
Optimized Process Parameters
Stirring Time = 8.5
Fixed Process Parameters
Stirring Speed = 400 rpms
Temperature = 700 to 710 Degree Celsius

61. Pilot Testing
Compressive Strength Hardness Compressive Strength Hardness
1 320 84 334 85
2 321 84 210 50
3 323 85 256 60
4 301 78 242 64
5 302 78 245 62
6 310 81 247 65
7 312 82 244 68
8 299 75 336 86
9 304 80 209 48
10 297 73 217 55
11 309 81 253 58
12 311 82 237 56
13 304 79 333 88
14 305 80 236 56
15 302 79 251 56
Pilot Testing at Optimized Settings
(Runs are repeated at Optimized Values of Parametrs)
Testing at General Settings
(Runs are executed by varying Parametrs randomly in
between their respective limits)
Run

62. Verification of Compressive Strength
Achieved
(by 2 Sample t-Test)
Hypothefication for Compressive Strength
Null Hypothesis (Ho) = Mean Compressive Strength is same at OS and GS of
Parameters
Alternate Hypothesis (Ha) = Mean Compressive Strength is different at OS and
GS of
Parameters
Note: Testing is performed at 95% confidence Level

63. Two-Sample T-Test
For Compressive Strength at Optimized Settings and Compressive Strength at General Settings
Two-sample T for Compressive Strength (OS) vs Compressive Strength (GS)
N Mean StDev SE Mean
Compressive Strength (OS 15 308.00 8.16 2.1
Compressive Strength (GS 15 256.7 42.8 11
Difference = μ (Compressive Strength (OS)) - μ (Compressive Strength (GS))
Estimate for difference: 51.3
95% CI for difference: (27.4, 75.3)
T-Test of difference = 0 (vs ≠): T-Value = 4.57
P-Value = 0.004
DF = 15
t-Test Statistics
(For Compressive Strength Comparison)

67. Verification of Hardness Achieved
(by 2 Sample t-Test)
Hypothefication for Hardness
Null Hypothesis (Ho) = Mean Hardness is same at OS and GS of Parameters
Alternate Hypothesis (Ha) = Mean Hardness is different at OS and GS of
Parameters
Note: Testing is performed at 95% confidence Level

68. Two-Sample T-Test
For Hardness at Optimized Settings and Hardness at General Settings
Two-sample T for Hardness (OS) vs Hardness (GS)
N Mean StDev SE Mean
Hardness (OS) 15 80.07 3.28 0.85
Hardness (GS) 15 63.8 12.8 3.3
Difference = μ (Hardness (OS)) - μ (Hardness (GS))
Estimate for difference: 16.27
95% CI for difference: (8.99, 23.55)
T-Test of difference = 0 (vs ≠): T-Value = 4.76
P-Value = 0.001
DF = 15

72. Validation of Optimization
Mechanical
Properties Achieved
Compressive
Strength (MPa)
Hardness
(HV)
Aim ≥ 300 ≥ 80
Optimized Values
from Minitab Software
321.80 81.29
Actual Achieved 308 .00 80.06
Error 13.00 1.23
Error (%age) 4.05 1.52
Since Percent Error is less than 10% in case of
Compressive Strength & Hardness,
Hence optimization Achieved is quite Valid.

73. Do the Microscopic Test (Micro-structure, SEM
etc.) for:
-Sample close to optimization values
-Lower Value
-and Higher Values
3 0.79 0.13 0.06 0.02 50 210
0.78 0.16 0.04 0.02 80 313

74. Draw Conclusion from Microscopic
properties and justify the Mechanical
Behavior of AA1100 MMHC

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