efecto de la limpieza del metal en la formacion de defectos de porosidad (die casting).pdf
TRANSCRIPT
Effect of melt cleanliness on the formation of porosity defectsin automotive aluminium high pressure die castings
C. Tiana,*, J. Lawb, J. van der Touwc, M. Murraya, J.-Y. Yaod, D. Grahamd, D. St. Johnd
aCSIRO Manufacturing Science and Technology, Preston, Vic., AustraliabNissan Casting Australia Pty Ltd., Dandenong, Vic., Australia
cCSIRO Mathematical and Information Science, Clayton, Vic., AustraliadCAST/The University of Queensland, St. Lucia, Qld, Australia
Received 2 September 1999; accepted 23 November 2001
Abstract
The effect of melt cleanliness on the formation of porosity defects in automotive aluminium high pressure die castings (TA Transmission
Case) was investigated experimentally. The experiments were conducted under actual industrial production conditions at Nissan Casting
Australia Pty Ltd. (NCAP). It was found that the probability of rejection due to excessive porosity present at critical locations in the castings
(determined using a real-time X-ray radiographic method) increased as the number of inclusions in the melt (measured with LiMCA II)
increased. The types of inclusion in the melt were identified as mainly amorphous oxides, oxide films and sludge particles. # 2002 Published
by Elsevier Science B.V.
Keywords: Porosity; Casting porosity; High pressure die casting; Melt cleanliness; Inclusions
1. Introduction
Porosity in cast automotive components is one of the
major quality problems facing high pressure die casters.
This is because porosity often causes leaking problems,
surface defects and machining problems. Depending on
its functionality, each type of casting has its own tole-
rance limits on porosity levels at certain locations in the
casting. Porosity in high pressure die castings is usually
classified as gas porosity, shrinkage porosity and flow
porosity, all of which are intrinsic problems associated
with the process.
Gas porosity is believed to be caused mainly by trapped
air, steam and burning products of organic lubricants used
in the shot sleeve. Shrinkage porosity occurs when the gate
area (from which the molten metal is injected into the
die cavity) solidifies before solidification in other areas of
the casting is completed (since in this case, the passage for
molten metal to feed the shrinkage due to solidification is cut
off). Thermal conditions of the die (dictated by its water
cooling system, the spray settings, the thermal conductivity
of the die material, the cycle time, etc.) and the temperature
of the molten metal are the major factors affecting the
amount of shrinkage porosity for a given alloy composition
and casting geometry. Flow porosity results from insufficient
pressure toward the end of cavity filling. Factors affecting
the porosity levels in the castings can be numerous. For
example, any factors affecting the fluid flow conditions
during cavity filling (such as the moving speed of the piston
in the shot sleeve, the velocity of the molten metal flowing
through the gate, the geometry and the location of the gate
for a given casting, pressure applied, etc.) may potentially
affect the amount and/or distribution of entrained air.
Melt cleanliness (i.e. inclusions and dissolved hydrogen
in the melt) may also have an effect on porosity formation in
high pressure die castings. Die casters have found by
experience that the porosity levels often increase when
100% returns (scrap) are used constantly for a period with-
out adequate treatment. The problem could become so
severe that up to 80% of the castings made from all casting
machines fed this type of melt failed to meet the quality
requirement due to excessive porosity present in the cast-
ings. Such a situation has been termed a porosity outbreak
[1]. In order to identify the cause of the porosity outbreak
and eventually prevent it from recurring, NCAP initiated a
research project with CSIRO (Commonwealth Scientific and
Industrial Research Organization)/CAST (Cooperative
Research Centre for Alloy and Solidification Technology)
to investigate the possible link between molten metal quality
and the quality of high pressure die castings.
Journal of Materials Processing Technology 122 (2002) 82–93
* Corresponding author.
0924-0136/02/$ – see front matter # 2002 Published by Elsevier Science B.V.
PII: S 0 9 2 4 - 0 1 3 6 ( 0 1 ) 0 1 2 2 9 - 8
2. The process
In high pressure die casting, the metal is forced into a steel
cavity (or die) through a narrow orifice (or gate) at speeds
ranging between 20 and 100 m/s. This is achieved by a
piston and a cylinder (or shot sleeve) where the piston is
driven by a high pressure hydraulic circuit capable of
achieving metal pressures of 100 MPa. The subsequent
casting is solidified under pressure with the aim of ‘feeding’
the casting with molten metal from the gate.
3. The premise
The effect of melt cleanliness on porosity formation in
castings is mainly manifested in the following ways: (a)
inclusions in the melt tend to impair the fluidity of the
molten metal [2], thus hindering feeding through the inter-
dendritic regions to difficult-to-access areas; (b) inclusions
in the melt tend to act as nucleation sites for dissolved
hydrogen to precipitate, thus increasing the melt sensitivity
to gas porosity [3–5]; (c) dissolved hydrogen in the melt
tends to precipitate out of solution to form hydrogen gas
bubbles during solidification due to its much lower solubi-
lity in solid than in liquid aluminium [6,7]. These effects are
well recognized in gravity castings. In high pressure die
casting, although these effects may, by intuition, not con-
stitute the major cause of the total porosity, they may result
in an additional effect thereby causing the permissible
porosity limit to be exceeded for a given situation. In
addition to the mechanisms mentioned above, the non-
wetting nature of oxide inclusions may facilitate large air
bubble formation which may otherwise, for the same
amount of entrained air, remain as dispersed smaller bub-
bles (the size of pores in automotive die castings is a major
criterion for quality control). In some thicker sections, if a
reduced or negative pressure is created due to solidification
shrinkage, the dissolved atomic hydrogen may come out
of solution to form hydrogen gas which then occupies the
shrinkage space and expands under high temperature
thereby aggravating the porosity in these areas. It has been
shown that the presence of excessive dissolved hydrogen in
the melt increased the total porosity (based on density
measurement) of a given casting by 60% (from 0.5 to
0.8%) [8].
The anecdotal increase in porosity when metal produced
from 100% returns are used indicates that something must be
abnormal in the melt (since this has been known to occur
over a number of machines in one plant at the same time, it is
unlikely that this event was due to localized deviation in
machine variables). The abnormalities may include varia-
tions in inclusion content, dissolved hydrogen and chemical
composition.1 In the present work, the effect of inclusion
content in the melt on the formation of porosity defects in the
castings was examined.
4. Experimental
4.1. The casting chosen for experimentation
In order to determine if there was a link between inclusion
level and the occurrence of excessive porosity (i.e. the
formation of sufficient porosity in critical locations to
warrant the rejection of the casting), a ‘TA Transmission
Case’ casting (see Fig. 1) with a relatively complex geo-
metry and sensitive to porosity formation was chosen. The
part is made in a fully instrumented high pressure die casting
machine so that any deviations in machine parameters could
be determined. Since casting geometry is an important
variable that affects the fluid flow and solidification char-
acteristics and thus porosity formation, all the experiments
were conducted with the same casting.
4.2. Melt cleanliness measurement
The alloy used was a Japanese standard aluminium die
casting alloy—ADC12 whose chemical composition is
similar to the Australian standard—AA335, British stan-
dard—LM2 and American standard—AA383, respectively.
The properties of AA383 aluminium alloy can be found
elsewhere [9]. The inclusion content in the melts was
measured using industry standard methods:
� LiMCA (liquid metal cleanliness analyser) [10] which is
capable of measuring particles greater than 20 mm in
molten aluminium in terms of number and size distribution.
� PoDFA (porous disc filtration apparatus) [11] was used to
assist in determining the type of inclusions by collecting
Fig. 1. A TA Transmission Case casting.
1 Although the melt is checked to ensure the alloy specification is met,
some uncontrolled minor and/or trace elements may vary.
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 83
the particles present in the molten metal on to the surface
of a fine ceramic filter.2 Approximately 1–2 kg of molten
metal was passed through the filter under pressure. Then,
the used filter was cut and polished and examined micro-
scopically. The types of particles present can be identified
either using optical microscopy based on their colour,
shape as well as morphology or, for some unknown types,
using scanning electron microscopy (SEM) or transmis-
sion electron microscopy (TEM) based on their X-ray
spectra and/or diffraction patterns.
The melts with different levels of cleanliness used for the
experiments were (a) normal melts tapped from a holding
reverberatory furnace which feeds all the high pressure die
casting machines, (b) dirty melts made of 100% returns and
(c) melts made of returns and ingots, melted in reverberatory
furnaces.
The contents of dissolved hydrogen in these melts were
assumed to be similar, based on the fact that all the melts
were prepared in a similar manner using natural-gas-heated
reverberatory furnaces.
The alloy composition was checked using conventional,
spark-emission spectrometry.
4.3. Experimental procedures
All the experiments were conducted using a 1250 t
locking-force, UBE high pressure die casting machine at
NCAP.
4.3.1. Small-scale batch experiments
To observe the trends in porosity formation when chan-
ging the level of inclusions, a series of small-scale batch
experiments were conducted using melts of varying inclu-
sion levels. In these trials, the experimental molten metal
held in a designated small holding furnace or a transfer ladle
was manually transferred to the casting machine during its
normal production operation. The particle levels in the melts
were measured with LiMCA II just prior to each trial.
PoDFA samples were also taken. The temperature of the
experimental metal was controlled at 640 8C, the same as
that of normal production melts. The experimental castings
along with six normal castings from production (three
immediately before and three immediately after the trial)
were selected for porosity examination. Since the experi-
mental castings were made during normal production, all
parameters except melt cleanliness should be the same as
those of normal production. Hence, the change in the amount
and distribution of porosity in these experimental castings
compared to those in the normal castings could be linked to
the melt cleanliness.
4.3.2. Large-scale batch experiments
Measurable effects of inclusions on porosity formation
were evidenced from the small-scale trials. In the large-scale
batch trial, the experimental metal was directly poured into
the holding furnace from which the molten metal was
automatically ladled into the casting machine. All para-
meters (except melt cleanliness) were maintained the same
as those of normal production. The particle level in the melts
was continuously measured with LiMCA II in the holding
furnace while the machine was running. A total of 49
castings were made during this trial.
4.3.3. Large-scale consecutive trials
The experimental procedure was the same as that men-
tioned in Section 4.3.2, however, the experiments continued
by consecutively re-filling the holding furnace when the melt
level in the holding furnace dropped to a certain level. Here
the experimental metal containing different levels of inclu-
sions was used to re-fill the furnace. The holding furnace was
re-filled eight times and a total of 240 experimental castings
were made.
4.4. Measurement of machine operating parameters
In the above trials, all the parameters, except the inclusion
content of the molten metal, were not intentionally changed.
However, the actual value of a given parameter may fluctuate
around its set value. This raised concerns as to whether the
rejected experimental castings due to excessive porosity were
caused by the ‘dirty’ metal or by variations of other para-
meters within their normal fluctuation range. For this reason,
in the large-scale consecutive trials, the principle machine
operating parameters (e.g. gate velocity, fill time, cycle time,
etc.) were monitored using a shot monitoring system con-
nected to the casting machine. The surface temperature of the
die was measured with an infra-red thermographic camera.
Fig. 2. An X-ray radiograph showing the porosity in a specific location of
a casting.
2 The need for collecting the inclusions in the melt to a concentrated area
(i.e. on the top of the PoDFA filter) for the purpose of examination arises
because the inclusion content in aluminium melts is normally too low to
allow a direct examination of a melt sample. Despite the low content, the
harmful effects of these inclusions can still materialize in most aluminium
fabrication processes and end products.
84 C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93
4.5. Casting quality assessment
4.5.1. Real-time X-ray inspection
All the castings made in the trials were examined using a
real-time X-ray radiographic inspection system (which is
routinely used by NCAP for normal production inspection)
to reveal the porosity in the castings (see Fig. 2). NCAP
classifies the porosity at a given location into four grades
according to its severity: a grade of ‘1’ denotes nil or little,
‘2’ some, ‘3’ considerable (or just acceptable), and ‘4’ not
acceptable. If the X-ray grade at one location in a casting
scores a 4, the casting will be rejected (there are 31 locations
that need to be inspected in the TA Transmission Case
casting). The accuracy and consistency of the X-ray grading
depend on the experience of the inspector.
A casting is rejected if the size of the pores at given
locations exceeds the prescribed limits set out by the cus-
tomer. The tolerance limit varies with locations in the same
casting. Some locations cannot tolerate any observable
porosity, while other locations may tolerate pores up to
several millimetres. It is the porosity at certain locations
in the casting that is of concern rather than the total
porosity.3 For this reason, the term ‘excessive porosity’
was used to indicate a level (at a given location) that requires
rejection of the casting.
4.5.2. Microscopic examination
In order to fully characterize the nature of the porosity,
detailed microscopic examination was also conducted. In
these analyses, the castings were cut up at locations of
interest, and the number, size, shape and morphology of
the pores at each location were measured using the X-ray
radiographic method. Metallographic examination was also
conducted.
5. Results and discussion
The experimental results in terms of reject rates as
determined by the X-ray grades vs. inclusion content are
presented in Fig. 3 for the small-scale batch experiments.
Fig. 4 shows the results for the large-scale consecutive
experiments together with the large-scale batch data point.
The combined data is presented in Fig. 5. The size of the
circles in these plots is proportional to the number of
experimental castings made.
From these results there appears to be a relationship
between inclusion level and reject rate. In order to deter-
mine whether the relationship is statistically valid, the
following statistical analysis was undertaken. It was found
that the data could be fitted into the following logistic
equation:4
pðxÞ ¼ eyðxÞ
1 þ eyðxÞ ; (1)
where p(x) is the probability of rejection, x the inclusion
content in terms of thousand particles (�20 mm) per kg of
molten metal (k/kg), and yðxÞ ¼ aþ bx.
Fig. 3. Reject rate vs. number of inclusions in the melts. Data obtained from the small-scale batch experiments.
3 A casting with a higher total porosity may be accepted, while a casting
with a lower total porosity may be rejected, depending on the distribution
of the porosity within the casting.
4 Logistic transformation is often used in statistics to map the (0, 1)
probability range onto the real line (�1, þ1) so that a correlation can be
investigated in a manner analogous to standard linear regression.
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 85
The coefficients a and b were estimated from the data
using the method of maximum likelihood. The fitted equa-
tions based on the experimental data were
yðxÞ ¼ �2:98 þ 0:0500x ðsmall-scale batch experimentsÞ;(2)
yðxÞ ¼ �5:02þ 0:0818x ðlarge-scale consecutive experimentsÞ;(3)
yðxÞ ¼ �4:08 þ 0:0617x ðcombined dataÞ: (4)
The fitted equations are shown in Figs. 3–5. The shaded
areas give 95% confidence intervals for the fitted equations.
The single data point from the large-scale batch experiment
shown in Fig. 4 was not taken into account during the
regression analysis (since it is a separate event). As can
be seen, this single data point is indeed consistent with the
set of data from the large-scale consecutive experiments,
Fig. 4. Reject rate vs. number of inclusions in the melt. Data obtained from the large-scale consecutive and batch experiments. The sizes of the circles
indicate the number of castings made for the corresponding data points.
Fig. 5. Reject rate vs. number of inclusions in the melt. Combined data from the consecutive and batch experiments. The size of the circles indicates the
number of castings made for the corresponding data points.
86 C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93
Fig. 6. Schematic drawings of the TA Transmission Case that show the zones where X-ray examinations were performed. There are 10 positions in zones A
and D, three in B and five in C, respectively.
Fig. 7. Porosity index (mm3, averaged from three castings) of: (a) normal castings; (b) castings made from a dirty melt, at locations where porosity must be
controlled according to prescribed standards (‘zone’ and ‘position’ denote specific locations in the castings).
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 87
indicating that batch experiment is as a valid approach as
consecutive experiments.
It is evident from these figures that the results obtained
from the small-scale batch and large-scale batch and con-
secutive experiments are consistent. Judging from the fact
that the correlation between inclusion content and prob-
ability of rejection was statistically significant, p < 0:05,
based on a standard statistical test using generalized linear
regression [12], it can be concluded that the probability of
rejection will increase with increasing inclusion content.
Eq. (1) is not intended to represent a theoretical relationship
between the probability of rejection and the inclusion content.
Rather, it merely represents an empirical relationship between
the two variables for the given casting and experimental
conditions in much the same way that a straight line is used
to illustrate a relationship between two correlated measured
variables. The logistic equation (1) is a generalization of a
linear equation to the case where one of the variables is a
probability rather than a directly measured variable. Note that
the logistic equation (1) can be re-written as
logpðxÞ
1 � pðxÞ
� �¼ aþ bx: (5)
Thus, the log of the odds against rejection is assumed to be
linearly related to the inclusion content.
The statistical nature of the effect of inclusions in the melt
on the reject rate of high pressure die castings due to the
formation of excessive porosity stems from the random nature
of inclusion distribution in the castings and the inadequate
account for the nature of inclusions as independent variables.
Fig. 8. The difference in porosity index between normal castings and castings made from a dirty melt.
Fig. 9. X-ray indices of three experimental and six normal castings.
88 C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93
For a given number of inclusions, depending on where the
inclusions end up in the casting, the effect on porosity
formation at certain locations would be different. The effect
of inclusions on porosity formation depends not only on the
number, size, and spatial distribution but also on the nature
of inclusions such as type (which, for example, may affect
wetting) and shape or morphology. For example, pore nuclea-
tion should be easier on non-wetting and/or sharp-edged
particles than on wetting and/or smooth spherical particles.
Among these variables, only the number, size (usually the
equivalent spherical diameter), and type of the inclusions can
be measured with a certain degree of success (e.g. using
LiMCA II and PoDFA). To use the total number of inclusions
greater than 20 mm in the melt as an independent variable to
assess the effect of inclusions on porosity formation in a
casting is apparently inadequate. (Due to the inherent diffi-
culties in measuring the various attributes of the inclusions in
molten metal, it is impractical to account for all attributes
as necessary independent variables.) That is why the results
were treated as probability events rather than deterministic
quantities.
In order to verify the result of the statistical analysis, two
additional approaches were taken to obtain supporting evi-
dence of the effect of melt cleanliness. Firstly, the castings
were characterized using a porosity index which is the
volume of porosity in mm3 estimated from the microscopic
X-ray examinations conducted at a number of locations in
the casting (see Fig. 6). Fig. 7 shows the porosity index at
Fig. 10. Cycle time of: (a) all castings; (b) rejected castings made in the consecutive large-scale experiments. The prolonged cycle times are associated with
minor stops.
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 89
different locations in: (a) normal castings and (b) castings
made from a dirty melt (80,000 particles greater than
20 mm/kg of molten aluminium), while Fig. 8 shows the
difference between the two at their corresponding locations.
It is clear that the porosity levels in the castings made from
the dirty melt increased at most locations compared to those
in the normal castings.
The second approach was to calculate X-ray indices. The
X-ray index is defined as the averaged X-ray grades at all
inspected locations in a given casting. Fig. 9 presents the
X-ray indices of nine castings (three experimental along
with six normal castings immediately before and after a
small-scale batch trial) made in a sequential order. It is
evident that the X-ray indices increased when the dirty
experimental melt was used in the trial.
To determine whether the cause of rejects is related to
deviations in operating conditions, plots were made of various
casting parameters vs. the casting number for the castings
made in the large-scale consecutive trial (Figs. 10–12). In each
case, the plot labelled (a) is for all the castings made, whereas
(b) is only for the rejected parts. It is interesting to note that
most of the rejected castings were not directly associated with
minor stops (i.e., prolonged cycle times caused by interrup-
tions of furnace re-fills, extractor or spray arm malfunctions,
etc.), and their corresponding gate velocities and fill time fell
randomly within the normal fluctuation range. The die surface
temperature from shot to shot was also relatively constant.
This appears to indicate that the rejected castings were not
caused by the normal fluctuations of the principle operating
parameters monitored during the experiments.
Fig. 11. Average gate velocities of: (a) all castings; (b) rejected castings made in the consecutive large-scale experiments.
90 C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93
The inclusions found in the PoDFA filter cakes were
examined and identified using optical microscopy, SEM
and TEM. It was found that the inclusions in the melts
consist mainly of amorphous oxides [13], oxide films and
sludge particles (see Fig. 13).
Since casting geometry is an important factor that affects
the fluid flow and solidification processes (which in turn
affect the formation of porosity in the casting), the results
obtained in this study cannot be generalized to apply to other
casting geometries or situations where the operating para-
meters are different from the ones used in the experiments
conducted in this study. Thus, it is the trend that is more
meaningful rather than the actual values. A general approach
would require identification of all relevant dimensionless
groups of all independent variables and, in some cases, the
satisfaction of geometric similarity which is impossible to
realize for different casting geometries.
6. Summary
The effect of melt cleanliness on the formation of
excessive porosity leading to rejection of an aluminium
high pressure die casting (TA Transmission Case) was
investigated experimentally. The results showed that the
reject rate increased with an increase in inclusion content
Fig. 12. Fill time of: (a) all castings; (b) rejected castings made in the consecutive large-scale experiments.
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 91
in the melts. The types of inclusion present in the melts
were found to consist of mainly amorphous oxides, oxide
films and sludge particles. The results obtained in this study
indicate that it is necessary to control melt cleanliness in
order to reduce the reject rate of structural, automotive
aluminium high pressure die castings, thus improving
productivity.
Acknowledgements
The authors would like to thank Peter Miller for the
identification of the amorphous oxides and Necip Kultur
and Stefan Gulizia for their assistance in carrying out the
plant trials. The authors would also like to thank the NCAP
staff for their assistance throughout the work. Finally, the
Fig. 13. Inclusions found in a filter cake formed from filtering a dirty melt (80,000 particles greater than 20 mm/kg of molten metal) with PoDFA. Top:
optical image; bottom: backscattered electron image (the bright phase is a sludge particle, the black particles are amorphous oxides).
92 C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93
authors would like to express their sincere gratitude to Trust
Bank for funding this research.
References
[1] K. Hooper, Private communications, 1997.
[2] D.E. Groteke, Influence of SNIF treatment on characteristics of
aluminum foundry alloys, AFS Trans. 93 (1985) 953–960.
[3] K.J. Brondyke, P.D. Hess, Interpretation of vacuum gas test results
for aluminum alloys, Trans. TMS–AIME 230 (1964) 1542–1546.
[4] E.L. Rooy, E.F. Fischer, Control of aluminum casting quality by
vacuum solidification tests, AFS Trans. 76 (1968) 237–240.
[5] D.E. Groteke, Testing for molten metal cleanliness, Die Casting
Engr. (September/October 1996) 18–26.
[6] P.N. Anyalebechi, Analysis and thermodynamic prediction of
hydrogen solution in solid and liquid multicomponent aluminum
alloys, Light Met. (1998) 827–842.
[7] C.E. Ransley, H. Neufeld, The solubility of hydrogen in liquid and
solid aluminum, J. Inst. Met. 74 (1948) 599–620.
[8] C. Tian, J. Law, M. Murray, Unpublished work, 1998.
[9] Properties of cast aluminum alloys, in: ASM Handbook Committee
(Eds.), Metals Handbook, Vol. 2, 9th Edition: Properties and
Selection: Nonferrous Alloys and Pure Metals, American Society
for Metals, Metals Park, OH, 1979, pp. 152–179.
[10] R.I.L. Guthrie, D.A. Doutre, On line measurements of inclusion in
liquid metals, in: Proceedings of the International Seminar on
Refining and Alloying of Liquid Aluminum and Ferro-alloys,
Trondheim, Norway, 1985, pp. 145–163.
[11] D. Doutre, B. Gariepy, J.P. Martin, G. Dube, Aluminium cleanliness
monitoring: methods and applications in process development and
quality control, Light Met. (1985) 1179–1195.
[12] P. McCullagh, J.A. Nelder, Generalized Linear Models, Chapman &
Hall, London, 1983.
[13] P. Miller, CSIRO Internal Reports, CSIRO Manufacturing Science
and Technology, Clayton, Vic., 1997.
C. Tian et al. / Journal of Materials Processing Technology 122 (2002) 82–93 93