International Journal of Pure and Applied Mathematics ... · of a polymer or plastic injection mould is an integ ral part of plastic injection moulding as the quantity of the final

OPTIMIZATION OF INJECTION MOULDING MOULD FLOW ANALYSIS USING

TAGUCHI APPROACH

1N.Subramani, 2J.Ganesh Murali, 3P.Vijaya Rajan, 4C.Godwin Jose

1Assistant Professor,

2Professor,

Karpagam College of Engineering, Coimbatore.

3Assistant Professor, Sri Sairam Engineering College, Chennai.

4Assistant Professor, PSN College of Engineering and Technology,Tirunelveli. [email protected]

Abstract: This work is intended to optimize the mould

flow of the hopper by using the ANSYS and Taguchi

method. Moulding is considered the most prominent

process for mass production. There are many kinds of

plastic moulding methods are there. In that method here

the injection moulding method is selected for the

research. Each technique has its own advantages in the

manufacturing of specific item. Among these various

plastic production technologies, injection moulding

takes up approximately 32%, because of its ability in

producing complex parts with low cost and high

productivity. Here the analysis helps us to optimize the

flow in moulding.

1. Introduction

Injection moulding has become the most important

process for manufacturing plastic parts due to its ability

to produce complex shapes with good dimensional

accuracy[1].Cad/ Cam can help designer to speed up

design for the plastic part and mould design process

and reduce the long lead time[2]

The Taguchi approach is mostly used in the

industrial environment, but it can also be used for

scientific research. The method is based on balanced

orthogonal arrays[3].In this work , the combined

effects of multi moulding process parameters are

analyzed by the combination of orthogonal experiments

and mould flow simulation tests and then the sensible

gate location and optimized parameter combination is

obtained[4].This study applies of the optimization

strategy based on Taguchi’s experimental designs [5-6]

The introduction of simulation software has made

a significant impact in the injection moulding industry.

With the increasing use of computers in design

engineering, the amount of commercially available

software on the market has also increased [7].

Traditional trial runs on the factory floor can be

replaced by less costly computer simulations. Now

days, research on optimizing the plastic injection

moulding process has developed a lot. CAD/CAE tools

are used to produce an optimal mould gating design

using CATIA and Mould flow applications. The mould

flow analysis helps in reducing costs and time and also

prevents other defects occurring in the process [8].

Injection moulding is a process of forming a product by

forcing molten plastic material under pressure into a

mould where it is cooled, solidified and subsequently

released by opening the two or three halves of the

mould. Bryce.M.D (1996) has stated that the injection

moulding is used for the formation of intricate plastic

parts with excellent dimensional accuracy. The design

of a polymer or plastic injection mould is an integral

part of plastic injection moulding as the quantity of the

final plastics part is greatly reliant on the injection

mould.

Figure 2.1 Injection moulding

International Journal of Pure and Applied MathematicsVolume 118 No. 11 2018, 241-250ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.eudoi: 10.12732/ijpam.v118i11.30Special Issue ijpam.eu

241

Figure 2.2 Injection moulding cycle

1. Factors Affecting Injection Moulding

There are several factors that are critical to the injection

moulding process. These include:

• Plastic Melt Temperatures

• Barrel Temperatures

• Nozzle Temperatures

• Plastic Flow Rates

• Plastic Pressure or Screw Back Pressure

• Plastic Cooling Rates

2. Mould Flow Analysis

Analysis is essential for designing and mould making

through simulation step-up and result interpretation to

show how changes to wall thickness, gate location,

material and geometry affects manufacturability and

also experiments with “what-if” scenarios before

finalizing a design.

Figure 2.3 Hopper

The Mould flow analysis was performed using

Autodesk Mould Flow analysis software.

3. Steps involved in Mould Flow Analysis

1. Converting the 3D model in STEP OR IGES format.

2. Meshing the model by using dual domain type of

mesh.

3. Importing the meshed file to the solver package

specifying the boundary condition, loads such as

injection pressure, injection time, mould temperature,

melt temperature, material properties etc.

4. Building the feed system such as sprue, runner and

gate.

5. Mesh the feed system and cooling lines.

6. Run the analysis for different analysis types like fill,

flow, war page etc.

7. Study the result, interpret them.

8. Establish the optimized data for runner, gate, sprue

dimensions, coolant temperature etc. Based on the

analysis the optimal combination of part geometry,

material choice, gate location and process parameter to

produce quality finish part are determined.

Figure 2.4 Meshing of Hopper part

4. Parameters for Mould Flow Analysis

•

• Specification of the moulding material including

grade and color.

• Moulding machine specification.

International Journal of Pure and Applied Mathematics Special Issue

242

• Number of impression.

• Shrinkage of the material.

• Type of mould

• Type of runner or gate

• Parting line of mould

• Types of ejection system.

• Type of cooling system.

• Injection pressure.

• Shot weight.

• Distance between the tie bars.

• Shut height of mould.

• Shut height of machine.

• Clamping force.

• A fully detailed component drawing.

5. Air trap analysis

Figure 5.1 Air Trap Analysis at 50cm3 / sec

mould flow rate

Figure 5.2 Air Trap Analysis at 60cm3/ sec

mould flow rate


mould flow rate


mould flow rate

The ANSYS Mould flow analysis of the

occurrence of air traps in the hopper component is

performed. Further the analysis for different situations

is considered based on the variance of mould flow

mould flow rate. In the above results, the pink colour

indicates the presence of air traps. For the first case air

traps occur throughout the mould. The number of air

traps is more due to the slow mould flow mould flow

rate. In the last case also the number of air traps is

more. This is due to the high mould flow mould flow

rate. So with slower as well as higher mould flow

mould flow rates we can see there is a high occurrence

of air traps. In the case three, there is a mode mould

flow rate number of air traps due to the mode mould

flow rate mould flow mould flow rate.

5.1 Bulk Temperature Analysis

Figure 5.5 Bulk Temperature Analysis at 50cm3/ sec

mould flow rate


mould flow rate


243


mould flow rate


mould flow rate

From the above cases we have concluded that,

when the temperature with in the mould is high, freeze

time will increase. Mould temperature is directly

proportional to the freeze time. The mould temperature

will also affect the cycle time of the process. In Fig 5.8

Bulk Temperature is low, so there is a decrease in

freeze time .Likewise in Fig 5.12 the Bulk temperature

increases and the freeze time also increases.

5.2 Freeze Time Analysis

Figure 5.9 Freeze Time Analysis at 50cm3/ sec

mould flow rate


mould flow rate


mould flow rate


mould flow rate

There is a balance always struck between freeze

times and feeding system. The freeze time depends up

on the wall thickness .From the above results we come

to conclude that the freeze time depends up on the

temperature of the mould and also heat transfer to the

walls. In Fig 5.18 The maximum time taken for

solidification is about 273.5 seconds and minimum

time for solidification is 266.7 seconds.

5.3 Fill Time Analysis

Figure 5.13 Fill Time Analysis at 50cm3/ sec

mould flow rate


mould flow rate


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Fig 5.15 Fill Time Analysis at 75cm3/ sec

mould flow rate


mould flow rate

Fill time analysis is used to evaluate the time for

filling the mould cavity with molten metal. If the mould

flow rate of flow of molten metal is high, then the fill

time is low. Thus the mould flow rate of flow of molten

metal is inversely proportional to the fill time. In Fig

5.19, the mould flow mould flow rate is low and so the

fill time is increased as 6.882 seconds. In Fig 5.17, the

mould flow mould flow rate is 100cm3 / second and the

fill time reduces to 1.666 seconds. If mould flow mould

flow rate increases the air trap increases for the optimal

process the correct mould flow rate should be selected.

5.4 Filling Pressure Analysis

Figure 5.17 Filling Pressure Analysis at 50cm3/ sec

mould flow rate


mould flow rate


mould flow rate


mould flow rate

From the results shows that the pressure is still

nonexistence at the initial stages and increases

somewhat due to the filling of small amount of

feedstock in to the mould. Filling pressure is inversely

proportional to the filling time and directly proportional

to mould flow rate. Increase in pressure leads to slight

increase in temperature.

5.5 Weld Line Analysis


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Figure 5.21 Weld Line Analysis at 50cm3/ sec

mould flow rate


mould flow rate


mould flow rate


mould flow rate

Weld lines are also a mouldings defects, Weld

lines are generally formed when two melt fronts come

in contact with each other so that they do not bond

perfectly. weld lines are also formed due to presences

of pins ,cores and multiple gates are one of the most

significant defects from both performance and

appearances point of u This can cause a weak area in

the part which can cause breakage when the part is

under stress. In the results we conclude that weld line

of different mould flow mould flow rate are studied and

the defects are highlighted in different colour. The fig

5.25 shows that there was an maximum defect in the

corners. Therefore increasing rate of mould flow results

in formation of weld line.

6. Optimisation Using Taguchi

There are a number of parameters that have influences

on an injection moulding process, which are types of

material used, types of mould base material, types of

cavity insert material, types of machine, the profile of

the parts, selection of coolant runners as well as

selection of the coolant liquid. However in this study,

only a few major factors are taken into considerations

as to make sure the result can be achieved.

Assumptions to be made

• Gate dimension factor is neglected because of its

design is not identical for every part.

• The temperature of the environment is assumed

constant.

• The coolant is assumed as pure water.

• The effects of other minor factors (Other than

melting temperature, mould temperature, filling and

packing processes) are not to be under the topic of

discussion.

• The layout of the cooling channels is assumed to

maintain a constant temperature.

• The effects due to the shape and size of the mould

and product are neglected due to various shapes of

product.

• The plastic material used in all of the simulations

is amorphous thermoplastic PC/ABS blend, Cycoloy

C2950HF from GE. Its viscosity is between 102 and

104poise

Where the shear rate is in 102-103 s-1 range. The

range of melt temperature is between 220 OC and 400 OC approximately.

Table 6.1 Physical and Mechanical Properties

Specific heat , Cp (J/kgoC) 1871

Glass t ransit ion temperature,

Tg (oC)

112

Thermal expansion coefficient,

α (mm/moC)

74

Elastic modulus, E (MPa) 2.63 x 103

Poisson's ratio, Ʋ 0.23

Thermal conductivity, K (w/moC) 0.27

The length of weld line X of the hopper obtained

from the experiment is used to calculate the signal-to-

noise (S/N) ratio to obtain the best parameter setting


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arrangement. From this technique, the percentage of

contribution is calculated in determining which of the

factor has significant effect on part’s war page. Taguchi

method is again applied where there are three factors

identified to be controlled; Pressure (A), Temperature

(B),Fill time(C). Each factor is downsized to five levels

where an orthogonal array of L9 is chosen and all

parameters have been identified.

Table 6.2 The Three Level of Effective Factor

For Experiment Variance

Factors Levels

1 2 3

Pressure , A (MPa) 6.2 7.1 7.8

Bulk temperature ,B

(oc) 230.0 230.5 231.06

Filling time ,C(s) 6.8 3.4 2.2

Table 6.3 L9 Orthogonal Array Variance

Trail Control factor

A B C

1 1 1 1

2 1 2 2

3 1 3 3

4 2 1 2

5 2 2 3

6 2 3 1

7 3 1 3

8 3 2 1

9 3 3 2

Table 6.4 The Combination Parameters for the Control

Factors

TRAIL

CONTROL FACTOR

A B C

1 6.2 230.0 6.8

2 6.2 230.5 3.4

3 6.2 231.1 2.2

4 7.1 230.0 3.4

5 7.1 230.5 2.2

6 7.1 231.1 6.8

7 7.8 230.0 2.2

8 7.8 230.5 6.8

9 7.8 231.1 3.4

The length of weld lines data obtained from the

simulation process are also analysed using Analysis of

Variance (ANOVA) and the level of confidence is set

at 0.05. The results are then taken and compared with

the results obtained from the SN ratio method. The

interaction effect of factors is identified and the

contribution of each factor towards the total effect is

analysed. The percentage contribution calculated

determines which of the factors mainly affect the length

of weld lines. The length of weld line is then measured

and S/N ratios are calculated. In this case, ‘the smaller

the better quality’ equation from Taguchi method is

chosen as far as weld line is concerned.

able 6.5 Summary of the Results Length of Weld Line

NO

CONTROL FACTOR LENGTH OF WELD LINE

S/N FOR D PRESSURE TEPERATURE FILLTIME

A B C D

1 6.2 230 6.8 6.14 -15.763

2 6.2 230.5 3.4 6.06 -15.649

3 6.2 231.1 2.2 6.42 -16.150

4 7.1 230 3.4 5.98 -15.534

5 7.1 230.5 2.2 6.21 -15.861

6 7.1 231.1 6.8 6.26 -15.931

7 7.8 230 2.2 6.34 -16.041

8 7.8 230.5 6.8 6.14 -15.763

9 7.8 231.1 3.4 6.1 -15.706

The data in Table 6.5 also analyzed using Analysis

of Variance (ANOVA) where the relative percentage

contribution of all factors is determined by comparing

the relative variance. The ANOVA then computes the

degrees of freedom, variance, F-ratio, sums of squares,

pure sum of square and percentage contribution. The

examples of calculations are shown below and the

results of S/N ratio for length of weld line in thin plate

are listed in Table 6. Only weld line at hole X is

considered because length of weld line formation at


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both of holes that shows the similar pattern under

different parameter settings.

Table 6.6 Response Table of S/N Ratio For

Length of Weld Line

Level Pressure Temperature Fill Time

1 -15.78 -15.78 -16.02

2 -15.78 -15.76 -15.63

3 -15.93 -15.93 -15.82

Figure 6.1 Main effects plot for SN ratios

From the S/N ratio response in Table VI, the

highest value from each factor is considered the best

and chosen as the finest grouping of parameters.

Table 6.7 Best Setting of Combination Parameters

Factors Paramerers

Pressure 7.1

Temperature 230.5

Fill Time 3.4

Furthermore the difference between levels in

Table 6.6 also shows which factor is more significant

that give effects on length of weld line in thin plate.

Therefore, it is understood that the most major factor

that affects on length of weld line in hopper is Pressure

(A), Temperature (B), Fill time(C).The data in Table

6.5 is also analyzed using Analysis of Variance

(ANOVA) that computes the sums of squares, degrees

of freedom, variance and percentage contribution. The

examples of calculations for these quantities are shown

below and the results lengths of weld line in thin plate

are summarized in Table 6.8.

Table 6.8 Anova Table For Hooper

SOURCE DF S V F P

Pressure 2 0.01027 0.005137 0.72 0.582

Temperature 2 0.05229 0.026147 3.66 0.215

Fill Time 2 0.22595 0.112977 15.81 0.046

Residual Error 2 0.01430 0.007148

Total 8 0.30282

7. Conclusion

There are several factors such as feed systems, cooling

channel positions, gate sizes that need to be determined

first in order to design a plastic injection mould.

Simulation software can help us reducing time taken to

test. From the above experiment we conclude that the

optimised parameters for injection moulding of

hooper is pressure 7.1 MPa, Temperature 230.5oC ,Fill

time 3.4s and Mould flow rate of 50cm3/s . In this stage

the formation of the weld line is low than compared to

the other cases where we get optimum weld line this

optimisation increase the product life and cycle time.

The Ansys mould flow results also shows that air traps

are minimum at these optimised condition.


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International Journal of Pure and Applied Mathematics ... · of a polymer or plastic injection mould is an integ ral part of plastic injection moulding as the quantity of the final