A practical approach to eliminate defects in gravity die cast al alloy casting using simulation software

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 01 | Jan-2015, Available @ http://www.ijret.org 114
A PRACTICAL APPROACH TO ELIMINATE DEFECTS IN GRAVITY
DIE CAST AL-ALLOY CASTING USING SIMULATION SOFTWARE
S. Ferhathullah Hussainy1
, M. Viquar Mohiuddin2
, P. Laxminarayana3
, A. Krishnaiah4
,
S. Sundarrajan5
1
Professor, M.E.D., MJCET, Telangana, India.
2
Associate Professor, M.E.D., MJCET, Telangana, India.
3,4
Professor, M.E.D., Osmania University, Telangana, India.
5
Director, National Institute of Technology - Tiruchirappalli, India.
Abstract
This paper deals with elimination of defects in aluminium alloy castings produced by gravity die casting process. The main
intention of work is to investigate the defects and improve quality of a gravity die cast component using Computer Aided Casting
Simulation Software. In this study an industrial gravity casting die is used which was producing defective components. The die
and components produced by the die are studied to eliminate the defects using virtual simulations. The defects in the components
are identified to be solidification shrinkage, cracks, unfilled riser and incomplete mould cavity. The reasons for the defects are
analyzed as either improper selection of process parameters, or improper design of gating and risering system. SOLIDCast
simulation software is used for simulating the solidification process of casting and visualizing outputs showing possible
problematic areas or defects which may occur in the cast product. The work is carried out in two stages. In first stage, few test
castings are produced by modifying the process parameters (pouring temperature, pouring time, pre heat and alloy type) and
results are compared with simulation results produced using same parameters. The pouring and simulation results are observed
to be in good accordance with each other. In second stage, number of virtual iterations of casting is performed by changing riser
dimensions. It was found from the simulation results that riser with 35mm diameter is required to produce casting with zero
defects. The die is modified accordingly with the simulation results and metal is poured. The castings produced are observed to be
sound and contain no defects; and also it is verified that solidification simulation helps in locating the defects, eliminating them
and ultimately improving the quality of castings without any shop-floor trails.
Keywords: Aluminum-Alloys, Casting Defects, Gravity Die Casting, Material Density and SOLIDCast Simulation
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1. INTRODUCTION
Casting is one of the most economical processes in
manufacturing industry to produce metallic components.
The process of producing a new casting in a foundry begins
with receiving design from a customer, which includes
dimensions, tolerances, type of material, surface finish,
strength, etc. The foundry engineer designs the gating and
risering system for the casting. The time spend in designing
and re-designing the gating and risering system might take
few days or up to several weeks, depending upon the
complexity of the casting, before sound castings are made.
In the past, the foundry man has strived for ways to improve
the casting process and eliminate the defects that occurred in
the castings by trial-and-error, and his past experiences.
Scientists throughout the years have studied the science of
casting and metallurgy and developed theories and
mathematical models to explain the properties of metals
while going through the solidification process. Casting
simulation programs are developed from these methods
which are useful in predicting how the casting will
come out. Defects and problems can be discovered before
the actual product is cast avoiding costly trails to prevent the
defects [3].
In the present scenario, the use of casting simulation
software is increasing day by day in Indian foundry industry
and essentially replacing or minimizing the shop floor trials
to attain sound castings. The casting simulation technology
has sufficiently matured and has become an essential tool
for casting defect troubleshooting and method optimization.
It enables quality assurance and high yield without shop-
floor trails, and considerably reduces the lead time for the
first good sample casting. Productivity is improved, higher
value castings can be taken up, and internal knowledge can
be preserved for future use and training new engineers [2].
In this work, an attempt has been made to investigate the
reasons for the defects occurring in the gravity die cast
components and resolve them using Computer Aided
Casting Simulation Technique along with experimental
validation.
2. LITERATURE REVIEW
Years after the development of casting simulation programs,
virtual simulations of castings have now stepped into the
maturity. Many new techniques have emerged and lot of
work is going on to test the results of simulation
experimentally. Some of the related works are
acknowledged here. T. R. Vijayaram. et. al. [4], in their

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work discussed about the simulation process of casting
solidification with the aid of an example, which will help the
foundry engineers to optimize the design parameters,
understand the temperature history of solidifying casting,
and identify hot-spot region with the aid obtained from time-
temperature contours. D. Kakas [5], observed a complex
shape piston casting produced in foundry with a
considerable scrap loss due to porosity. During production
there are some solidification problems, due to the poor
feeding of the thinnest part of the piston wall, where the
copper chills are applied. The idea was to investigate the
influence of variety casting parameters and casting design
by computer simulation. A. P. Wadekar et. al. [6] in their
research work have taken a Compressor Housing and
performed casting simulation with the help of high end
package. It is seen that designer can easily identify various
defects of casting before actual production starts, this helps
to reduce rework and finally produces good quality product
in minimum time. Adnan S. Jabur [7] has given details of
how to predict the shrinkage cavities of Al-Si castings by
using the solidification simulation software. . S. G. R.
Brown et. al. [8] detailed the use of visualization techniques
for a complete design process for a generic automotive
component. Their work was to redesign a generic
automotive component considering both the stress related
and solidification related design problems simultaneously.
Filling and solidification of the designs were simulated
using MAVISFLOW. D. R. Gunasegaram et. al. [9] in their
paper have given details of vital process parameters
affecting the size and location of a shrinkage pore defect in
an aluminium alloy permanent mould casting of varying
section thicknesses. The foundry achieved a reduction of
more than 13% in its annual scrap rate for the casting
involved. V. R. Maniar et. al. [10] in their paper have
applied casting simulation software PROCAST to visualize
complete solidification process which was not possible
during real casting. Defects such as shrinkage, porosity, gas
porosity, unfilled mould, cold shut etc. were graphically
observed. T. Nandi et. al. [11] in their paper has optimized
riser size of LM6 aluminum alloy by using conventional
method and computer aided casting simulation software.
They have considered plate casting with different riser sizes
to study solidification behavior of the alloy used. N. A.
Dukare et. al. [12] has optimized a gating system by using
MOULDFLOW software. Objective of their work was to
optimize gating/riser system design based on CAD and
simulation technology with the goal of improving casting
quality such as reducing incomplete filling area, decreasing
large porosity and increasing yield.
3. CASTING SIMULATION
Casting simulation software can predict where and what
defects might occur in a casting so the time and material
used in the trial stage may be reduced. The casting process
simulation is temperature and time dependent program.
Freezing of castings is a non-linear transient phenomenon
and involves modification of phase with liberation of latent
heat from an affecting liquid-solid boundary. The casting
process simulation programs consider the thermo physical
data of the alloys and suitable boundary conditions data as
an input and helps in predicting the defects by observing
temperature distribution or hot spots in the castings. The
casting simulation programs have different approaches in
calculating and predicting the outcome of a casting. Each
method hold advantages and disadvantages compared to
other. Few casting simulation methods are mentioned
below:
1) Numerical Approach.
 Finite Element Method (FEM).
 Finite Difference Method (FDM).
2) Geometrical Approach.
 K-Contour Method.
3) Computer Wave Front Analysis.
 Pour-out Method.
 Cubic Spine Functions.
4) Mesh less Method.
5) Grid-based simulation system.
In this study SOLIDCast software is used to carryout casting
process simulation. It is a program which simulates the
solidification process of castings using Finite Difference
Method. This software has been developed by Finite
Solutions Inc., USA.
3.1 Steps in Casting Simulation
Steps involved in casting simulation using SOLIDCast
software are as follows:
1) Select Materials: Casting Alloy, Mould Material and
Boundary Conditions.
2) Create a 3D Model: Import STL files from CAD
system or create 3D shapes within SOLIDcast.
3) Mesh the model.
4) Run a simulation:
 SOLIDCast simulation.
 FLOWCast simulation.
5) Plot simulation results.
6) Decide whether to redesign/rerun the simulation.
3.2 SOLIDCast Simulation
SOLIDCast is a casting simulation software program which
can simulate thermal changes and heat transfer in the
solidification process of a casting. It assists the user to
visualize the solidification process of a particular casting.
The program offers functions to help guide a user in
producing gating and riser designs. It also has functions
which produce visual outputs showing possible problem
areas and defects which may occur in a casting. It can help
shorten the lead time and reduce the loss in the trial casting
stage.
3.3 FLOWCast Simulation
FLOWCast is the fluid flow modeling module for mold
filling simulation, which works in conjunction with the
SOLIDCast modeling system. It simulates the flow of liquid
metal into a mold, along with the cooling of the metal and
heating of the mold. It has two modes - Quick Simulation
and Full Simulation. Quick simulation is a fast-filling
algorithm, where as Full Simulation is a full CFD

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simulations of fluid flow. It uses the meshed SOLIDCast
model to run its simulation and displays the temperature,
velocity and pressure during the fill.
4. EXPERIMENTAL PROCEDURE
The following steps were performed during gravity casting
process:
 Melting of aluminium
 Degassing
 Coating of die
 Clamping of die
 Preheating the die
 Pouring of metal
 Cooling and solidification
 Cleaning and inspection
4.1 Dimensional Details
Figure shows the dimensional details of 3D model of the
product developed using SolidWorks modeling software and
imported to SOLIDCast simulation software and assembled
with gating and risering system.
Fig-1: Dimensions of casting with gating and risering
4.2 Gravity Die Casting Mould
The mould for gravity die casting is of two plates with
parting line in vertical plane having mould cavity with
gating and risering system machined on it.
Fig-2(a): First plate of the mould
Fig-2(b): Second plate of the mould
4.3 Casting Materials
The chemical compositions of LM6 and LM25 aluminium
alloys used are given in the Table-1. Finally the component
has to be cast by any one of the two alloys; hence both the
alloys are considered in the study for the purpose of
simulation and experimentation.
Table-1: Chemical Composition.
%Wt. LM-6 LM-25
%Si 12.72 6.29
%Mg 0.08 0.34
%Fe 0.72 0.70
%Mn 0.20 0.33
%Cr 0.02 0.01
%Cu 0.29 0.05
%Pb 0.03 0.02
%Zn 0.21 0.05
%Ni 0.03 0.01
%Al 85.6 92.1
Large quantities of sand and permanent mould castings are
made from Al-Si alloys such as LM6, LM25 etc., in LM25
(Al-7Si-0.3Mg) small additions of magnesium induce
significant age hardening through precipitation of Mg-Si in
the aluminium matrix. Aluminium-Silicon alloys have high
fluidity because of the presence of relatively large volumes
of the Al-Si eutectic. The advantages of Al-Si alloy castings
are high resistance to corrosion, good weldability and
moreover, silicon reduces the coefficient of thermal
expansion.
5. METHODOLOGY
The actual production is quite complicated as castings are
associated with many defects. To produce good quality
castings it is essential to identify the defects, understand the
causes for the defects, find the remedies, and work on it to
eliminate them. Defects in the produced components are
identified as solidification shrinkage, cracks, unfilled riser

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and incomplete mould cavity. One of the reasons for
solidification shrinkage is improper riser dimensions
meaning that there is no available liquid metal in the riser to
feed the casting when it is solidifying. Cracks are due to
stresses developed during solidification as complete metal
mould is acting as a chill. Unfilled riser and incomplete
mould cavity occurs due to the loss of fluidity in the metal
because of chilling effect of the mould and air entrapment.
Molten metal is loosing heat while flowing through the
gating system, mould cavity, risering system and solidifying
in the way before completely filling the mould. Hence to
eliminate these defects and produce quality castings, the
experimental trails are to be performed either by varying the
process parameters like pouring temperature, pouring time,
alloy type and preheat temperature; or by redesign the gating
and risering system; or maybe both.
The experimentation in this paper is explained in two stages.
In the first stage experiments are conducted by varying the
process parameters and practical experiments are compared
with virtual trials. In the second stage virtual trials are
carried to determine the correct riser dimensions suitable for
the casting. The results of simulations are then compared
with that of experimentation for the purpose of validation.
5.1 Stage-1
In first stage, few test castings are produced by changing the
process parameters to check whether the defects are
eliminated or getting minimized by change in process
parameters. The Gravity die casting process parameters
include: casting material, mould material, pouring
temperature, pouring-time, preheat and die coating.
Aluminium alloys LM6 and LM25 were used as casting
materials; the material for the mould was Low Carbon Steel.
The literature suggests that the optimum pouring
temperature for gravity die casting is 720o
C, hence all the
castings were poured at 720o
C (et. al. Zaid). Pouring time
was approx. 3 seconds based upon shape and size of the
casting. The mould was preheated at 200o
C and 250o
C.
Sodium silicate + chalk powder is used as die coat as it was
commonly used in industries. The practical experiments
were conducted by varying parameters as given in the
Table-2.
Table-2: Process Parameters & Expt. Results for Stage-1.
Trail
Material
(Al-alloy)
Preheat
(o
C)
Expt. Results
(Sound/Defective)
1 LM6 200 Defective
2 LM6 250 Defective
3 LM25 200 Defective
4 LM25 250 Defective
5.1.1 Simulation Studies
After the experimental trial the virtual trial was conducted in
SOLIDCast simulation software by using the same
parameters as used in experimentation. Casting materials
used are LM6 and LM25; the material for the mould was
Low carbon steel. The Heat transfer coefficients (HTC) used
for the alloy type LM 6 and LM25 in virtual trails are given
in the Table-3:
Table-3: Heat Transfer Coefficients for virtual trials.
HTC
Between
LM 6
(W/m2
-k)
LM 25
(W/m2
-k)
Casting - Riser 56784 41832
Casting - Ambient 8.5 6.4
Casting - Mould 1135.5 1777
Riser - Ambient 8.5 6.4
Riser - Mould 709.8 588
Ambient - Mould 45.4 45.4
3D models of the cast product, gating system, and risering
system are created using SolidWorks CAD software and
STL files from CAD system are imported in SOLIDcast
program. If CAD files are not present, 3D shapes can also be
created within SOLIDCast. After model is imported, it is
meshed to run a simulation using SOLIDCast and
FLOWCast. Moreover, the mold is created automatically
around the casting when mesh is generated. Sample images
of meshed casting, mould, SOLIDCast simulation and
FLOWCast simulation are shown in the Figures 3-6.
Fig-4: Meshing of Mould
Fig-5: SOLIDCast Simulation

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Fig-6: FLOWCast Simulation
After completion of the simulation, results are
plotted using CastPic function. CastPic is a function that can
create a detailed, three-dimensional image of the casting
with result data plotted onto the image as a range of colors.
This function can show the whole casting or section the
image to show internal details in the casting. Sample plot
using hotspot feature is shown in the Figure-7.
Fig-7: Plotting of results for Hotspot.
After the simulation, the results can be interpreted using
following features:
 Solidification Time
 Critical Fraction Solid Time
 Material Density Function
 Temperature Gradient
 Cooling Rate
 The Niyama Criterion
 Hot Spots
 Custom Criterion
In this study Material Density Function is used to
analyze the defects. Material Density criterion is a result
of a calculation in which the contraction of the casting
and resulting flow of liquid metal is taken into account
during solidification. Areas having metal removed due to
feeding liquid metal to other areas of the casting will have
lower material density number. The material density
function is a number varying between 0 and 1; 0
meaning that the metal has been completely drained from
that part of the casting while 1 indicates completely sound
metal. It is found that, in general, values in the range
between 0.995 or 0.990 and below are areas of detectable
shrinkage porosity in castings. Using the material density
function results are plotted and compared with that of
experimental castings in the Figures 8-11 shown below.
5.1.2. Stage-1 results
Fig-8a, 8b: Trial-1, Material LM6, Preheat 200o
C

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C
C
C

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From the above Figures 8-11, it is apparent that
LM25 is showing good results when compared to LM6. By
preheating the die, in LM25, cracks are completely
eliminated, riser is getting completely filled, there is no air
entrapment or incomplete mould cavity, but the
solidification shrinkage still exists exactly at the bottom of
the riser. Hence it is confirmed, that in this case, change in
parameters alone is not successful to eliminate all the
defects completely. But it can be concluded that the
software results are in validation with experimental results,
as both experimental and simulation results are in good
agreement with each other.
5.2. Stage-2
Process parameters were varied in the first stage in
order to minimize the defects but it was not successful as all
the components produced are defective. Therefore, in the
second stage gating / risering system is to be varied and
simulated for elimination of defects. From stage-1
simulations it is apparent that the metal is flowing smoothly
in the gating channels and the defects are happening near the
riser. Hence the design for risering system with LM25 alloy
is only considered for further study.
The preliminary design of die was having rectangular
riser. The rectangular risering system is leading to a quick
solidification pattern and insufficient central flow, which
prematurely closing the edges and was leaving the last filled
areas fall into the inner portion of the casting. This resulted
in a high probability of air entrapment in the casting and the
risering system design was considered not proper for the
part. Hence the existing riser shape was considered to
change from rectangular to cylindrical. The cylindrical riser
is modeled in SolidWorks and imported in SOLIDCast to
run the simulation and observe the results. Likewise the
numbers of virtual trials are performed by varying riser
dimensions in SolidWorks and importing and simulating the
results in SOLIDcast. The simulation results are plotted for
varying riser dimensions and are shown in Figures 12-17.
5.2.1. Stage2 results
Fig-12: Riser Diameter 12mm

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From the simulation results it is apparent that the riser with
diameter 35mm is not producing any defects and is suitable
for the casting. Hence die is machined accordingly with the
simulation result to check the quality of the produced
castings.
5.3. Experimental Validation
The gravity die casting mould is machined on
milling machine using 35mm diameter milling tool (Figure-
18). After machining the riser dimension of 35mm (Figure-
19), the mould is taken to the foundry shop for testing by
melting and pouring the molten metal into the modified die.
It is observed that produced castings are sound and have no
defects (Figure-21). Hence Zero defect casting has become a
reality owing to Computer Aided Design of Casting.
Fig-18: Die during machining
Fig-19: Die after machining
Fig-20: Final simulation result

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Fig-21: Finally sound casting
6. CONCLUSIONS
It can be concluded that the casting simulation has
become a powerful tool to predict the location of defects and
eliminate them by visualizing mould filling, solidification
and cooling. It can be used to trouble shoot the existing
castings or to develop a new castings without shop-floor
trails by using fewer resources which reduces cost and time
to market.
Modification in risering system design by changing
riser dimensions eliminates the defects from the cast part.
Simulation showed that the new design provides a
homogeneous mold filling pattern and the last filled area
was transferred from part to the riser. The results of
simulation are in good accordance with that of
experimentation. The defects like solidification shrinkage,
cracks, unfilled riser and incomplete mould cavity are
completely eliminated from the casting. So, zero defect
casting has become a reality owing to computer aided design
of casting, by using which it is possible produce casting
right first time and every time.
REFERENCES
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Analysis”, Prentice-Hall India, ISBN-81-203-2726-8,
4th
print, 2007.
[2]. B.Ravi, “Casting Simulation and Optimization:
Benefits, Bottlenecks, and Best Practices”, Technical
Paper for Indian Foundry Journal, January - 2008,
Special Issue.
[3]. M. Piyapong, “Solidification Modeling of Iron Casting
Using SOLIDCast”, Master diss., West Virginia
University, Morgantown, West Virginia, 2007.
[4]. T. R. Vijayaram, S. Sulaiman, “Numerical Simulation
of Casting Solidification in Permanent Metallic
Molds”, Journal of Materials Processing Technology
178, (2006) 29-33.
[5]. D. Kakas, P. Terek, “Mould Filling Improvement by
Computer Simulation and Parameter Variation”,
copyright Faculty of Engineering - Hunedoara,
Romania.
[6]. A. P. Wadekar1, B. A. Ahire, “Die Casting Defect
Analysis & Experimental Validation for Compressor
Housing”, IOSR Journal of Mechanical and Civil
Engineering (IOSR-JMCE), ISSN(e) : 2278-1684,
ISSN(p) : 2320–334X, PP : 55-61.
[7]. Adnan S. Jabur, “Prediction of Shrinkage Cavities in
Aluminium-Silicon Sand Casting”, Journal of Thi-Qar
University, Volume 5, March, 2010.
[8]. S.G.R. Brown, J.A. Spittle, and J.D. James, “The
Mould Filling and Solidification of a Complex
Foundry Casting”, JOM-e, January, 2002.
[9]. D. R. Gunasegaram, D. J. Farnsworth, and T. T.
Nguyen, “Identification of Critical Factors Affecting
Shrinkage Porosity in Permanent Mould Casting Using
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Experiments”, Journal of Material Processing
Technology, P-209-219, March, 2008.
[10]. V. R. Maniar, Bharat Gupta, Abhisek Chaubey et., al.,
“The Application of Solid Modelling, and Casting
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[11]. T. Nandi, R. Behara, S. Kayal, A. Chanda, G.
Sutradhar, “ Optimization of Riser size of Aluminium
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BIOGRAPHIES
Mr. Syed Ferhathullah Hussainy received
his B.E. in Mech. Engg. (1992), and M.E.
in Prodn. Engg. (1997) from O.U., India.
He has total of 21 years of Teaching
experience and presently working as Prof.
and Dean in M.J.C.E.T., India.
Mr. M. Viquar Mohiuddin received his
B.E. in Mech.-Prodn. Engg., from O.U.,
India (1999), and M.S. in Adv. Mfg.
Engg., from SHU, U.K. (2002). He has
total 12 years of Industrial and Teaching
experience.
Dr. P. Laxminarayana received his B.E.
in Mech. Engg. (1989), M.E. in Prodn.
Engg. (1995), and Ph.D. in Mech. Engg.
(2003) from O.U., India. He has total 23
years of Teaching experience. Presently
working as Prof. in M.E.D., O.U., India.
Dr. A Krishnaiah, received his B.E. in
Mech. Engg. (1994), M.E. in Prodn.
Engg. (1998) from O.U., India. He did his
Ph.D. from IIT Madras (2006), Post
Doctoral Research from South Korea
(2008). He has total 17 years of Teaching
experience, 37 publications, & Presently
working as Prof. in M.E.D., O.U., India.
Dr. S. Sundarrajan, done his graduation in
Mech. Engg. from TCE, India, P.G. and
Ph.D. in Industrial Metallurgy from
IITM. He edited 2 Engg. Hand books,
published over 80 Tech. papers and
guided 7 PhD’s. Prior to joining NIT-T,
he was with missile programme of
DRDO for over 30 years and received
mentoring by Dr. A. P. J. Abdul Kalam.

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A practical approach to eliminate defects in gravity die cast al alloy casting using simulation software

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