Int. Comm. Heat Mass Transfer; Vol. 29, No. 1, pp.91-105, 2002 Copyright 0 2002 Elsevier Science Ltd Printed m the USA. All rights reserved 0735-1933/02/$-m front matter
Pergamon
PLI: SO7351933(01)00328-l
COMPARISON OF THE RESULTS FOR SEMISOLID AND PLASTIC INJECTION MOLDING PROCESS
Y.K. Shen, J.J. Liu, C.T. Chang and C.Y.Chiu LungHwa University of Science and Technology Department of Mechanical Engineering 300 Wanshou RD.,secl, Kueishan, Taoyuan County, Taiwan, ROC 333
(Communicated
by J.P. Hartnett
and W.J. Minkowycz)
ABSTRACT Understanding the time-dependent flow behavior of semisolid and plastic materials is essential for the injection molding. The 3C (Computer, Communication, Consumer) product is more light, thin, short and small on today. Traditional injection molding uses the plastic for the shell of 3C product. Because the EMI, good heat dissipation etc., the magnesium for the shell of 3C product is more increasing now. The properties of plastic are shear-thinning. The properties of magnesium are shear-thickening and it injects the mold by semisolid form. Therefore, the situation of injection molding between plastic and magnesium is very different. This paper uses the CAE software (MoldFlow) to analysis the result with different materials (ABS, ABS/PC, Mg), different processing parameters (injection temperature, mold temperature, injection pressure, injection time), and different thickness (1 .Omm, 0.9mm). In order to obtain the optimum results, the simulation introduces Taguchi method to discuss the influence of each parameter in injection molding. Q 2002 Elsevier Science Ltd
Introduction Semisolid-injection
molding
Consumer, Communication)
is the branch of precision
injection
molding.
The 3C (Computer,
product is more emphasis on today. But the product design, machine design,
mold design, the control of process parameter and quality of product has not yet deeper research. The die-casting
is often used to metal forming. Semisolid
injection molding process is less useful on the
world.
Alexandrou et al.,[ l] used numerical simulation to predict die filling, and hence to optimize the die 97
Y.K. Shen et al.
98
design. In their study, a “Bingham type”, or Herschel-Bulkley
Vol. 29, No. 1
constitute relation is introduced, capable of
describing correctly the bulk behavior of semisolid slurry. Hu et al.,[2] discussed a thin-wall magnesium telecommunication
part that was selected
technique was applied for the optimization
to be hot chamber
die cast and a numerical
of the runner and gating. Alexandrou
simulation
et al.,[3] concentrated
on Bingham fluid tilling of a 2-D cavity and examined the relative important of inertial, viscous and yield stress effects on the filling profile. Their results presented Which was modified by introducing
are obtain using PAM-CAST/SIMULOR.
a regularized Bingham fluid constitute
relation. Burgos et al.,[4]
introduced the flow behavior of semisolid materials is essential for the simulation of semisolid process. Experimental results show that the transient behavior of semisolid materials at constant structure is shear thickening, and there exits a shear-dependent consistency
finite yield stress. The results show that the yield stress, the
index, and the power-law index are assumed to be function of solid fraction and a structural
parameter that changes with the processing history. Hieber and Shen [5] simulate the filling process of injection molding that uses a generalized Hele-Shaw flow for the non-Newtonian
fluids.
The process parameters that affect the quality of injection molding products include cooling time, injection pressure, injection speed, injection time, filling time, melt temperature, ejecting pressure, mold temperature, mold geometry shape, material property of melt, melt speed and heat transfer action of flow field. Shen [6] suggested that filling time, melt temperature
* mold temperature and injection pressure are
the significant control factors that affect warpage and mechanical properties.
In the CAE analysis,
only the filling time, melt temperature
* mold temperature
and injection
pressure are imported to the MoldFlow software, and the ABS, ABSIPC, Mg material are taken as the material being injected. The parameters of processing conditions and materials have a lot of values. This paper uses the Taguchi method to get the optimal results. Arrangement
table Lg can simulate the results
by efficacy and system.
The purposes of this paper are using MoldFlow analysis to plan the process conditions of semisolid (Mg) and plastic (ABS, ABS/PC) injection molding and looking for the optimal process condition.
Mathematical Model The governing equation is non-isothermal,
Continuity Equation:
generalized Newtonian fluid.
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aP a(P) -+-+-+-_=o
WV) ay
a~
at
SEMISOLID AND PLASTIC INJECTION MOLDING PROCESS
a(PJ)
az
(1)
Momentum Equation:
(2)
p
au av -+u-+v!$p[$+$)-$ at ax
(
(3)
Energy Equation:
(4)
The viscosity model for magnesium:
(I n/a
v=vm(fs)
!i’ 11 r*u
1+ --+
1
(5)
Y
vm(fs) = A,exp(B,f,)
r*(f,)
=
4 exp( B2fs)
(6)
(7)
The viscosity model for plastic:
G+AP)=
(8)
99
100
Y.K. Shen et al.
Vol. 29, No. 1
(9)
Then i=,/m
(10)
Boundary and initial conditions:
At
z=fb:u=v=O;
T=T,
(11)
(12)
The pressure is independent of z-direction. Because the thin product of notebook computer. The momentum equation (2) (3) (for the Hele-Shaw model) integrates to the following equations:
(13)
o(E)=[%)z
(14)
by the boundary condition, the equation (13), (14):
IA=
(-z 1“f
(15)
(16) integrates the equation (15) and (16):
(17)
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s =
j,“p-
SEMISOLID AND PLASTIC INJECTION MOLDING PROCESS
101
z 2dz
tl
Equation (17) and (18) add to (I), then get
Because
p = p(T, p)
(21)
(22)
(23)
The boundary conditions for equations for equation (2 1) is:
p=o
P = P,(%YTG
3P -_=O
an
on flow front
(24)
on inlet
(25)
on mold wall
(26)
Then uses the finite element method to solve the former equations [7]. The shell of notebook computer is the thin model. The mold dimension of the shell of notebook computer
102
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Y.K. Shen et al.
is shown in Figure 1.
FIG. 1 Dimensions of the shell of notebook’s computer.
Results and Discussion The levels of each operating parameter for ABS, ABS/PC and Mg are listed in Table l-3. According to the levels of each of each parameter, a suitable experiment arrangement table Lg in Table 4.
This paper can simulate nine results by Lg orthogonal
array. This paper can find the optimal
processing conditions by the ration plot for injection time, injection pressure and temperature difference. Then the authors use the MoldFlow analysis to simulate the case for this optimal processing condition.
Table 5 shows that the optimal processing factors for ABS, ABS/PC, Mg (O.lmm, 0.9mm).Table 6 shows that the simulation result according to Table 5.
The suitable material is Mg > ABS > ABS/PC for the shell of notebook computer (0.9mm, lmm). Because the injection time, pressure, temperature difference for Mg are smaller than the other materials. The smaller injection time can short the processing difference cause the shrinkage and warpage smaller.
situation. The smaller pressure and temperature
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SEMISOLID AND PLASTIC INJECTION MOLDING PROCESS
TABLE 1
TABLE 2
TABLE 3
103
Y.K. Shen et al
104
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TABLE 4
TABLE 5
TABLE 6 Simulate results according to Table 5 Injection
Injection
Temperature
Time
Pressure
Difference
ABS (1 .Omm/0.9mm)
0.38/0.38
241.96/218.03
31.05/27.26
ABS/PC (1 .Omrn/0.9mm)
0.38/0.38
267.081247.45
28.83126.59
Mg (1 .Omm/0.9mm)
0.07/0.06
100.47/111.08
20.02/20.63
Unit
Second
MPa
“C
Conclusions
The numerical results are very different for plastic and semisolid injection molding. The results show that the injection temperature and mold temperature for Mg are higher then plastic. The results also show that the injection pressure, filling time and temperature difference for Mg are smaller than plastic. Therefore, The Mg material is more suitable than plastic material.
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SEMISOLID AND PLASTIC INJECTION MOLDING PROCESS
105
References 1.
A. N. Alexandrou, F. Rardinet and W. Loue , Journal of Materials Processing Technology, 96, 59 (1999).
2.
B. H. Hu, K. K. Tong, X. P. Niu and T. Pinwill , Journal of Materials Processing Technology, 128 (2000).
3.
A. N. Alexandrou, E. Due and V. Entov , J. Non-Newtonian FIuidMech.,
4.
G. R. Burgos, A. N. Alexandron and V. Entov, Journal of Materials Processing Technology, 110,
105,
96,383 (2001)
164 (2001).
5.
C. A. Heieber and S. F. Sben, Isreal of Technology, 16,248 (1978).
6.
C.I. Shih, Y.M. Liu, H.C. Chen and Y.K. Shen, The Research of Computer Simulation on Component of Fiber Communication (MEMS), 2#’ Mechanism Conference, E- 11,Taiwan (2000).
7.
P.Kennedy, Flow Analysis Reference Manual, Hanserpublishers,
New York (1993). Received August IO,2001