investigation of mould design and process parameter …
TRANSCRIPT
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
INVESTIGATION OF MOULD DESIGN AND PROCESS PARAMETER
OPTIMISATION OF PLASTIC INJECTION MOULDING FOR THIN WALL
PART
AZNIZAM BIN AHMAD
A thesis submitted in
fulfillment of the requirement for the award of the
Degree of Master of Mechanical Engineering
TITLE
Faculty of Mechanical and Manufacturing Engineering
Universiti Tun Hussein Onn Malaysia
MAY 2019
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
iii
DEDICATION
Special thanks to my strength on their support and cares, father, mother, wife and
kids.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
iv
ACKNOWLEDGEMENT
First of all, thanks to Allah S.W.T for giving me the strength and chances in completing
this master thesis. In preparing this research report, I would like to express my sincere
appreciation and gratitude to my supervisor, Prof. Ir. Dr. Md. Saidin bin Wahab for his
guidance, critics and friendship along the journey to complete my study.
I would also like to thank to staff and lecturers in Universiti Tun Hussein Onn
Malaysia (UTHM) that have assisted me, their support and encouragement. May all
the good deeds that were done will be blessed by Allah S.W.T.
Last but not least, my greatest thanks from my deepest heart to my father,
Ahmad bin Ihsan, my mother Junaidah binti Sahib, my beloved wife Norasliza binti
Mohd Bisri, my kids Muhammad Faris, Muhammad Faiz and the rest of my family
member for their support. I just want them to know that I am very grateful to have
them whom always assisting me despite of many challenges that I had faced in
completing this research.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
v
ABSTRACT
In plastic injection moulding industries such as automotive, packaging and medical,
demands for thin wall parts increases for the reason of light weight, lower cycle time,
lower part cost and higher productivity. However, a lot of challenges faced by the
moulders since the mould and processing parameters are critical to produce good
quality of thin wall parts. This research describes the mould design and process
parameter aspects of thin wall part focusing on tubular shape The aim of the research
is to investigate the factors that influence the moulded part quality in terms of part
shrinkage and weight. The research begin with development of mould for a
polypropylene thin wall tubular part and followed by study on the effect of injection
moulding process parameter towards moulded part quality. In order to identify the
moulding parameters that influences the moulded part quality, Taguchi optimisation
method was employed in the research. Based on the obtained simulation result, the
preferred size of runner was diameter of 4 mm, gate size was 1 mm and the gate
number was 4 number for actual mould fabrication. On the effect of injection pressure,
the result shows that with increasing in injection pressure the part shrinkage reduced
and part weight increased. As for the effect of melt temperature, the result shows that
with increasing in melt temperature the part shrinkage increased and part weight
reduced. As for the optimisation, the result shows that temperature contributed
significantly to shrinkage and weight of moulded part. Mould temperature have
significant effect to outer diameter shrinkage while melt temperature have significant
effect to inner diameter shrinkage.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
vi
ABSTRAK
Dalam industri pengacuanan suntikan plastik seperti automotif, pembungkusan dan
perubatan, permintaan untuk komponen dinding nipis semakin meningkat disebabkan
oleh ringan, masa kitaran yang lebih rendah, kos yang lebih rendah dan produktiviti
yang lebih tinggi. Walau bagaimanapun, banyak cabaran yang harus dihadapi oleh
pihak industri kerana acuan dan parameter pemprosesan adalah rumit bagi
menghasilkan komponen dinding nipis yang berkualiti. Kajian ini menerangkan aspek
reka bentuk acuan dan parameter proses dalam proses pengacuan suntikan plastik
(PIM) untuk menghasilkan komponen tiub dinding yang nipis. Tujuan penyelidikan
dijalankan adalah untuk mengkaji faktor-faktor yang mempengaruhi kualiti komponen
yang terhasil dari segi pengecutan dan berat komponen. Penyelidikan bermula dengan
pembangunan acuan untuk komponen tiub dinding polipropilena nipis dan diikuti
dengan kajian mengenai kesan parameter proses pengacuanan suntikan terhadap
kualiti komponen yang dihasilkan. Untuk mengenalpasti parameter pengacuanan yang
mempengaruhi kualiti komponen yang dihasilkan, kaedah pengoptimuman Taguchi
telah digunakan dalam penyelidikan. Berdasarkan hasil yang diperoleh, saiz pelayar
yang dipilih adalah 4 mm, saiz pintu adalah 1 mm dan bilangan pintu adalah 4 untuk
pembuatan acuan sebenar. Bagi kesan tekanan suntikan, hasilnya menunjukkan
bahawa dengan peningkatan tekanan suntikan, pengecutan komponen berkurangan
manakala berat komponen meningkat. Untuk kesan suhu leburan pula, hasilnya
menunjukkan bahawa dengan peningkatan suhu pencairan, pengecutan komponen
meningkat dan berat komponen berkurangan. Bagi pengoptimuman, dapatan
menunjukkan bahawa suhu menyumbang dengan ketara kepada pengecutan dan berat
komponen acuan. Suhu acuan mempunyai kesan ketara kepada pengecutan diameter
luar manakala suhu pencairan mempunyai kesan ketara kepada pengecutan diameter
dalaman.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
vii
CONTENTS
TITLE i
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
ABSTRAK vi
CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xiii
LIST OF SYMBOLS AND ABBREVIATIONS xvi
LIST OF APPENDICES xix
CHAPTER 1 INTRODUCTION 1
1.1 Background of study 1
1.2 Problem statement 2
1.3 Objectives 4
1.4 Scope of study 4
1.5 Thesis outline 5
CHAPTER 2 LITERATURE REVIEW 6
2.1 Introduction 6
2.1.1 Mould for injection moulding 6
2.1.2 Simulation for injection moulding 11
2.1.3 Injection moulding process parameter 12
2.1.4 The effect of injection moulding process
parameter
13
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
viii
2.1.5 Optimisation in injection moulding 16
2.2 Polymer material for injection moulding 19
2.3 Thin wall part in injection moulding 22
2.4 Summary 25
CHAPTER 3 METHODOLOGY 26
3.1 Introduction 26
3.2 Development of mould 27
3.2.1 Runner size 33
3.2.2 Gate size 34
3.2.3 Gate number 35
3.2.4 Assembly and evaluation of mould design 36
3.3 Injection moulding process parameter 39
3.3.1 Short shot and injection pressure
comparison
41
3.3.2 The effect of process parameter on part
shrinkage
47
3.3.3 The effect of process parameter on part
weight
49
3.4 Optimisation of injection moulding process
parameter
51
3.4.1 Quality factor evaluation on part
shrinkage and part weight
55
3.4.2 Signal to noise ratio 56
3.4.3 Optimised injection moulding process
parameter
57
3.5 Summary 58
CHAPTER 4 RESULTS AND DISCUSSION 59
4.1 Introduction 59
4.2 Development of mould outcomes 59
4.2.1 Runner size result (simulation) 61
4.2.2 Gate size result (simulation) 63
4.2.3 Gate number result (simulation) 65
4.2.4 Assembly and evaluation of actual mould 67
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
ix
design result
4.3 Injection moulding process parameter outcomes 69
4.4.1 Short shot and injection pressure
comparison result
69
4.3.2 The effect of process parameter on part
shrinkage result
72
4.3.3 The effect of process parameter on part
weight result
74
4.4 Optimisation of injection moulding process
parameter outcomes
76
4.4.1 Part shrinkage result 76
4.4.2 Part weight result 78
4.4.3 Signal to noise ratio result 79
4.4.4 Optimised injection moulding process
parameter result
86
4.5 Summary 87
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS 88
5.1 Conclusion 88
5.2 Recommendations 89
5.2.1 Mould design and development 89
5.2.2 Injection moulding process parameter 90
5.2.3 Optimisation of process parameter 90
5.2.4 Polymer material 90
REFERENCES 91
APPENDIX 99
VITA 121
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
x
LIST OF TABLES
2.1 Simulation software used by previous researches 11
2.2 Process parameter in injection moulding used by previous
researches
13
2.3 Previous researches study involved on mould temperature 14
2.4 Previous researches study involved on melt temperature 15
2.5 Previous researches study involved on injection time 15
2.6 Previous researches study involved on injection pressure 16
2.7 Design of experiment (DOE) method used by the previous
researches
17
2.8 ANOVA method used by previous researches 18
2.9 Hypothesis of process parameter for shrinkage response
(Hindle, 2018)
19
2.10 Differences in homopolymer and copolymer (Charles &
Carraher, 2012)
21
2.11 Advantages and disadvantages of polypropylene (Maddah,
2016)
21
2.12 Specification of Titanpro® PM803 (M-Base Engineering,
2015)
21
2.13 Thermoplastic material in injection moulding used by
previous researches
22
2.14 Maximum (L/t) ratio for few common polymer materials
(Mastip, 2015)
23
2.15 Definition of the thin wall by previous researches 24
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xi
2.16 Recommended wall thickness for the polymer material
(Berlin, 2017)
25
3.1 List of considered polymer materials 31
3.2 Typical properties of polypropylene polymer material used
in the experiment (M-Base Engineering, 2015)
32
3.3 Key characteristics of typical mould material (Beaumont et
al., 2002)
33
3.4 Specification for plastic injection mould 33
3.5 Factors related to runner size 34
3.6 Factors related to gate size 35
3.7 Factors related to gate number 35
3.8 Initial Processing Parameter for the simulation of moulding 40
3.9 Typical polymer material properties polypropylene
Titanpro® PM803 (Titan, 2017)
40
3.10 Short shot comparison process parameter 42
3.11 Injection pressure comparison process parameter 43
3.12 Comparison of various pressure transducers (Rauwendaal,
2000)
44
3.13
Effect of injection pressure towards part shrinkage process
parameter
47
3.14 Effect of melt temperature towards part shrinkage process
parameter
47
3.15 Effect of injection pressure towards part weight process
parameter
50
3.16 Effect of melt temperature towards part weight process
parameter
50
3.17 Factor and level selection for part shrinkage and part
weight
52
3.18 Orthogonal array for part shrinkage and part weight 52
3.19 Standard specifications of Matsui mould temperature
controller
53
3.20 List of polymer material for mould temperature controller
setting
54
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xii
3.21 Quality characteristics and the formula (Michaeli &
Wolters, 2000)
56
4.1 Result of melt flow rate for considered polymer materials 60
4.2 Result of factors related to runner size 61
4.3 Result of factors related to gate size 63
4.4 Result of factors related to gate number 65
4.5 Comparison of the flow length between simulation and
experiment at different injection time
70
4.6 Simulation and experiment shrinkage result 77
4.7 Comparison of shrinkage result between experimental and
simulation
78
4.8 Difference percentage between simulation and
experimental of part weight
79
4.9 The S/N ratio value for inner diameter shrinkage at 37.50
mm
80
4.10 The S/N ratio value for outer diameter shrinkage at 37.50
mm
80
4.11 The optimum parameter to control inner diameter
shrinkage at 37.50 mm
81
4.12 The optimum parameter to control outer diameter
shrinkage at 37.50 mm
82
4.13 ANOVA result for inner diameter shrinkage at 37.50 mm 83
4.14 ANOVA result for outer diameter shrinkage at 37.50 mm 83
4.15 The S/N ratio value for part weight 84
4.16 The optimum parameter to control part weight 85
4.17 ANOVA result for part weight 85
4.18 Confirmation test result for inner diameter shrinkage at
37.50 mm
86
4.19 The confirmation test result for outer diameter shrinkage at
37.50 mm
86
4.20 Margin error in experimental of ID and OD shrinkage 86
4.21 Confirmation test result for part weight 87
4.22 Margin error in experimental of part weight 87
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xiii
LIST OF FIGURES
2.1 A plastic injection moulding system (Rosato & Rosato,
2000)
7
2.2 Two plate cold runner mould system (Clara, 2006) 10
2.3 The position of stripper in a mould (Misumi, 2018) 10
2.4 The processing effects on thermoplastic polymer (IMould,
2009)
20
2.5 Thin wall injection flow (Mastip, 2015) 24
3.1 Overview of the work flow process for the research 27
3.2 Cross section drawing of cup in AutoCAD 29
3.3 A cup part modeling in SolidWorks 29
3.4 Part in 3D printing process using UP Mini 3D Printer 30
3.5 Parting line for cup 36
3.6 Location of the edge gate 37
3.7 (a) Stripper plate (b) Stripper plate in assembly condition 37
3.8 (a) 3D model of cavity insert (b) 3D model of core insert 38
3.9 (a) 3D model cooling channel in cavity insert case (b) Hole
(in red) for brass baffle in core insert
39
3.10 Location of pressure reading in mould 42
3.11 Kistler 6189 pressure temperature sensor 44
3.12 Kistler 6182 pressure sensor 44
3.13 Kistler 5155A charge amplifier 45
3.14 National Instrument NI cDAQ 9174 45
3.15 National Instrument NI 9125 analog input module 45
3.16 Arrangement of the sensor and other peripherals at
injection moulding machine
46
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xiv
3.17 Fanuc roboshot 50 ton plastic injection moulding machine 44
3.18 Volumetric part shrinkage based on simulation result 48
3.19 CMM Mitutoyo Crysta Apex S544 49
3.20 Graph of part weight from the simulation result 51
3.21 Digital weighing scale 51
3.22 Matsui mould temperature controller model GMCH-55A 53
3.23 Inner diameter measurement by CMM 55
4.1 Melt flow rate vs polymer material 60
4.2 Graph of volumetric shrinkage vs runner size 61
4.3 Graph of shear stress vs runner size 62
4.4 Graph of part weight vs runner size 62
4.5 Graph of volumetric shrinkage vs gate size 63
4.6 Graph of shear stress vs gate size 64
4.7 Graph of part weight vs gate size 64
4.8 Graph of volumetric shrinkage vs gate number 65
4.9 Graph of shear stress vs gate number 66
4.10 Graph of part weight vs gate number 66
4.11 Actual stripper plate after machining 67
4.12 (a) Cavity insert fabricated in NAK80 (b) Core insert
fabricated in NAK80
67
4.13 Cavity insert during machining 68
4.14 Complete assembly of cavity side plastic injection mould 68
4.15 Complete assembly of core side plastic injection mould 69
4.16 Graph of flow length between simulation and experiment 70
4.17 Graph of injection pressure inside the mould vs time 72
4.18 Graph part shrinkage vs injection pressure 73
4.19 Graph part shrinkage vs melt temperature 74
4.20 Graph part weight vs injection pressure 75
4.21 Graph part weight vs melt temperature 76
4.22 Location of part shrinkage measurement on moulded part 77
4.23 Main effect plot of S/N ratio for inner diameter shrinkage
at 37.50 mm
81
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xv
4.24 Main effect plot of S/N ratio for outer diameter shrinkage
at 37.50 mm
82
4.25 Main effect plot of S/N ratio for part weight 85
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xvi
LIST OF SYMBOLS AND ABBREVIATIONS
AISI - American Iron Steel Institute
ADC - Analog digital converter
ANOVA - Analysis of variance
ANN - Artificial neural network
BPNN - Back propagation neural network
Bhd. - Berhad
cc/s - Centimetre cubic per second
CAD - Computer Aided Design
CNC - Computer numerical control
DAQ - Data acquisition system
°C - Degree celsius
D - Depth
DOE - Design of experiment
Ø - Diameter
DMLS - Direct metal laser sintering
EDM - Electrical discharge machining
EOF - End of filling
EOP - End of packing
GN - Gate number
GS - Gate size
GA - Genetic algorithm
g/10 min - Gram per 10 minute
g/cm2 - Gram per centimetre square
H - Height
HDPE - High density polyethylene
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xvii
IP - Injection pressure
IT - Injection time
ID - Inner diameter
kg - Kilogram
kg/cm2 - Kilogram per centimetre square
kg/m3 - Kilogram per meter cubic
kW - Kilowatt
L/t - Length per thickness
L - Litre
L/min - Litre per minute
LDPE - Low density polyethylene
LKM - Lung Kee Group
M - Malaysia
MSD - Mean square deviation
MT - Melt temperature
mm/s - Millimetre per second
MoT - Mould temperature
NI - National Instruments
NA - Not available
OD - Outer diameter
PSE - Parametric sampling evaluation
% - Percent
PA - Polyamide
PBT - Polybutylene terephthalate
PC - Polycarbonate
kN - Polycarbonate
PEEK - Polyether ether ketone
PE - Polyethylene
PMMA - Polymethyl methacrylate
POM - Polyoxymethylene
PPO - Polyphenylene oxide
PPS - Polyphenylene sulfide
PS - Polystyrene
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xviii
PVC - Polyvinyl chloride
RSM - Response surface methodology
RS - Runner size
Sdn. - Sendirian
3D - Three dimensional
UV - Ultraviolet
V - Volts
wt - Weight
W - Width
ABS - Acrylonitrile butadiene styrene
CMM - Coordinate measuring machine
dB - Decibel
DF - Degree of freedom
g - Gram
MPa - Megapascal
mm - Millimetre
OA - Orthogonal array
PIM - Plastic injection moulding
PP - Polypropylene
s - Second
S/N - Signal to noise
SS - Sum of square
UTHM - Universiti Tun Hussein Onn Malaysia
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
xix
LIST OF APPENDICES
APPENDIX TITLE PAGE
A Product drawing 99
B Assembly drawing cavity side 100
C Assembly drawing core side 101
D Assembly drawing front side 102
E Simulation results of runner size (2, 3 & 4 mm) 103
F Simulation results of gate size (0.50, 0.75 & 1.00
mm)
106
G Simulation results of gate number (3, 4 & 5) 109
H Simulation and experiment data for part shrinkage 112
I Simulation and experiment data for part weight 116
J Simulation and experiment data for optimisation
part shrinkage
118
K Simulation and experiment data for optimisation
part weight
120
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
CHAPTER 1
INTRODUCTION
1.1 Background of study
In plastic injection moulding industries such as automotive, packaging and medical,
demands for thin wall parts increases for the reason of light weight, lower cycle time,
lower part cost and higher productivity. However, a lot of challenges faced by the
moulders since the mould and processing parameters are critical to produce good
quality of thin wall parts. Thin wall injection moulding is defined as moulding of part
that have a maximum thickness of wall of 1 mm and a flow length to wall thickness
ratio (L/t) ratio of 100:1 or higher. The thickness of the wall cannot exceed 1 mm and
a minimum part surface area of 50 cm2 (Selden, 2000).
This study focuses on the moulded part that has a nominal wall thickness of 1
mm. Thin wall moulded parts are lighter, more compact, less expensive and faster
cycle time because of fast cooling. The injection moulding process needs appropriate
setting parameters especially if the plastic part wall thickness reduced or become
thinner (Rosato & Rosato, 2000). Hence, the demand from the industry for plastic
injection moulding techniques that able to produce plastic parts with thin wall
characteristics becomes higher.
A proper processing parameters selection for the injection moulding process
becomes more complicated for the applications that relevant to thin wall parts.
Processing of injection moulding at lower temperature make it difficult for the polymer
to flow smoothly into the mould cavities and often leads to an inconsistent distribution
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
2
of residual stresses, volumetric shrinkage and warpage in moulded parts especially in
thin wall parts.
According to Huang and Tai (2001), thin wall moulded parts requires fast
filling to prevent solidification of the plastic before the cavities were completely filled.
Processing parameters such mould temperature, packing time, packing pressure,
melting temperature and injection time were important factors on the surface quality
of the thin moulded plastic parts. The thickness of the moulded part should be thick
enough for the polymer material to fulfil its function but also thin enough to benefit in
terms of cycle time and cost. Thick walls were uneconomical because consume more
polymer material, increase the risk of moulded part defects and extends the cycle time
by requiring longer cooling time.
1.2 Problem statement
Plastic injection moulding for thin wall component become common due to
commercial and environmental concerns. The processing of thin wall component
facing many difficulties thus systematic investigation is required to study on machine
performance, mould design requirement, moulding characteristics, plastic injection
moulding simulation, part quality and part design. The combination of various polymer
material, intricate moulding geometry and recurring process condition contributed to
moulded part quality issues such as flow mark, sink marks, warpage, shrinkage and
varies in moulded part weight in high speed and high pressure injection moulding. The
aspects of design, operation and control of thin wall injection moulding is vital to
produce good quality part thus reduce the process cost (Xu, 2004).
According to Martins et al., (2006) during injection moulding process, polymer
material solidified and shrink towards core of the mould. For the case of box or tubular
formed parts, the shrinkage is constrained by the mould. Furthermore, part weight
control and dimensional stability test methods are inexpensive, fast and easy
techniques that can be performed at moulding site. Most of the time, weight control is
chosen over dimensional method due to weight difference can be more obvious than
the part dimensions. If the moulded part shows wide variation in term of part weight,
it indicates that the process of moulding or machine tolerances need an adjustment. In
general, stabilising the part weight shows stabilised the moulding process
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
3
(Nagahanumaiah & Ravi, 2009). The part weight data can also help in checking other
defects in moulding such air traps and voids or other nonconformity from filling rate
of the cavity in the mould. Therefore, the control in part weight can be associated to
strength of the moulded part (Ong et al., 2001). Dimensional stability of the moulded
part mostly influenced by shrinkage which the factors contributed by mould thermal
properties, polymer polymerization, injection and holding pressure. Maintaining the
part dimension stability is crucial for the product assembly and interchangeability
(Vlachopoulos & Strutt, 2003).
In regards of mould design, gate design for thin wall injection moulding have
been studied by Shen et al., (2008). The study focused on PC + ABS polymer material
and the finding stated that two gate location arranged oppositely was the most suitable
among others configuration. The study was conducted using plastic injection moulding
simulation software. According to Dassault Systemes (2017), the runner system from
moulded part is cut from the cavity at the gate after ejection process. A small gate
produced a visible small mark on the moulded part. Polymer material can be damaged
if the shear stress or shear rate exceed a critical value. Generally, the high shear rate
occurred at gate locations due to the polymer material flow through the small opening
of the gate. The defect is known as gate blush that can be seen by a visible mark at the
gate position. Size and location of gating system have influence on pressure loss and
heat loss of the polymer material melt through the gating system in the process of
injection and gate design is vital (Zhu et al., 2011).
There is important relationship between process parameter and the quality of
moulded part in injection moulding activities. Inappropriate setting of process
parameter caused defects on moulded part such as warpage, shrinkage, sink mark and
residual stress. However, the optimisation of relevant process parameter can improve
the product quality hence prolong the machine life and reduce the production cost.
Therefore, the result of optimised parameter is extremely important (Hassan, 2013).
In response to this matters, the research was conducted to investigate the mould
design aspect and influence of process parameter towards the moulded part quality
particularly on part shrinkage and part weight. The selected experimental process
parameter result was also compared with plastic injection moulding simulation
software to see correlation of both method.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
4
1.3 Objectives
The objectives are set based on the aim of the research as below:
i. To design and evaluate a gating system for tubular thin wall part towards shear
stress, shrinkage and part weight.
ii. To investigate the effect of processing parameters on part shrinkage and part
weight.
iii. To optimise the process parameter of injection moulding towards part
shrinkage and part weight.
It is expected that through this research, various finding from the experimental results
are able to benefit the plastic injection mould industry to make appropriate judgment
in identifying critical factor start from plastic part and mould design, to set initial
moulding processing parameters and optimising the process. The application of plastic
injection moulding simulation software is really essential to assist the moulding
industries to expedite deliver product from design stage to mass production.
1.4 Scope of study
There are several scopes of study in this research. The scopes are:
(i) The Polypropylene (PP) polymer material used in this research was a semi-
crystalline thermoplastic homopolymer Titanpro® PM803, from Lotte
Chemical Titan.
(ii) The 2D drawing of the part and mould components was designed and drawn
using AutoCAD.
(iii) The solid model of the part and mould components was developed using
SolidWorks.
(iv) The plastic injection moulding simulation software used was Solidworks
Plastics.
(v) Study focus on injection moulding essential process parameter of mould
temperature, melt temperature, injection time and injection pressure.
(vi) The injection moulding machine to produce samples in this study was FANUC
ROBOSHOT α-S50iA which have clamping force 500 kN located at Modern
Manufacturing Technology Workshop, UTHM Pagoh Campus.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
5
(vii) The part profile to produce the sample was a tubular shape of 45 mm in height
and diameter of 35 mm with uniform wall thickness of 1 mm.
(viii) The Taguchi method was used to get the optimal moulding parameter for
Polypropylene (PP) polymer material.
(ix) The part measurement was done using CMM Mitutoyo Crysta Apex S544
located at Measurement Technology (Metrology) Laboratory, UTHM Pagoh
Campus.
1.5 Thesis outline
In this research, the mould for thin wall part for plastic injection moulding process was
developed. The plastic injection moulding simulation software namely SolidWorks
Plastics was employed to analyse the critical plastic part mould design in regards of
ease of fill, fill time, volumetric shrinkage at end of packing, shear stress at end of fill
and part weight. At mould design stage, the other design parameter namely runner size,
gate size and gate number were evaluated. For initial processing condition setting, the
information from the SolidWorks Plastics were obtained in regards of mould
temperature, melting temperature, injection time and injection pressure. During
processing condition optimisation stage, the Minitab software was applied to obtain
the optimised setting towards part shrinkage and part weight.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This chapter reviews the previous research that related to the injection mould design
and process parameter optimisation for thin wall part. The processing parameter is
intended to be used as a guideline only for designers and moulders for plastic injection
moulding process. The previous research findings about thin wall plastic moulded part,
application of plastic injection moulding simulation software and the optimisation
condition of injection moulding processing were included in this chapter.
2.1.1 Mould for injection moulding
Injection moulding is a major part of the plastic industry and massive business
worldwide, consuming approximately 32 wt percent of all plastic. It is in the second
place to extrusion, which consumes approximately 36 wt percent (Rosato & Rosato,
2000). The injection moulding process consists of melting of polymer and then
injected into the cavities of the mould. The moulded part is ejected from the mould
after reaching the ejection temperature. Thus, the main phases of the injection
moulding process are injection, packing, cooling and part ejection. Among those
mentioned process, part cooling takes up 50 to 80 percent of the cycle time (Masood
& Trang, 2006). The amount of time in the injection and packing phases is low and
cannot be reduced much further. However, because cooling time can be more than
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
91
REFERENCES
Abeykoon, C., Martin, P. J., Li, K., Kelly, A. L., Brown, E. C., & Coates, P. D. (2014).
Melt temperature consistency during polymer extrusion.
Ahamed, A. R., Dawood, A. K. S., & Karthikeyan, R. (2013). Designing and
Optimizing the parameters which affect the molding process using design of
experiment, 1, 116–122.
Al-Refaie, A., & Li, M.-H. (2011). Optimizing the performance of plastic injection
molding using weighted additive model in goal programming. International
Journal of Fuzzy System Applications, 1, 43–54.
Altan, M. (2010). Reducing shrinkage in injection moldings via the Taguchi , ANOVA
and neural network methods. Materials and Design, 31, 599–604.
Amran, M. A. M., Idayu, N., Faizal, K. M., Sanusi, M., Izamshah, R., & Shahir, M.
(2016). Part weight verification between simulation and experiment of plastic part
in injection moulding process. IOP Conference Series: Materials Science and
Engineering, 160, 012016.
Amran, M., Salmah, S., Marjom, Z., Al-amani, U., Izamshah, R., Abdullah, Z., &
Sanusi, M. (2014). Warpage analysis verification between simulation and
experimental of dumbbell plastic part in the injection moulding process.
Azrin, A., & Azuddin, M. (2017). Study of the Effects of injection molding parameter
on weld line formation. Procedia Engineering, 8, 663–672.
Barzegari, M. R., & Rodrigue, D. (2009). The effect of injection molding conditions
on the morphology of polymer structural foams.
Beaumont, J. P., Nagel, R., & Sherman, R. (2002). Successful injection molding.
Hanser Publishers.
Berlin, N. (2017). Essential tips for designing a part for injection molding.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
92
Bhalerao, S. P., Badgujar, T. Y., & Mahajan, D. R. (2017). Experimentation and
optimization of injection moulding process parameter through Taguchi method
and mould flow analysis, 51, 97–105.
Bryce, B. D. M. (2018). Controlling Shrinkage, 1–3.
Caren, S. (1993). Prehardened mold steels offer machinability and weldability.
Charles, E., & Carraher, J. (2012). Introduction to polymer chemistry (3rd ed.). CRC
Press.
Chen, C. P., Chuang, M. T., Hsiao, Y. H., Yang, Y. K., & Tsai, C. H. (2009).
Simulation and experimental study in determining injection molding process
parameters for thin-shell plastic parts via design of experiment analysis. Expert
Systems with Applications, 36, 10752–10759.
Chen, S. C., Chen, H. L., & Hsu, P. M. (2008). Effect of molding condition on
mechanical properties of injection molded nylon 6-clay nanocomposites. Journal
of Reinforced Plastics and Composites, 27, 1381–1395.
Chen, W., Wang, M., & Chen, C. (2009). An integrated parameter optimization system
for MISO plastic injection molding, 501–511.
Clara, S. (2006). Machine Components.
Creative Mechanisms Staff. (2016). Everything you need to know about
polypropylene (PP) plastic.
Daido, S. (2016). Plastic mold steels: NAK80 - general design guidelines.
Dang, X. (2014). General frameworks for optimization of plastic injection molding
process parameters. Simulation Modelling Practice and Theory, 41, 15–27.
Dar, U. A., Xu, Y. J., Zakir, S. M., & Saeed, M.U. (2017). The Effect of injection
molding process parameters on mechanical and fracture behavior of
polycarbonate polymer. Journal of Applied Polymer Science, 134, 1–9.
Dassault Systèmes S.A. (2017). SolidWorks plastics feature matrix.
Deng, W.J., Chen, C.T., Sun, C.H., Chen, W.C., & Chen, C.P. (2008). An effective
approach for process parameter optimization in injection molding of plastic
housing components. Polymer-Plastics Technology and Engineering, 47, 910–
919.
Evans, J. R. G. (1989). The control of sprue solidification time in ceramic injection
moulding, 24, 840–848.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
93
Farotti, E., & Natalini, M. (2018). Injection molding. Influence of process parameters
on mechanical properties of polypropylene polymer. A first study. Procedia
Structural Integrity, 8, 256–264.
Fei, N. C., Mehat, N. M., & Kamaruddin, S. (2013). Practical applications of Taguchi
method for optimization of processing parameters for plastic injection moulding:
A retrospective review, 2013, 1–11.
Feldmann, M. (2016). The effects of the injection moulding temperature on the
mechanical properties and morphology of polypropylene man-made cellulose
fibre composites. Composites Part A: Applied Science and Manufacturing, 87,
146–152.
Fuh, J. Y., Zhang, Y. F., Nee, A. Y., & Fu, M. W. (2004). Computer aided injection
mold design and Manufacture. Marcel Dekker.
Goff, J. (2013). Injection molding of thermoplastic materials. Springer Science &
Business Media.
Guerrier, P., Tosello, G., & Hattel, J. H. (2015). Analysis of cavity pressure and
warpage of polyoxymethylene thin walled injection molded parts : experiments
and simulations, 110006, 1–6.
Hassan, H. (2013). An experimental work on the effect of injection molding
parameters on the cavity pressure and product weight. International Journal of
Advanced Manufacturing Technology, 67, 675–686.
Henri, J., Guerrier, P., Tosello, G., & Hattel, J. H. (2014). Analysis of cavity pressure
and warpage of polyoxymethylene thin walled injection molded parts :
experiments and simulations.
Hindle, C. (2018). Polypropylene (PP).
Huang MC, & Tai CC. (2001). The effective factors in the warpage problem of an
injection-molded part with a thin shell feature. 1-9.
Hussin, R., Mustafa, M. ., Annuar, A. ., Azmi, H., Zakaria, M. ., & Khalil, A. N. .
(2015). An optimization of shrinkage in injection molding parts by using Taguchi
method. Journal of Advanced Research in Applied Mechanics, 10, 1–8.
Ibrahim, M. H. I., Manaff, M. H. A., Othman, M. H., Mustafa, N., Masrol, S. R., &
Rafai, N. H. (2014). Optimisation of processing condition using Taguchi method
on warpage for HDPE-clay composite. Applied Mechanics and Materials, 660,
28–32.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
94
IMould. (2009). Plastic injection mould molecular weight and mechanical properties.
Inamdar, D. N., Chiniwalar, G. V., & Naik, G. A. (2016). Design and fabrication of
single-cavity injection mold using hot runners and direct hot tip gates. Journal of
Advances in Science and Technology Science & Technology, 12, 524–533.
Jae, G. W. (2014). Optimization of plastic injection molding process parameters for
manufacturing a brake booster valve body. Materials and Design, 56, 313–317.
Kamaruddin, S., Khan, Z. A., & Foong, S. H. (2010). Application of Taguchi method
in the optimization of injection moulding parameters for manufacturing products
from plastic blend. International Journal of Plastics Technology, 14, 152–166.
Kamaruddin, S., Khan, Z. A., & Wan, K. S. (2004). The use of the Taguchi method in
determining the optimum plastic injection moulding parameters for the
production of a consumer product, 98–110.
Kannakumar, K., & Jithin, K. (2017). Plastic flow analysis & simulation of automobile
brake light lens with optimum injection mold design. International Research
Journal of Engineering and Technology (IRJET), 4, 2876–2880.
Kapila, A., Singh, K., Arora, G., & Agarwal, N. (2015). Effect of varying gate size on
the air traps in injection molding, 5, 161–166.
Khoirul, L., Miftakhul, N., Budiyantoro, C., Budi, M., Rahman, N., Mesin, T.,
Yogyakarta, D. I. (2017). Desain dan optimasi injection mold sistem slider pada
produk preform stick T15. Jurnal Rekayasa, 8, 155–165.
Kr Dwiwedi, A., Kumar, S., Noor Rahbar, N., & Kumar, D. (2015). Practical
application of Taguchi method for optimization of process parameters in injection
molding machine for PP material. International Research Journal of Engineering
and Technology (IRJET), 2.
Kurt, M., Kamber, O. S., Kaynak, Y., Atakok, G., & Girit, O. (2009). Experimental
investigation of plastic injection molding : Assessment of the effects of cavity
pressure and mold temperature on the quality of the final products. Materials and
Design, 30, 3217–3224.
Lal, S. K., & Vasudevan, H. (2013). Optimization of injection moulding process
parameters in the moulding of low density polyethylene (LDPE). International
Journal of Engineering Research and Development, 7, 35–39.
Lee, K., & Lin, J. C. (2013). Optimization of injection molding parameters for LED
lampshade. Transactions of the Canadian Society for Mechanical Engineering,
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
95
37, 313–323.
Lo, C. (2016). Analysis of injection molding for computer cooling fans by Taguchi
method and grey relational analysis. Mathematics Subject Classification, 15,
4199–4211.
Lopez, A., Aisa, J., Martinez, A., & Mercado, D. (2016). Injection moulding
parameters influence on weight quality of complex parts by means of DOE
application: Case study. Measurement.
M-Base Engineering. (2015). Datasheet Titanpro® PM803.
Maddah, H. A. (2016). Polypropylene as a promising plastic : A Review, 6, 1–11.
Maldanis, R. (2015). Injection molding : Know your resin choices, 1–9.
Martins, L. C., Ferreira, S. C., Martins, C. I., & Pontes, A. J. (2006). Study of ejection
forces in injection moulding of thin-walled tubular mouldings, 281–286.
Masood S. H., & Trang N. (2006). Thermal analysis of conformal cooling channels in
injection mouldingtle. Proceedings of the 3rd BSME-ASME International
Conference on Thermal Engineering.
Mastip. (2015). Thin wall moulding. In Mastip Technology Limited (pp. 1–2).
Mathivanan, D., Nouby, M., & Vidhya, R. (2010). Minimization of sink mark defects
in injection molding process – Taguchi approach, 2, 13–22.
Mehat, N. M., & Kamaruddin, S. (2011). Multi-response optimization of injection
moulding processing parameters using the Taguchi method. Polymer-Plastics
Technology and Engineering, 50, 1519–1526.
Menges, G., Michaeli, W., & Mohren, P. (2000). How to make injection molds (3rd
Edition). Hanser Publishers.
Michaeli, G., & Wolters, V. (2000). Training in plastic technology. Hanser Gardner
Publication (2nd Edition).
Minh, P. S., Minh, T., & Uyen, T. (2014). Numerical study on flow length in injection
molding process with high-speed injection molding, 2, 58–63.
Misumi. (2018). Ejecting stripper plate structure.
Mysore, G. (2018). Mould theory (pp. 1–96).
Nagahanumaiah, & Ravi, B. (2009). Effects of injection molding parameters on
shrinkage and weight of plastic part - Produced by DMLS mold. Rapid
Prototyping Journal, 15, 179–186.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
96
Nust, P., & Nust, P. (2016). Optimization of injection molding process for sink marks
reduction by integrating response surface design methodology & Taguchi
approach. Journal of Quality and Technology Management, XII, 45–79.
Ong, N.-S., Lee, H. L., & Parvez, M. A. (2001). Influence of processing conditions
and part design on the gas-assisted injection molding process. Advances in
Polymer Technology, 20, 270–280.
Ozcelik, B., & Erzurumlu, T. (2006). Comparison of the warpage optimization in the
plastic injection molding using ANOVA, neural network model and genetic
algorithm. Journal of Materials Processing Technology, 171, 437–445.
Pareek, R., & Bhamniya, J. (2013). Optimization of injection moulding process using
Taguchi and ANOVA, 4.
Paul W. Britton. (2012). Three considerations for mold steel selection. Retrieved from
http://www.moldmakingtechnology.com/articles/three-considerations-for-mold-
steel-selection
Polymers, E. (2018). Injection moulding guidelines.
Rauwendaal, C. (2000). SPC: Statistical process control in injection molding and
extrusion. Hanser Publishers.
Ravi, B. (2009). Effects of injection molding parameters on shrinkage and weight of
plastic part produced by DMLS mold, 3, 179–186.
Redwood, P. (2017). Amorphous vs. semi-crystalline thermoplastics.
Rosato, D. V., Marlene G., R., & D. V., R. (2000). Concise encyclopedia of plastics.
Springer Science & Business Media.
Rosato, D. V, & Rosato, M. G. (2000). Injection molding handbook. Kluwer Academic
Publisher.
Selden, R. (2000). Thin wall molding of engineering plastics – A literature survey.
Sheharyar, M. (2009). Injection molding simulation analysis of car rim using
SolidWorks ® Plastics, 1–7.
Shen, Y. K., Liu, J. J., Chang, C. T., & County, T. (2002). Comparison of the results
for semisolid and plastic, 29, 97–105.
Shen, Y., Wu, C., Yu, Y., & Chung, H. (2008). Analysis for optimal gate design of
thin-walled injection molding, 35, 728–734.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
97
Shi, H., Xie, S., & Wang, X. (2013). A warpage optimization method for injection
molding using artificial neural network with parametric sampling evaluation
strategy. International Journal of Advanced Manufacturing Technology, 65, 343–
353.
Shoemaker, J. (2006). Moldflow design guide: A resource for plastics engineers.
Hanser Publishers (vol. 10).
Smialek, C. D., & Simpson, C. (1998). SPE ANTEC Tech. Papers, 3373-7.
Song M. C., Liu Z., Wang M. J., Yu T. M. (2007). Research on effect of injection
process parameters on the moulding process for ultra-thin wall plastics parts.
Journal of Materials Processing Technology, 187–188, 668–671.
Thyregod, P. (2001). Modelling and monitoring in injection molding.
Tidke, Y. P., Dhote, A. V, & Patil, C. R. (2014). Study and optimization of process
parameters in plastic injection moulding - A review, 2, 58–65.
Titan, L. C. (2017). Titanpro PM803 polypropylene homopolymer. Retrieved from
www. lotte chemical Titan Titanpro®PM803 polypropylene homopolymer.html
Tran, P. (2016). SolidWorks 2017 advanced techniques. SDC publications.
Tsai, K., & Lan, J. (2015). Correlation between runner pressure and cavity pressure
within injection mold. Springer-Verlag London, 14–23.
Vlachopoulos, J., & Strutt, D. (2003). Polymer processing.
Wang, Q., Zhen, M., Wu, Z., & Cai, Y. (2017). Effect of process parameters on cavity
pressure in injection molding, 050005, 1–8.
Wang, R., Zeng, J., Feng, X., & Xia, Y. (2013). Evaluation of effect of plastic injection
molding process parameters on shrinkage based on neural network simulation
evaluation of effect of plastic injection molding. Journal of Macromolecular
Science, Part B: Physics, 37–41.
Xu, G. (2004). Study of thin-wall injection molding. Thèse.
Yu, F., Deng, H., Zhang, Q., Wang, K., Zhang, C., Chen, F., & Fu, Q. (2013).
Anisotropic multilayer conductive networks in carbon nanotubes filled
polyethylene / polypropylene blends obtained through high speed thin wall
injection molding. Polymer, 54, 6425–6436.
Zhai, M., Lam, Y. C., Au, C. K., & Liu, D. S. (2005). Automated selection of gate
location for plastic injection molding processing. Polymer-Plastics Technology
and Engineering, 44, 229–242.
PTTAPERP
USTAKAAN TUNKU T
UN AMINAH
98
Zhong, Z. W., Leong, M. H., & Liu, X. D. (2011). The wear rates and performance of
three mold insert materials. Materials and Design, 32, 643–648.
Zhu, H., Wang, C., & Sen, J. (2011). Analysis of injection molding of thin-walled parts
based on Moldflow, 6–8.