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Influence of molding conditions on the shrinkage and roundness of injection molded parts

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During the plastic injection molding process, one of the biggest challenges is shrinkage which deteriorates the quality of produced parts. To control and reduce this defect, the essential way is to perfectly determine the variables like molding parameters. In this study, the effects of molding parameters including packing pressure, melt temperature, and cooling time on shrinkage and roundness have been investigated experimentally. Also, the relationship among initial molding parameters, the cavity pressure, and mold temperature was investigated. The results of this experimental study and analysis fulfill various requirements of plastic injection molding and clarify the relationship between molding conditions and the overall quality of produced parts. This study illustrated that packing pressure and melt temperature are dominant factors which determine the quality of parts.
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ORIGINAL ARTICLE
Influence of molding conditions on the shrinkage
and roundness of injection molded parts
Mustafa Kurt &Yusuf Kaynak &Omer S. Kamber &
Bilcen Mutlu &Barkin Bakir &Ugur Koklu
Received: 4 January 2009 / Accepted: 26 May 2009 / Published online: 10 June 2009
#Springer-Verlag London Limited 2009
Abstract During the plastic injection molding process, one
of the biggest challenges is shrinkage which deteriorates the
quality of produced parts. To control and reduce this defect,
the essential way is to perfectly determine the variables like
molding parameters. In this study, the effects of molding
parameters including packing pressure, melt temperature,
and cooling time on shrinkage and roundness have been
investigated experimentally. Also, the relationship among
initial molding parameters, the cavity pressure, and mold
temperature was investigated. The results of this experi-
mental study and analysis fulfill various requirements of
plastic injection molding and clarify the relationship
between molding conditions and the overall quality of
produced parts. This study illustrated that packing pressure
and melt temperature are dominant factors which determine
the quality of parts.
Keywords Plastic injection molding .Molding parameters .
Cavity pressure .Shrinkage .Roundness
1 Introduction
Plastic injection is one of the most considerable molding
processes thanks to some significant reasons. The first
important reason is that the use of plastic parts in daily life
has tremendously increased in the last decades. For
instance, most of the communication, electronic, kitchen,
and daily consumer products are made of plastic materials.
Another remarkable reason is that plastic injection molding
is capable of producing products which have complicated
shapes, and different geometric aspects have perfect surface
quality and restricted quality tolerances. Therefore, the
expectation of this process is noticeable. In a plastic
injection molding process, a significant task is to select
initial molding parameters appropriately for producing
high-quality products. Generally, the desired molding
parameters are determined based on experience or by using
a handbook. Yet, these selection methods do not ensure that
determined parameters have optimal molding performance
in particular in order to obtain parts with minimal defects.
In order to determine the relationship between molding
conditions and produced part quality, the researchers have
been publishing many research results.
According to Chang [1], the product quality of injection
molded plastic parts is the result of a complex combination
of the material used, the part and mold designs, and the
process conditions used to manufacture them. Shrinkage is
one of several important factors determining the quality of
injection molded parts. Many factors, including materials,
processing parameters, and part and mold designs, can
affect shrinkage behavior. However, some research results
indicate that the packing pressure is the most important
process parameter affecting shrinkage during plastic injec-
tion molding process [25]. Postawa et al. [6] presented the
changes in shrinkage and weight of injection molded parts
as a function of processing conditions. According to this
study, not only packing pressure but also injection
temperature has considerable effects on the shrinkage
behavior of the parts produced [7]. Delaunay et al. [8]
have studied the influence of mold deflection on pressure
history and shrinkage. They reported that the effect of mold
deflection on shrinkage is ignorable. Wu et al. [9] focused
on the influence of cavity deformation on shrinkage and
Int J Adv Manuf Technol (2010) 46:571578
DOI 10.1007/s00170-009-2149-x
M. Kurt (*):Y. Kaynak :O. S. Kamber :B. Mutlu :B. Bakir :
U. Koklu
Technical Education Faculty, Marmara University,
34722, Kadikoy,
Istanbul, Turkey
e-mail: mkurt@marmara.edu.tr
reported that controlling this parameter can decrease the
shrinkage and overall quality of parts. On the other hand,
Kazmer et al. [10] investigated multi-cavity pressure
control in the filling and packing stages of the injection
molding process. Their study showed cavity pressure to be
a critical factor for the injection molding of high quality
parts. Bushko et al. [11] studied the effects of process
conditions on the shrinkage and residual stresses of thermo-
viscoelastic melts between two parallel plates. Titomanlio et
al. [12] investigated the influence of in-mold shrinkage on
the dimensions and residual stress distributions of the final
products. Angstadt and Coulter [13] investigated the
relationship between process conditions and part quality
in the injection molding process.
It can be concluded from the above literature survey that
the effects of molding parameters on shrinkage of the
produced parts have been investigated by researchers.
However, especially the quality of the cylindrical part
may not only be limited by shrinkage. To capture
dimensional validity, measurements of the part must
include lateral measurements. In this way, the relationship
between the results of measurements and the molding
parameters can be understood in depth. In addition, as it
shown from the above literature, some of the researchers
only focused on the molding parameters, such as packing
pressure, melt temperature, etc., and some of them only
studied the cavity pressure or mold temperature in order to
understand the effects of these parameters on shrinkage or
other kinds of defects; hence, it is clear that the relation-
ships of initial molding parameters with cavity pressure and
mold temperature have not been investigated comprehen-
sively before. One of the aims of this study is to highlight
those relationships.
On the other hand, many researchers have been using
computer-based simulation results in order to investigate
relationship between molding process and the obtained
parts quality [1417]. Generally, the presented results of
this kind of study are acceptable, but under some circum-
stances, there may be differences between the simulation
and experimental results. Although the cost of experimental
study is high, it is necessary to get more precious results.
Besides, in order to completely understand the effects of
variable parameters on the quality of the obtained parts, it is
necessary to use sensitive measurement devices. In this
way, trustworthy results can be obtained from the experi-
mental research.
In an attempt to investigate the effect of molding
parameters, cavity pressure and mold temperature during
plastic injection molding process, intensive experimental
research was carried out in this study by using advance
technological measurement device. This study focused on
understanding the function of molding parameters as well
as the effect of cavity factors on occurrence of the
shrinkage and roundness error problems in this process. It
is hoped that the results obtained from this study may be
beneficial to both researchers and manufacturers.
Fig. 1 Geometry and dimensions of the specimen
Fig. 2 Modeling of the plastic injection mold
572 Int J Adv Manuf Technol (2010) 46:571578
2 Experimental details
In order to do experimental study in molding process, there
are several steps which have to be followed. The first step
is to draw specimens with exact dimension which are
shown in Fig. 1. The design mold was modeled considering
all over dimensions and simulated by using the Pro-Eng
software (Fig. 2). Finally, the modeled mold was fabricated
taking into account the modeled dimensions. As shown in
Fig. 3, four cavity inserts were used in this research. A
dimmer cover is used for some kinds of home appliances.
For assembly of such parts, the dimensional and positional
tolerance is tight. The tolerance of the part during the
plastic injection molding process has therefore been
considered.
This experiment was conducted on a Haitian type
HTW58 injection molding machine with 244 MPa injection
pressure, 25 mm screw diameter, and 2.43 ton ejector
tonnage. The initial molding parameters for the experimen-
tal study were determined by consulting the literature and
considering industrial application. The material used in the
experiments was acrylonitrile-butadiene-styrene copolymer
(ABS). ABS thermoplastic resins are made with a wide
range of properties and are suitable for injection molding to
produce products of exceptional dimensional stability and
secondary processability for plating, painting, etc. The
properties of the ABS used in this study are summarized in
Table 1.
2.1 Determination of molding parameters
Before conducting the experimental study, determination of
molding parameters is necessary. Hence, first of all the
simulation model of the dimmer cover was designed using
the Pro-Eng software program. Afterwards, this model was
imported to MoldFlow. Base and mesh geometry are shown
in Fig. 4. MoldFlow software is a commercial software
based on hybrid finite element/finite difference techniques
in order to solve pressure, flow, and temperature of the
molding process. The molding process was simulated to
determine optimal molding parameters considering filling
stage of molding. As shown in Fig. 4, melt temperature,
packing pressure, and cooling time were determined by
using the MoldFlow software. As a result of this simula-
tion, the experiments were performed with varying packing
pressures ranging from 850 to 1,000 bar, melt temperatures
ranging from 185°C to 225°C, and cooling times ranging
from 20 to 35 s.
2.2 Measurements of cavity pressure and mold temperature
Although the sensing of pressure can increase the cost of
the experimental study, this research can be expected to
improve the accuracy of scientific studies. In such studies, a
significant aspect of implementing process controls is the
proper placement of these sensors. The most reliable
measurements can only be made by using properly placed
sensors.
In this study, cavity pressure and temperature have been
monitored by means of an instrumentation system employ-
ing three Kistler 6157BA piezoelectric pressure transducers
in the cavity and a 6190BAG temperaturepressure-
combined transducer. A Kistler CoMo 2869A injection-
type apparatus has been used for cavity pressure-based
Fig. 3 Male and female plates of mold
Table 1 Mechanical properties of ABS
Properties Tensile strength Elongation Flexural strength Impact strength Rockwell hardness
Condition 23°C 23°C 23°C 6.1 mm
Method (ASTM 750) D 638 D 638 D 790 D 256 D 785
Unit kg/cm
2
% kg/cm
2
kg cm/cm R-scale
General purpose 500 30 600 21 104
Int J Adv Manuf Technol (2010) 46:571578 573
optimization, control, monitoring, and documentation of the
injection molding process. The CoMo injection-type appa-
ratus has eight channels and is supplemented by a database
system with statistical functions and reporting. This all-in-
one unit contains all the functions needed for evaluating the
injection molding process. Signals can be directly acquired
and evaluated from the injection molding machine as well
as from piezoelectric cavity pressure sensors. The charge
amplifiers have a measuring range of 2,00050,000 pC.
The voltage inputs have a measuring range of 010 V
(http://www.kistler.com/). Hence, these sensors are suitable
for direct pressure and temperature measurements from the
cavities of the mold. The locations of these sensors are
shown schematically and photographically in Figs. 5and 6,
respectively. The sensors were placed at one-third of the
Fig. 5 Locations of sensors in the mold Fig. 6 The location of the pressure connectors
Fig. 4 Sample of molding process simulation
574 Int J Adv Manuf Technol (2010) 46:571578
distance from the gate in the cavities. Figure 7illustrates
the sample of the plot of cavity pressure and mold
temperature.
2.3 Measurement of shrinkage and roundness
On the other hand, in order to determine the deflections of
parts, an Advanced Topometric Sensor (ATOS) system was
used. The automated ATOS So system (three-dimensional
optical scanner) scanned the produced parts without the
need for special fixtures or reference markers on the part.
Then, the ATOS system automatically created the final
mesh after scanning. Additionally, the computer-aided
design (CAD) data (obtained using the Pro-Eng software)
were imported into the ATOS system. Finally, the scanned
data were registered into the CAD data to calculate and
Fig. 8 Sample of GOM results
Cavit
y
p
ressure measurement Mold tem
p
erature measurement
Fig. 7 Plots of cavity pressure
and mold temperature versus
time
Int J Adv Manuf Technol (2010) 46:571578 575
display the deviations of the two data sets by using the
GOM software (Fig. 8). The following quality attributes
were measured: (1) y-direction shrinkage, (2) x-direction
shrinkage, and (3) roundness of the part (see Fig. 9).
3 Results and discussion
The influence of molding conditions on shrinkage has been
discussed for decades. In fact, shrinkage occurs in all
molded plastic parts and error of roundness occurs in all
molded cylindrical parts on account of many reasons.
However, the question is how these defects can be reduced
and which parameters are dominant in this process.
Therefore, it is significant to understand and determine the
cause and effect of these defects. The current studies have
obtained considerable results to identify the relationship
between them. In addition, another measurable characteris-
tic of molded parts is roundness which is also discussed in
this section. In order to determine tendency of shrinkage
behavior, many experiments have been conducted taking
into account molding conditions. Packing pressure is one of
the molding parameters which influence the variation of
shrinkage and error of roundness. In fact, shrinkage
behavior of parts is measured considering axis xand y
and their maximum total values are presented (Fig. 10).
Furthermore, the error of roundness of each sample has
been measured and the maximum value of those measure-
ments is presented in Fig. 10, which shows the relationship
between packing pressure and total shrinkage value in xand
ydirections and error of roundness. When packing pressure
increases, the total shrinkage in xand ydirections
decreases. However, this inverse changing is not linear
because other parameters can be affected from the rising of
packing pressure. A similar tendency can be observed from
the variation of error of roundness. As a result of these
measurements, the effect of packing pressure not only on
shrinkage but also on error of roundness for cylindrical
molded parts is great which is shown in Fig. 10. The
selection of appropriate packing pressure can remarkably
reduce the defect rates of the plastic parts produced. In
addition, determination of the relationship between packing
pressure and cavity pressure and molding temperature is
one of the considerable results of this study. The influence
of packing pressure on measured maximum cavity pressure
(P
max
) and maximum mold temperature (T
max
) is shown in
Fig. 11. Due to the packing pressure, maximum cavity
pressure is increased sharply but mold temperature is
increased gradually. The quality of the molded parts has
been profoundly influenced from these variations. In fact,
packing pressure may not directly reduce the shrinkage and
error of roundness of the molded parts. It influences the
Fig. 11 Effect of packing pressure on measured maximum cavity
pressure and maximum mold temperature
Fig. 10 Effect of packing pressure on total shrinkage value in xand y
directions and error of roundness
y-direction shrinkage x-direction shrinkage Roundness
Fig. 9 Measurements of x- and y-direction shrinkages and roundness of parts
576 Int J Adv Manuf Technol (2010) 46:571578
cavity conditions; hence, the molded parts can be influ-
enced from this new cavity condition. Although, all
measurement costs are high, this study clarifies the effects
of initial condition and process conditions of plastic
injection molding.
One of the remarkable factors of molding conditions is
melt temperature. In order to obtain homogeny of molded
parts and reduction of defects, melt temperature is the key
parameter. Therefore, in this study, the effect of melt
temperature on total shrinkage in xand ydirections of
parts and error of roundness have been investigated.
Contrary to the packing pressure effects, the collected data
from the present experimental study show that when the
melt temperature was increased from 185°C to 210°C, the
total shrinkage in xand ydirections of the part decreased
from 0.23 to 0.18 mm; however, after that point, the
shrinkage was increased at 0.20 mm (Fig. 12). The reason
for these results is the 950-bar packing pressure. This high
pressure was the cause of higher melting temperature and
increased cooling time for plastic part. Because of this,
determination of optimal melt temperature is necessary to
obtain acceptable part quality. Similar variation behavior
was observed from the error of roundness of molded parts.
The error of roundness is a kind of warpage defects. Hence,
the temperature of the part is high because of the high value
of temperature inside the mold, but after the ejection
process, the hot part cools sharply in the room temperature
and this sharp temperature change increases the error of
roundness of parts. Although variation direction is opposite
of shrinkage and error of roundness, the second considerable
result from this study is that similar inclination behavior can
be observed from the measurements of cavity pressure
(Fig. 13). Yet, when the melt temperature was increased,
the mold temperature also increases. The relationship
between the melt temperature and mold temperature can be
inevitable, though description of the behavior of the cavity
pressure in this case is not easy because in plastic injection
molding, there are so many parameters which may influence
cavity conditions or quality of parts. However, on the other
perspective, these results show that the cavity pressure has a
dominant effect on the amount of shrinkage and error of
roundness that occurs.
One of the significant times in the plastic injection
process is the cooling time which is necessary to cool down
the plastic materials in the cavity and the extra time allows
the part become rigid enough and endure the ejection
process. Although all of the other parameters can be chosen
correctly, the inappropriate selection of cooling time can
Fig. 14 Effect of cooling time on total shrinkage value in xand y
directions and error of roundness
Fig. 13 Effect of melt temperature on measured maximum cavity
pressure and maximum mold temperature
Fig. 12 Effect of melt temperature on total shrinkage value in xand y
directions and error of roundness (packing pressure, 950 bar)
Fig. 15 Effect of cooling time on measured maximum cavity pressure
and maximum mold temperature
Int J Adv Manuf Technol (2010) 46:571578 577
cause failure of the process and unacceptable dimensions or
defects. On the other hand, if the cooling time is too long
and the parts are keep in the cavity for a longer period of
time, the cost of parts can increase due to the longer time
consumed. Additionally, the wall thickness of the part must
be considered when deciding the cooling time. Therefore,
in order to determine appropriate time, serious experimental
studies have to be conducted. During this experimental
study, the relationships between dependent and independent
parameters have been investigated. Figure 14 shows the
effect of cooling time on total shrinkage value in xand y
directions and error of roundness. It is worth mentioning
here that the defects of parts decrease with a longer cooling
time. Especially, error of roundness decreases profoundly
because as mentioned above the part needs enough time to
become solid; however, longer time can improve the cost of
the manufacturing process. Thus, after some experimental
study, the appropriate cooling time can be determined
considering the defects of the parts. On the other hand,
Fig. 15 shows that effect of cooling time on measured
maximum cavity pressure and d maximum mold tempera-
ture. It can be easily observed from Fig. 15 that the
influence of cooling time on cavity pressure is ignorable.
Yet, when cooling time is increased, the mold temperature
decreases expectedly.
To produce better quality products, the shrinkage and
error of roundness values must be decreased. As is evident
from the figures, the use of appropriate molding parameters
led to a profound decrease in the shrinkage and error of
roundness. While this is a notable improvement, by using
the relationship between initial molding parameters and
cavity pressure and mold temperature with defects, it may
be possible to develop models and to determine optimal
molding conditions by statistical techniques.
4 Conclusions
In this study, the molding process has been accurately
delineated and analyzed by using effective experimental
measurement techniques, highlighting the relationships
between molding parameters and the defects of the final
parts. Continuous sensitive measurement and data collec-
tion from a cavity mold have been successfully performed
by using piezoelectric pressure transducers and a pressure
temperature-combined transducer. The influence of initial
molding parameters on cavity pressure and mold tempera-
ture was clarified correctly. Also, the selected molding
parameters considerably affect the shrinkage of the product
in the y- and x-directions and its roundness. In addition,
although the cooling time influences the error of roundness
strongly, its effect on cavity pressure is not effective. It is
also highlighted that packing pressure is one of the
dominant factors which influence the cavity condition and
product quality. The selection of suitable initial molding
parameters can remarkably decrease the defects of parts and
increase the dimensional quality of production.
References
1. Chang TC (2001) Shrinkage behavior and optimization of
injection molded parts studied by the Taguchi method. Polym
Eng Sci 41(5):703710
2. Liao SJ, Chang DY, Chen HJ, Tsou LS, Ho JR, Yau HT, Hsieh
WH (2004) Optimization process conditions of shrinkage and
warpage of thin-wall parts. Polym Eng Sci 44(5):917928
3. Zhai M, Lam YC, Au CK, Liu DS (2005) Automated selection of
gate location for plastic injection molding processing. Polymer
Plast Tech Eng 44:229242. doi:10.1081/PTE-200048523
4. Jansen KMB, Titomanlio G (1996) Effect of pressure history on
shrinkage and residual stresses-injection molding with constrained
shrinkage. Polym Eng Sci 36(15):20292040
5. Jafairan AR, Shakeri M (2005) Investigating the influence of
different process parameters on shrinkage of injection-molding
parts. Am J Appl Sci 2(3):688700
6. Fu MW, Fuh HYJ, Nee AYC (1999) Undercut feature recognition
in an injection mould design system. Comput Aided Des 31:777
790. doi:10.1016/S0010-4485(99)00070-6
7. Berginc B, Kampus Z, Sustarsic B (2006) The use of the Taguchi
approach to determine the influence of injection-molding param-
eters on the properties of green parts. J Achiev Mater Manuf Eng
15(12):6370
8. Delaunay D, Bot PL (2000) Natural of contact between polymer
and mold in injection molding. Part II: Influence of mold
deflection on pressure history and shrinkage. Polym Eng Sci 40
(7):16921700
9. Wu CH, Huang YJ (2007) The influence of cavity deformation on
the shrinkage and warpage of an injection molded part. Int J Adv
Manuf Technol 32:11441154. doi:10.1007/s00170-006-0435-4
10. Kazmer D, Barkan P (1997) Multi-cavity pressure control in the
filling and packing stages of the injection molding process. Polym
Eng Sci 37:18651879. doi:10.1002/pen.11837
11. Bushko WC, Stokes VK (1996) Polym Eng Sci 36:322335.
doi:10.1002/pen.10419 Solidification of thermoviscoelastic melts.
3. Effects of mold surface-temperature differences on warpage and
residual stresses
12. Titomanlio G, Jansen KMB (1996) In-mold shrinkage and stress
prediction in injection molding. Polym Eng Sci 36:20412049.
doi:10.1002/pen.10599
13. Angstadt DC, Coulter JP (1999) Cavity pressure and part quality
in the injection molding process. The Science, Automation, and
Control of Material Process Involving Coupled Transport and
Rheology Changes, vol, 89, ASME, pp. 7-17
14. Tang SH, Kong YM, Sapuan SM, Samin R, Sulaiman S (2006)
Design and thermal analysis of plastic injection mould. J Mater
Process Technol 171:259267. doi:10.1016/j.jmatprotec.2005.06.075
15. Garcia N, Gonzalez E, Baselga J, Bravo J (2003) Critical
thickness estimation in ISO-MC cards injection using CAE tools.
J Mater Process Technol 143144:491494
16. Turng LS, Peic M (2002) Computer-aided process and design
optimization for injection moulding. Proc Inst Mech Eng B J Eng
Manuf 216:15231532. doi:10.1243/095440502321016288
17. Ozcelik B, Sonat I (2009) Warpage and structural analysis of thin
shell plastic in the plastic injection molding. Mater Des 30:367
375
578 Int J Adv Manuf Technol (2010) 46:571578
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