the effect of processing condition towards the quality of ... · the effect of processing condition...

The Effect of Processing Condition towards the

Quality of Snap Fit Samples Using Taguchi

Method

Mohd Hilmi Othman Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia

Email: [email protected]

Sulaiman Hassan Department of Manufacturing and Industrial Engineering, Universiti Tun Husein Onn Malaysia


Li Lin Division of Manufacturing Engineering, School of Mechanical & Aerospace Engineering, College of Engineering,

Nanyang Technological University Singapore


Abstract—The objective of this research is to explore the

effects of parameter settings towards the quality of

thermoplastics snap fit samples through practical injection

moulding. The selected parameters in this experiment were

barrel temperature, holding pressure, injection velocity and

injection holding. The material selected for this project is

polypropylene. The quality of samples was gained by

measuring the value of shrinkage and warpage. The design

of experiment shall implement Taguchi Method L934

Orthogonal Array. Signal to Noise Ratio shall be calculated

to define the best combination of parameter settings for

each formulation. Analysis of Variance shall be used to

define the most influential factor that contributes towards

the quality of samples. Based on the results, the optimum

parameters to control warpage and shrinkage have been

rectified. The most influential factor, that affecting warpage

is holding pressure with 33.68% of the contribution. In the

other hand, injection holding with 44.25% of contribution,

need to be closely monitored if the manufacturer needs to

control shrinkage. The findings of this project shall be good

enough to be used as reference in producing similar product

in future.

Index Terms—

Taguchi Method, parameter setting

I. INTRODUCTION

The injection moulding is a greatly preferred in

manufacturing industry because of its capacity to

manufacture complex-form parts within very short cycle

time, and with good dimensional accuracy as well.

However, several processes parameters such as barrel

temperature, mould temperature, holding pressure,

injection velocity, injection time, and cooling time need

to be monitored due to the potential effects towards the

quality of injection moulded plastic artefacts. Thus,

choosing suitable parameters that concurrently satisfied

part qualities are imperative to produce good quality

product. In injection moulding, these parameter settings

were obtained either based on statically experimental

methods, computer aided simulations or operator's

experiences [1], [2]. The task becomes more difficult

when the product used for this process involving intricate

parts like a snap fit sample. Therefore, this project was

design to investigate the effect of injection moulding

parameter setting, towards the quality of a snap fit

product made from polypropylene.

II. LITERATURE REVIEW

Taguchi Method was developed by a Japanese

Statistician named Geneici Taguchi, whereby in this

method, the parameter design is employed to find optimal

process values that should be able to improve the quality

characteristic. The tolerance design is used for

determining and analyzing of the tolerance in optimal

setting recommended by the parameter design [3]. By

applying Taguchi method based on orthogonal arrays,

time and cost required for conducting of the experiments

can be reduced. Taguchi recommends the use of the

signal to noise (S/N) ratio for the determination of the

quality characteristics implemented in engineering design

problems. The S/N ratio characteristics with signed-target

type can be divided into three stages: the smaller is the

better, the nominal is the best, and the larger is the better.

In this study, the smaller the better quality characteristic

is chosen to solve warpage problem with shrinkage

variation through the optimal levels of process parameters.

In addition to S/N ratio, analysis of variance (ANOVA) is

employed to obtain the effect of the process parameters

on mechanical properties. In this way, optimal levels of

the process parameters can be estimated [4].

Journal of Industrial and Intelligent Information Vol. 2, No. 2, June 2014

2014 Engineering and Technology Publishing

Manuscript received September 4, 2013; revised November 27, 20

injection moulding, polypropylene, snap fit,

154doi: 10.12720/jiii.2.2.154-158

Several researches have successfully achieved good

control in reducing defects by using this method. For

instance, Ozcelik [3] had used Taguchi experimental

method to study the influence of injection parameters and

weld line on the mechanical properties of polypropylene

during plastic injection. In his research, he had found that

in general the mechanical tests were increased under

optimum conditions.

As for another example, Oktem et al. [4] have applied

the Taguchi optimization technique to reduce warpage

problem which were related to shrinkage variation that

were depended on process parameters. This project was

focused on producing good samples of thin-shell plastic

components for orthose part. The S/N and ANOVA are

used to find the optimum levels and to indicate the impact

of the process parameters on warpage and shrinkage. The

results show that warpage and shrinkage are improved by

about 2.17% and 0.7%.

Urzurumlu et al. [5] have minimized warpage and sink

index by controlling the process parameters of the plastic

parts with different rib cross-section types, and rib layout

angle by using Taguchi optimization method. Taguchi

optimization method was used by exploiting mould

analyses to find optimal levels and the effect of process

parameters on warpage and sink index.

Mehat et al. [6] have studied the mechanical properties

of product made from recycled plastic by utilizing the

Taguchi optimization method. She had discovered the

appropriate blending ratio of virgin and recycled plastic

that can enhance the mechanical performance exhibited

by the compound. The results reveal that the product

made of 25% recycled polypropylene (PP) and 75%

virgin PP exhibits a better flexural modulus compared to

the virgin form. The same products exhibits a 3.4%

decrease in flexural strength.

Taguchi Method application was chosen based on a

comprehensive review regarding the applications of

Taguchi Method in quality control and design

optimization of plastic products. This review has

provided more than enough information about past

research which relates to this design of experiment

approach. Therefore, it can be concluded that Taguchi

method is very suitable to solve the quality problem in

injection moulding of thermoplastic parts [7].

In terms of shrinkage and warpage studies, a research

has been carried out by Chang and Tsaur [8] by applying

an integrated theory and computer program for producing

a simulation of shrinkage, warpage, and sink marks of

crystalline polymer injection moulded parts. These

methods were applied to predict the shrinkage, warpage,

and sink marks of crystalline polypropylene and

amorphous ABS for the plate cavity. Both the qualitative

results for the theoretical prediction correlated

sufficiently with the experimental data [8]. Other

researchers, Prashanta et al. [9] have focuses on the effect

of multi-walled carbon nanotube addition on shrinkage

and warpage properties of polypropylene injection

moulding products before and after annealing. While

Huang and Tai [10] in Journal of Materials Processing

Technology have determined the effective factors in the

warpage problem of an injection-moulded part with a thin

shell feature.

In the other hand, a research conducted by

Kramschuster et al. [11] have investigated the effects of

processing conditions on the shrinkage and warpage

behaviour of a box-shaped, polypropylene part using

conventional and microcellular injection moulding. Two

sets of 26-1

fractional factorial design of experiments were

employed to perform the experiments and proper

statistical theory was used to analyze the data. In this

research, after the injection moulding process reached

steady state, the results show that the supercritical fluid

content and the injection speed affect the shrinkage and

warpage of microcellular injection moulded parts the

most, whereas pack/hold pressure and pack/hold time

have the most significant effect on these defects [11].

The author also has carried out several researches

about injection moulding processing conditions by

utilizing injection moulding simulation with different

type of samples, material and responses. The inputs from

these projects were used as guidance for this project. An

attempt also has been made by optimising the test sample

made from polypropylene and clay, without using any

compatibilizer [12]–[15]. Therefore, this project was

conducted as the extensive version of previous research

conducted by the author.

III. METHODOLOGY

A. The Selection of Cavity Shape, Injection Moulding

Machine and Material.

The cavity shape selected in this study was a snap fit

product, as displayed in Fig. 1. The base and the cover

should be able to snap and fit together as a product. This

sample will be used to investigate the effects of injection

moulding parameters toward the quality of this sample

through practical injection moulding. The injection

moulding machine used in this project was JSW 75

Tonne E11 Plastic Injection Moulding Machine (Fig.2),

located at Material Processing Lab, School of Mechanical

and Aerospace, Nanyang Technical University, Singapore.

The material used in this research was Polypropylene

(PP)-Homopolymer Cosmoplene Y101H.

Figure 1. Snap fit samples for injection moulding.

Base Cover


2014 Engineering and Technology Publishing 155

Figure 2. JSW E11 75 tonne injection moulding machine.

B. Design of Experiment

Based on the Taguchi optimization method, four most

significant factors that affect part quality were selected.

Three levels of each parameter had been chosen for

analysis, as stated in Table I. Based on the value in Table

I, 'Level 1' indicate the lowest value of parameter, 'Level

2' means medium value and 'Level 3' means the highest

value of parameter selected. In this research, the (L934)

orthogonal was chosen as an orthogonal array because it

is suitable for three levels and four factors. The value for

the barrel temperature, holding pressure, injection

velocity and injection holding was obtained based on the

previous studies [15]. Table II shows the detail

orthogonal array for this experiment.

TABLE I: FACTOR AND LEVEL SELECTION

Factor Label Level 1 Level 2 Level 3

Barrel Temperature (ºC) BT 230 240 250

Holding Pressure (%) HP 10 15 20

Injection Velocity (%) IV 5 10 15

Injection Holding (s) IH 5 7 9

C. Signal to Noise (S/N) Ratio and Analysis of Variance

(ANOVA)

Signal to noise (S/N) ratio for mechanical properties

will obtained and optimum levels of the injection

parameters will determine through S/N values to achieve

maximum mechanical result. In this study, the smaller the

better quality characteristic is chosen to solve warpage

and shrinkage. The S/N values shall be calculated by

using statistical software which was Minitab 16. The

response graphs shall be generated through this software,

and the peak value for each factor shall be chosen as the

optimum setting to control the defects.

In this research, the aim of using the Analysis of

Variance (ANOVA) is to determine the significance of

process parameters on warpage and shrinkage. Based on

the calculation of S/N ratio, ANOVA value can be

obtained. The most significant parameter was determined

by calculating the percentages of pure sum. From the

analysis results, the higher percentages pure sum of factor

will contribute more affects from these factors to the

samples or product.

TABLE II: ORTHOGONAL ARRAY WITH SHRINKAGE AND WARPAGE

Trial No. BT HP IV IH W (mm) S

(%)

1 230 10 5 5 1.0683 0.0464

2 230 15 10 7 0.2467 0.0371

3 230 20 15 9 0.2933 0.0382

4 240 10 10 9 0.3083 0.0410

5 240 15 15 5 0.2783 0.0415

6 240 20 5 7 0.3367 0.0415

7 250 10 15 7 0.4583 0.0414

8 250 15 5 9 0.3583 0.0389

9 250 20 10 5 0.4200 0.0420

IV. RESULTS AND DISCUSSION

After the experiments have been carried out based on

the selected parameter setting in the orthogonal array,

values of average warpage and shrinkage was gained, as

stated in Table II. These values were measured for both

base and cover of the samples. Before the measurement

took place, a snap and fit test shall be conducted to ensure

that the samples were in good condition. The lowest

value obtained from this experiment was 0.2467 mm for

warpage and 0.0371 % for shrinkage.

Fig. 3 shows the main effect plots for S/N ratios,

specifically for warpage case. From this figure, the

optimum value of parameter setting that should be able to

reduce warpage is stated in Table III. By using this

setting, a validation test has been carried out and the

value of warpage was 0.2083 mm with 84% improvement.

250240230

10.8

9.6

8.4

7.2

6.0

201510

15105

10.8

9.6

8.4

7.2

6.0

975

BT

Me

an

of

SN

ra

tio

s

HP

IV IH

Main Effects Plot for SN ratiosData Means

Signal-to-noise: Smaller is better

Warpage

Figure 3. Main effect plot for SN ratio (Warpage)

TABLE III: THE OPTIMUM PARAMETER TO CONTROL WARPAGE

Factor BT HP IV IH Warpage Value

Value 240 15 10 9 0.2083

Level 2 2 2 3



Fig. 4 shows the Main Effect Plots for S/N ratios,

specifically for shrinkage case. As for the S/N ratios for

Shrinkage, the optimum value is displayed in Table IV.

The shrinkage value by using this optimum setting was

0.0211 %. This is 56% improvement based on the lowest

shrinkage value gained from previous settings in Trial 2.

The ANOVA test was applied to determine the influence

of each parameter in the designed experimental study.

The P (%) value or the pure summary value percentage

for each data was monitored. The result for ANOVA for

the snap fit samples can be summarized in the Table V

for warpage and Table VI for shrinkage.

250240230

28.2

28.0

27.8

27.6

27.4

201510

15105

28.2

28.0

27.8

27.6

27.4

975

BT

Me

an

of

SN

ra

tio

s

HP

IV IH

Main Effects Plot for SN ratiosData Means

Signal-to-noise: Smaller is better

Shrinkage

Figure 4. Main effect plot for SN ratio (Shrinkage)

TABLE IV: THE OPTIMUM PARAMETER TO CONTROL SHRINKAGE

Factor BT HP IV IH Shrinkage Value

Value 230 15 10 9 0.0211

Level 1 2 2 3

TABLE V: THE ANOVAS RESULT FOR WARPAGE

Factor f S V F S' P (%)

BT 2 0.0784 0.0392 0 0 15.34

HP 2 0.1722 0.0861 0 0 33.68

IV 2 0.1291 0.0646 0 0 25.26

IH 2 0.1314 0.0657 0 0 25.71

Total 8 0.5112 100.00

TABLE VI: THE ANOVAS RESULT SHRINKAGE

Factor f S V F S' P

(%)

BT 2 Pooled

BT 2 0.0784 0.0392 0 0 15.34

HP 2 2.16E-

05

5.17E-

07 1.00

2.06E-

05 35.57

IV 2 8.55E-

06

1.08E-

05 20.86

7.52E-

06 13.01

IH 2 2.66E-

05 4.27E-

06 8.26

2.56E-05

44.25

Pooled Error

0 1.03E-

06 7.17

Based on the results of ANOVA in Table V, the most

influential factor that affecting warpage was holding

pressure (HP), with 33.68% of the contribution, and

followed by injection holding (IH) with 25.71% of P

value. The weakest factor that contributes towards

warpage is barrel temperature with 15.34% of P value.

As for the ANOVA for shrinkage, the most influential

factor was injection holding, and then followed by

holding pressure. Barrel temperature has been pooled in

the calculated since it produced the weakest influence

towards shrinkage.

Based on [1], as holding pressure is increased, it will

force more material into mould cavity causing shrinkage

to be reduced. This statement was same from the analysis

result of this research. The entire significant factor which

is influent shrinkage was packing pressure.

According to [2], the quality of injection moulded part

is almost entirely determined by two processing

parameters, namely pressure and temperature, while the

injection velocity exerts only a limited influence. This

can be strengthened that the selection of parameters in

this research is appropriate to examine the quality of

injection moulded part especially for shrinkage and

warpage.

V. CONCLUSION

To summarize the findings, the optimum setting that

should be followed to control shrinkage and warpage in

producing a snap fit samples have been achieved. The

most influential factor, that affecting warpage is holding

pressure with 33.68% of the contribution, followed by

injection holding (IH) with 25.71% of P value. In the

other hand, injection holding with the contribution of

44.25% need to be closely monitored if we want to

reduce shrinkage and then followed by holding pressure.

The findings of this project shall be good enough to be

used as reference in producing similar product in future.

ACKNOWLEDGMENT

The authors would like to recognize the Ministry of

Higher Education (MOHE) Malaysia for the Fundamental

Research Grant Scheme (FRGS) under VOT 0750,

Nanyang Technical University (NTU), Singapore and

Universiti Tun Hussein Onn Malaysia (UTHM) for the

fund and facilities. Special thanks to Mr Tony Wee Tiew

Teck for providing good guidance in handling the

injection moulding machine during laboratory works.

REFERENCES

[1] M. P.Groover, Principle of Modern Manufacturing, 4th Edition, SI

Version, John Wiley & Sons (Asia) Pte Ltd., 2011. [2] F. Johannaber, Injection Molding Machine, 4th Edition, Hanser

Gardner Publication Inc., 2007, pp. 27

[3] B. Ozcelik, “Optimization of injection parameters for mechanical properties of specimen with weld line of polypropylene using

taguchi method," International Communications in Heat and Mass Transfer, vol. 38, no. 8, pp. 1067-1072, 2011.

[4] H. Oktem, T. Erzurumlu, and I. Uzman, “Application of Taguchi

optimization technique in determining plastic injection moulding process parameters for a thin-shell part,” Materials & Design, vol.

28, no. 4, pp. 1271-1278, 2005.



[8] R. Y. Chang and B. D. Tsaur, “Experimental and theoretical

studies of shrinkage, warpage, and sink marks of crystalline polymer injection molded parts,” Polymer Engineering & Science,

vol. 35, no. 15, pp. 1222-1230, 1995.

[9] K. Prashantha, J. Soulestin, M. F. Lacrampe, E. Lafranche, P.

Krawczak, G. Dupin, and M.Claes, “Taguchi analysis of shrinkage

and warpage of injection-moulded polypropylene/multiwall

carbon nanotubes nanocomposites,” Express Polym Lett, vol. 3, no. 10, pp. 630-638, 2009.

[10] M. C. Huang and C. C. Tai, “The effective factors in the warpage

problem of an injection-molded part with a thin shell feature,” Journal of Materials Processing Technology, vol. 110, no. 1, pp.

1-9, 2001.

[11] A. Kramschuster, R. Cavitt, D. Ermer, Z. Chen, and L.S Turng, “Quantitative study of shrinkage and warpage behavior for

microcellular and conventional injection molding,” Polymer

Engineering & Science, vol. 45, no. 10, pp. 1408-1418, 2005. [12] S. Hasan, M. H. Othman, and S. Rasli, “The effect of parameter

setting towards the processing of hinges test samples through cadmould 3D-F injection moulding simulation,” Applied

Mechanics and Materials, vol. 315, pp. 171-175, 2013.

[13] S. Shamsudin, S. Hasan, M. H. Othman, and M. N. Abd Rahman, “The effects of Injection moulding processing parameters and

mould gate size towards weld line strength,” Advanced Materials Research, vol. 488, pp. 801-805, 2012.

[14] M. H. Othman, S. Shamsudin, and S. Hasan, “The effects of

parameter settings on shrinkage and warpage in injection molding through cadmould 3D-F simulation and taguchi method,” Applied

Mechanics and Materials, vol. 229, pp. 2536-2540, 2012. [15] M. H. Othman, S. Hasan, W. N. A. Wan Muhammad, and Z.

Zakaria, “Optimising injection moulding parameter setting in

processing polypropylene-clay composites through taguchi method,” Applied Mechanics and Materials, vol. 271, pp. 272-276,

2013.

M. H.Othman was born at Malacca, 1978. He

obtained his first degree in B. Eng. Mechanics and Material Engineering, from Universiti

Kebangsaan Malaysia (UKM), Bangi, Malaysia

in year 2000. In year 2008, he acquire his second degree in M.Sc. Packaging Technology

from Loughborough University, United Kingdom. At present his is pursuing the third

degree which is PhD in Mechanical Engineering

at Universiti Tun Hussein Onn Malaysia (UTHM), Johor, Malaysia. He is currently working as a lecturer in Universiti Tun Hussein Onn

Malaysia (UTHM) from year 2004 until present. Before that he worked as a process engineer in Fine Pulse Sdn Bhd, Melaka, Malaysia from

year 2000 until 2004. During his service at UTHM, he had published

several journals such as:

1.

S. Shamsudin, S. Hasan, M. H. Othman, and M. N. Abd Rahman,

“The Effects of Injection Moulding Processing Parameters and Mould Gate Size towards Weld Line Strength”, Advanced

Materials Research, vol. 488, pp. 801-805, 2012.,

2.

M. H. Othman, S. Shamsudin, and S. Hasan, “The Effects of Parameter Settings on Shrinkage and Warpage in Injection

Molding through Cadmould 3D-F Simulation and Taguchi Method”, Applied Mechanics and Materials, vol. 229, pp. 2536-

2540, 2012.

3.

M.

H. Othman, S. Hasan, W. N. A. Wan Muhammad, and

Z.

Zakaria,

“Optimising Injection Moulding Parameter Setting in Processing Polypropylene-Clay Composites through Taguchi

Method”, Applied Mechanics and Materials,vol. 271, pp. 272-276, 2013.

His current research interests are about packaging technology and

automation, specifically in injection moulding of polymer

nanocomposites and hydraulics.

Mr. Mohd Hilmi is a graduate member of Board of Engineers Malaysia (BEM). He had won a gold prize at Seoul International Invention Fair in

year 2006.


2014 Engineering and Technology Publishing

[5] T. Urzurumlu and B. Ozcelik, "Minimization of Warpage and sink index in injection-molded thermoplastics parts using taguchi

optimization method," Materials & Design, vol. 27, no. 10, pp.

853-861, 2006.[6] N. M. Mehat and S. Kamaruddin, "Optimization of mechanical

properties of recycled plastic products via optimal processing parameter using the taguchi method,” Journal of Materials

Processing Technology, vol. 211, no. 12, pp. 1989-1994, 2011.

[7] N. M. Mehat and S. Kamaruddin "Quality control and design optimisation of plastic product using Taguchi method: a

comprehensive review." International Journal of Plastics

Technology, vol. 16, no. 2, pp. 194-209, 2012.

158

the effect of processing condition towards the quality of ... · the effect of processing condition...

Documents