OPTIMIZATION IN GREEN SAND CASTING
PROCESS: A REVIEW
Sarita Dansena1, HarishKumar Patel2
Abstract— Among the mechanical exercises sand giving
process still remains a role as a standout amongst the
most perplexing and uncertain exercises. Because of the
mind boggling relationship between throwing abandons
and green sand properties, it is basic to control numerous
green sand attributes that impact throwing quality.
Conventional system for experimentation in view of skill
and experience has numerous hindrances, for example,
being nonsystematic, drawn out, slip inclined and
prerequisite for long terms of experimentation. There is a
need to supplant this customary way to deal with produce
higher quality throwing items inside sensible times of time
improving utilization of insights, computerized reasoning
information procurement neural systems and information
mining apparatuses. This paper broadly surveys
distributed research on green sand throwing methodology.
The impacts of riser outline, gating framework,
embellishment sand, oxidation and deformity of throwing
amid warmth treatment, machining stipend, and so on.,
on the conservative production quality castings were
looked into. Deciding the ideal procedure parameter
setting will fundamentally enhance the mold yield, yield
proportion of metal, abbreviate producing period, spare
vitality and asset, lessen contamination, and enhance the
aggressiveness of undertakings.
Keywords- Green sand casting, gating system, riser, mould
yield, casting yield etc.
adaptable courses of action in assembling in light of the fact
that it is utilized for most metals and combinations with
high softening temperatures, for example, iron, copper, and
nickel. The sand throwing procedure comprises of emptying
liquid metal into a sand mold, permitting the metal to set,
and afterward splitting endlessly the sand mold to evacuate
a throwing item. The throwing item can then be machined
to evacuate surface blemishes or to include new highlights
by standard machining
strategies,
for
example,
granulating,
turning,
processing, and cleaning. The sand utilized as a part of the
sand throwing methodology is regularly fortified with
bentonite and water to shape the sand. The utilized sand can
be reused commonly by adding new material to the arrival
sand amid reconditioning.
fundamentally.
The
initially
automated
embellishment lines comprised of sand slingers and/or jar
press gadgets that reduced the sand in the cups. Resulting
mold taking care of was mechanical utilizing cranes,
derricks and straps. After center setting the adapts and drags
were coupled utilizing aide sticks and clasped for closer
precision. The molds were physically pushed off on a roller
1.
INTRODUCTION
transport for throwing and cooling. The trim lines can
The expression "Green sand throwing" alludes to an item
accomplish an embellishment rate of 90 to 100 sand molds
cemented in green sand mold. Green sand molds are
every hour. In 1962, Dansk Industri Syndikat A/S
arranged with mixtures of silica sand, holding dirt and
concocted a jar less trim process by utilizing vertically
water. Sand castings are created in specific manufacturing
separated and poured molds. defects or to include new
plants called foundries. More than 70% of every single
highlights by standard machining routines, for example,
metal throwing are delivered through a green sand throwing
granulating, turning, processing, and cleaning. The sand
procedure. Albeit there are numerous new propelled
utilized as a part of the sand throwing methodology is
advances for metal throwing, green sand throwing stays a
ordinarily fortified with bentonite and water to form the
standout amongst the most generally utilized throwing
sand. The utilized sand can be reused commonly by adding
procedures today because of the minimal effort of crude
new material to the arrival sand amid reconditioning.
materials, a wide assortment of castings regarding size and
structure, and the likelihood of reusing the trim sand. The
sand throwing procedure is a standout amongst the most
Today embellishment lines can attain to a trim rate
of 550 sand molds every hour and requires one and only
checking administrator. Greatest befuddle of two mold parts
is 0.1 mm. Centers need to be set with a center veil instead
configuration and PC supported building are joined for riser
of by hand and must hang in the mold rather than being
plan as of late.
determined to separating surface. Castings are innovative
items which are coordination of materials, metallurgy,
2.1 OPTIMAL RISER DESIGN
throwing, warmth treatment, welding, estimation, and so
Lots of examines on the optimality of riser configuration
on., Although some new throwing advances thrive, for
have been completed for its importance. In view of the
instance, lost froth throwing and pass on throwing, the
limited component examination of cementing warmth
green sand throwing innovation is still the most essential
exchange, a shape enhancement method for riser outline was
and famously utilized strategy for large scale manufacturing
completed by Zhang et al. [5] by utilizing a global
of little and medium weight throwing. While foundry
convergence strategy.
designers have entry to a mind-boggling measure of test
work did in the course of the most recent hundred years or
more, numerous outcomes repudiate one another, and
inapplicable to genuine throwing Most foundries still take a
few weeks to add to a throwing, dismissal level will be
high
and
the
yield
will be
imperfect. Accordingly
acknowledgment of productive and conservative production
of
throwing
is
critical
headed
straight
toward
Shen et al. [6] achieved a programmed improvement
framework for riser without impedance of human. The
framework could naturally discover the imperfections of
throwing part, create riser's base size as the item work and
the
necessity
of
methodology
as
the
requirement
circumstance through examination of results by throwing
reproduction programming, and utilize the numerical
streamlining calculation taking into account temperature
modernization.
inclination to focus beginning riser parameters, and after that
2.
MEASURESFOREFFICIENTAND ECONOMICAL
MANUFACTURE OF QUALITYCASTINGS
further enhance it till the best plan of riser is gotten.
Li et al. [7] proposed a molecule swarm calculation to focus
Prof.
John
Campbell's
'Casting
rules"
were
developed over a lifetime of work in the foundry and later
research at the University of Birmingham. A great part of
the exploration work concentrated on the impact of melt
taking care of at the different stages on the quantity of
imperfections made and the impact on the unwavering
riser parameters, for example, riser width, neck breadth and
tallness, and the outcomes demonstrated that the riser
volume diminished by 11.77% contrasted with that of
modulus calculations. These routines above are of
improvement approaches through
the
multi- update of the
risers of known position and size.
quality of throwing therefore made [4].
The nature of castings is influenced by the
Shouzhu et al. [8] proposed another bolstering separation
innovations utilized as a part of each generation step, for
standard utilizing throwing reproduction
example, example outline, example plate use, bolstering
relationship between the Niyama basis and radiographic
and
throwing
gating
framework,
sand
innovation,
center
soundness.
The
displayed
base on a
standards
are
configuration and its arrangement, softening and pouring,
demonstrated to give longer nourishing separations in most
warmth treatment, repair welding, and so forth.
throwing circumstances.
Risers are utilized for anticipation of shrinkage
deformities (Figure 2). Then again, they diminish the
utilization rate of metal and amplify the cooling time of
castings after hardening also. Subsequently, fitting riser size
Tavakoli el al. [9, 10] proposed an improvement
methodology named the feeder development strategy. The
technique is made out of three stages: determination of the
riser neck association point, development of the riser neck
needs to be intended to fulfill nourishing with the littlest
and the riser development. Amid the development arrange,
volume. Customarily Caine's technique, Modulus strategy
the riser topology is enhanced bit by bit until fulfilling some
and Naval exploration lab strategies were utilized for riser
plan. Underway, customary techniques and PC helped
predefined criteria. These days, its application is just
restricted to the situations where one and only riser is
needed. Hence, further augmentation to defeat this limit can
for gating design recently. But potential exists for further
be considered as the viewpoint of future research.
optimization of gating system.
Tavakoli et al. [11, 12] likewise introduce a strategy named
Mcdavid et al [14] displayed, a technique for the optimal
transformative topology advancement which is inversed to
design of flow in foundry throwing apparatus frameworks.
the development system. Mayur sutaria et al. (13) displayed
The philosophy is taking into account a novel, completely
work to register sustain ways and problem areas by joining
expository configuration affectability plan for transient,
level set technique based sharp interface and food way show.
turbulent, free-surface flows. The filling phase of the casting
The model is in view of the arrangement of vitality and level
process is displayed by unraveling the time- arrived at the
set comparison in strong and fluid with Stefan condition on
midpoint of manifestation of the Navier–Stokes comparisons
the interface. What's more, for development of the holding
through a turbulent blending length model, in conjunction
temperature of riser before complete cementing, the surface
with the volume-of-fluid (VOF) technique for displaying the
covering materials on risers are additionally noteworthy for
free surface.
riser outline through fortifying the efficiencies of holding
temperature and an exceptionally exothermic riser is
likewise connected in foundries.
Nesterova [15] presented a mathematical model of kinetics
of filling the model during Casting by Gasified Models
based on an analysis of thermal destruction of cellular
polystryne.
Jeoan Kor et al. [16] giving outline is figured a role as a
multi-target enhancement issue with clashing targets and an
intricate inquiry space. An improvement strategy utilizing
multi-objective transformative calculation (MOEA)
is
produced to overcome such complexities. A casing work for
incorporating the streamlining strategy driven by information
for the outline assessment is then introduced. The proposed
Figure 1:-shows the foundry process division into branches
and areas of a modern foundry
enhancement system is connected to the gating arrangement
of a sand throwing. It is demonstrated that the MOEA
techniques yield great results and gives more adaptability in
choice making.
Niels Skat Tiedje and Per Larsen,[17] examined melt
stream in four diverse gating frameworks intended for the
generation of brake plates tentatively and by numerical
demonstrating. In the examinations, molds were fitted with
glass fronts and melt stream was recorded on feature. The
Figure2. Shrinkage defect
feature recordings were contrasted and the displaying of melt
stream in the gating frameworks.
2.2 OPTIMAL GATINGDESIGN
Fu-Yuan Hsu et al. [18] researched the L-formed
intersections in running and gating frameworks utilized as a
The gating design and ingate position (Figure 3) plays
part of aluminum gravity throwing. Utilizing computational
an important role in the quality and cost of a metal casting.
demonstrating, a rule for building two geometries of L-
Due to the lack of theoretical procedure to follow, the
intersections was created. The successive filling profile of
design process is normally carried out on a trial and error
fluid metal along L- intersection was affirmed by constant
basis. In production, traditional methods and computer-
X-beam feature of an aluminum composite sand throwing.
aided design and computer aided engineering are combined
[26] simulated both the technology of low pressure
permanent mold casting and the bending test. The shrinkage
defects and residual stresses were predicted by computer
methods. An overview is presented on modeling of alloy
casting solidification and heat treatment by Jianzheng et al.
[27] Abdullin. [28] presented a work on modeling a complex
problem on the stress- strain state of a casting in the
software
Pro CAST.
It describe the main steps in the
calculations, the initial data, and the results obtained from
calculation of the filling of the mold, the crystallization of
Figure3. Average Metallostatic height‘H’ in
three types of ingate position
SIMULATION
SOLIDIFICATION
DEFECTS
2.3
the alloy, and the stresses in the casting
Charles Monroe [29] presented a work on development on
hot tear indicator based on the physics of solidification and
OF MOULDFILLING,
AND
CASTING
deformation. This indicator is derived using available data
The defects such as shrinkage, crack and deformation were
the key topics in castings production. Once the shrinkage
from computer simulation of solidification and solid
deformation.
deformation and the cracks appear in castings, it will cost
Yinggan Tang et al. [30] proposed an effective segmentation
much fees and time for repair welding. The casting might be
method for the detection of typical internal defects in
discarded if these problems are severe. The stress is one of
castings derived for an X-ray inspection system.
the main factors that cause deformation and cracks in
castings during casting, heat treatment,
machining, and
service. Deformation, tendency to hot tearing, and residual
2.4.OPTIMIZING PROCESS PARAMETERS OF
SAND MOLD
stress in casting could be predicted by numerical simulation
Sand mold is one of the key factors that directly
of the thermal and stress fields in casting during casting and
affect the production rate and product quality. Metal casting
heat treatment, which is helpful
the
industries are actively involved to reduce the scrap rejection
foundry technology, reducing the defects caused by stress-
and rework during the manufacturing process of the
strain, ensuring the shape and size of casting, and improving
components. To achieve this, the production concerns must
the service life of casting. Malcom
follow the quality control procedures
for
optimizing
blair
et
al
[19]
correctly
and
describes recent work to predict the occurrence and nature
perfectly without any negligence. Timely implementation
of defects
of the modified techniques based on the quality control
in casting and determine their effect on
performance. Vijayaram et al. [20] presented a work on
research is a must to avoid defects in the products.
numerical simulation of casting solidification in permanent
metallic molds.
Y.Chang et al [31] investigated the properties of green
molding sand and a new model is developed to evaluate the
Sulaiman et al.[22,23], describes the simulation and
flowability of molding sand compact in this study
experimental results of thermal analysis in sand casting
experimental results are presented to show how the
process. Simulation model of 2-ingate mould and 3-ingate
flowability of silica sand is affected by water content,
mould of sand casting are developed. They also presented a
bentonite and sea coal content.
work on simulation of metal filling progress during the
casting process. Karunakar et al.[24] presented a work on
prevention of defects in casting using back propagation
neural networks. Griffiths et al. [25] proposed a method for
determining inclusion movement in steel castings by
positron emission particle tracking (PEPT). Ogorodnikova
Charnnarong Saikae and Sermsak Wiengwisetto
[32] optimize the proportion of bentonite and water added
to a recycled sand mold for reducing iron casting waste
using the following analysis techniques: a mixture
experimental design, response surface methodology, and
propagation of error. The effects of variation in bentonite
analysis of variance (ANOVA) and optimization project
and water added to a recycled sand mold on the properties
were used to investigate the FEM results.
of the molding sand were investigated.
Noorul Haq et al. [38] demonstrated optimization of carbon
The iron castings were measured qualitatively using
dioxide casting process parameters by using Taguchi’s
a stereo microscope and its surface hardness was also
design of experiment method. Senthil kumara et al. [39]
measured using a Rockwell hardness testing machine. The
presented a work on Process factor optimization for
research concluded that the optimal proportion was 93.3
controlling pull-down defects in iron casting. The identified
mass% of one-time recycled molding sand, 5 mass% of
factors were analyzed using ‘Design of Experiments’
bentonite, and 1.7 mass% of water having a green
approach. ‘Signal-to- noise’ ratio was estimated.
compression strength of 53,090 N/m2 and a permeability of
design factor values were estimated from the ‘signal-to-
30 A.F.S.
noise’ calculations. ANOVA analysis was done for robust
Parappagoudar et al. (33) utilized back-propagation
Robust
design factor values.
neural network (BP-NN) and genetic-neural network (GANN) to model green sand mold system in forward
2.5 OPTIMIZATION OF HEAT TREATMENT
mapping (to predict the responses from the known input
parameters) as well as reverse mapping (to predict the set of
input parameters for a set of desired outputs).
B.
Surekha
et
al.
(34)
2.5.1. Reduction of burns-off
The metal materials will be oxidized at high
presented
multi-
temperature
and
oxidizing
atmosphere
during
heat
objectiveoptimization of green sand mould system using
treatment. The material corrosion will result in addition of
evolutionary algorithms, such as genetic algorithm (GA)
de-scaling
and particle swarm optimization (PSO). In this study, non-
performance. The burning loss of materials during heat
linear regression equations developed between the control
treatment is about 3%–4% of total casting mass at present.
factors (process parameters) and responses like green
Decreasing the burning loss of materials is an efficient
compression strength, permeability, hardness and bulk
method for improvement of the output ratio of metal. The
density have been considered for optimization utilizing GA
oxidation of steel during heat treatment is closely related to
and PSO.
the furnace temperature, time in the furnace, and furnace
process
and
deficiency
in
economic
atmosphere. [40]
An optimization technique for process parameters
of green sand casting based on the Taguchi parameter
design approach is proposed by Guharaja et al. [35] and
also by Sushil Kumar et al [36]. The process parameters
considered are green strength, moisture content, pouring
temperature, and mould hardness vertical and horizontal.
An attempt has been made to obtain optimal level of the
process parameters in order to yield the optimum quality
characteristics of the casting.
2.5.2. Deformation control
The casting volume and shape will change, and
even distort under the action of thermal stress and phase
transformation during heat treatment. The final shape of
casting is affected by thermal strain, elastic strain,
traditional
plastic
strain,
phase
strain,
and
phase
transformation- induced plastic strain. It is necessary to
optimize heat treatment for controlling the deformation of
Zhang [37] presented a work on optimizing casting
casting, which will reduce or avoid the possible repair
orthogonal
welding and shape correction work, and also decrease the
method, The influence and signification of casting
machining layer thickness and time greatly affects the
parameters on the solidification process of steel ingot were
production cost and the casting quality in production.
discussed based on the finite element method (FEM) results
Large machining allowance will result in extension of
by orthogonal experiment method. The range analysis,
machining period and cost [41].
parameters
of
steel
ingot
based
on
•
2.6. Efficient cooling in the casting process
•
Reducing oxidation and controlling deformation of
casting in heat treatment
Dimensional control and reducing machining
allowance
•
Efficient sand reclamation and recycling
cooling rate after solidification and shorten the cooling
•
Foundry mechanization
period in mold
•
Data acquisition system and automatic control
•
Efficient Shake out.
The production rate in the casting process is related
to the solidification rate. The production period for sand
casting is long enough, Therefore, it is critical to increase the
To realize efficient
cooling
some
kind of methods were proposed.
Shi et al developed a method by using a fluidization
plate and for improvement of the cooling rate of riser after
solidification, a method mixed the mist cooling, and wind
cooling was developed by Kang et al. [40]. In addition, the
The significance of optimization may be one or more of
the followings
• Quality casting
• Improving output ratio of metal
methods for increasing the cooling rate of casting still need
• Saving energy
to be developed for improvement of production efficiency,
• Saving resources
for example, rapping of sand mold, local shakeout, and
• Increasing manufacture rate
increasing shakeout temperature
• Increasing enterprise benefit
3.
CONCLUSIONS
Product and process design is the soul to realize efficient
• On-time delivery schedule
• Reducing pollution
and economical manufacture of quality sand castings. There
4.. REFERENCES
is great progress of green sand castings production, but it is
still far away from optimal design. There is still huge
1.
potential for the improvement of casting design and process
control technology. Computer science, artificial intelligence
New age publication, New Delhi 2010.
2.
techniques and statistical process control methods have been
Processes”,
Tata
Mc
Graw-hill,New
Delhi,2008
3.
industry especially to reduce the defect percentages to
reasonable levels.
Campbell,”Principle of Manufacturing Materials
and
utilized for solving various problems in manufacturing.
Similar tools can be used to solve the problems in casting
Rao T.V.“Metal casting principle and practice”,
Ravi B.,”Metal casting : Computer aided design and
analysis”, Pearson Education, New Delhi,2012
4.
John Campbell, “Ten rules for good castings”.
Journal of Modern casting, 1997, Volume (4),
The main areas for optimization in green sand casting
pp36-39.
process for efficient and economical quality casting are:
5.
Zhang D,Zhang W H, Li F G ,”Application of shape
•
Optimizing and reducing riser mass
•
Optimizing gating system
•
Simulation of mould filling and solidification to
avoid casting defects
•
Optimizing process parameters of sand mold
Technology”,Wuxi: proceeding of china foundry
•
Optimizing pattern plate utilization
week,2008,447-452.
•
Optimization of mould yield
•
Optimum use of pads and chills.
on
•
Optimization of melt composition and temperature
2005,54(2):176-178.
•
Efficient cooling during solidification
optimization based on numerical simulation in
feeder design”.2004,Foundry,53(2):129-132,
6.
Shen X, Chen L L, Zhou J X , “Automatic optimal
riser design in steel casting process based on CAE
7.
8.
Li Z, Mao Z, Li W. “Optimal design of riser based
particle
Shouzhu
Ou
swarm
et
algorithm”.
al,”Development
Foundry,
of
New
Feeding- Distance Rules Using Casting Simulation:.
The New Rules”.
Metallurgical And Materials
18.
for gravity casting” Journal of Materials Processing
Transactions B, 2002,Volume 33B, 741.
9.
Rohallah
Tavakoli
,”Automatic optimal
casting
10.
,
Parviz
feeder
Davami
design
in
steel
Technology 209 (2009) 5736–575016)
19.
process”, Comput. Methods Appl. Mech
thermal history of sand casting process”, Journal of
R. Tavakoli Q
250.
P. Davami,. “Feeder growth: a
processes”,
20.
Struct Multidisc
casting solidification in permanent metallic molds”,
Journal of mechanical processing Technology,
Rohallah Tavakoli Q
2000,100: 224-229.
optimization with
approximation
Parviz Davam, “Optimail
SIMP
method
of nonlinear
21.
and
heat
transfer
in sand casting, Journal of Material Processing
Technology,2004, 155-156:1723-1726
22.
Malcom blair et al ,“Predicting the Occurence
R. Tavakoli Q P Davami, Optimal “riser design in
and effects of defects in castings” , Journal of the
sand casting process with evolutionary topology”,
Minerals, Metals and Materials Society,2005
23.
S.
Sulaiman,
A.M.S.
Hamouda,
S.
Abedin,
Mayur sutaria, Vinesh H. Gada, Atul Sharma,
M.R. Osman “Simulation of metal Flling progress
B.Ravi, “Computation of feed path for casting
during the casting
solidification using level-set-method”, Journal of
Material
material processing technology 212(2012)1236-
156:1723-1726.
1249
24.
process”,
Processing
Journal
of
Technology,2004,155-
D. Benny Karunakar & G. L. Datta ,”Prevention
Robert
M. Mcdavid And Jonathan A. Dantzig,
of defects in castings using back propagation neural
”Fluid
Flow
networks”,International
Modeling,
in
Casting
Validation,
Rigging
and
Optimal
Systems:
Design
“,Metallurgical And Materials Transactions B,
N.
V.
Nesterova, and
A.
G.
25.
Ermilov,
“Mathematical Model of Kinetics of Filling the
Model during Casting by Gasified Models”,Russian
journal
of
advance
manufacturing technology, 2008,39:1111-1124.
Volume 29b, 679,1998
W. D. Griffiths
et al., The determination of
inclusion movement in steel
castings by positron
emission
(PEPT).Journal
particle
tracking
of
material science, 2008, 43: 6853-6856.
26.
E.O.Ol’khovik,V.V.Desnitskii,
and
Journalof Non ferrous metals,2010,Vol.51, No.1, pp
R.A.Molchanyuk, “”Interaction between Casting
52-58.
and Mold during Solidification,
Jean Kor , Xiang Chen and Henry Hu; “ Multi-
0967-0912,Steel
objective optimal gating and riser design foe
translation,2007,Vol.37,No.5 pp 422-424.
metal casting” IEEE multi-conference on system
and
17.
Modelling
experimental investigation of solidification process
Struct Multidisc Optim, 2009, 38: 205- 214.
16.
A.M.S.Hamouda
Poisson
202.
15.
S.Sulaiman,
I:
equation”, Struct Multidisc Optim , 2008,36 : 193-
14.
T.R. Vijayaram et al. “Numerical simulation of
Optimization, 2009, 39:519-530.
riser design in sand casting process by topology
13.
the
A.M.S.Hamouda,”Modeling
Material Processing Technology 2001,113: 245-
gravity casting
12.
S.Sulaiman,
Eng,2008 ,921-932.
new method for automatic optimal feeder design in
11.
Fu-Yuan Hsu et al. “A multiple-gate runner system
control
27.
Saint Petersburg, Russia, July 8-
in
Jianzheng Guo and Mark Samonds, “Modeling of
Alloy Casting Solidification, Journal of the
10,2009
Minerals”,
Niels Skat Tiedje and Per Larsen “Investigation of
2011,Vol.63 No.7,
the Stability of Melt Flow in Gating Systems”
ISSN
28.
Metals
and
Materials
Society
,
D. Abdulli “Modeling a Complex Problem On
The Minerals, Metals & Materials Society and
The Stress-Strain State Of A Casting In The
ASM International 2010
Software Procast”, Metallurgist, 2011,Vol.55, Nos
7-8
29.
Charles
Monroe,
“Development
of
Christoph
a
hot
tear
Beckermann,
indicator
for
steel castings” Materials Science and Engineering:
Volumes 413–414, 15 December
Journal
40.
2005, Pages
Processing
Hai-Liang
YU et
al
economical manufacture
;
“Efficient
of
steel
and
castings,
Material science”, 2020,4(4):332-338.
Yinggan Tang et al. “Application of a new image
41.
Shi H Y, Wang Y G Fluidization plate for cooling
segmentation method to detection of defects
of
in castings”
201338071
Int J Adv Manuf Technol (2009)
43:431–439
31.
Material
Technology,2009,209:554-560.
30-36.
30.
of
42.
Y. Chang , H. Hocheng
“The Flowability Of
sand
during
casting.
Chinese
Patent,CN
Kang J, Huang T Y,Hu Y Y,” A method
for acceleration
Bentonite Bonded Green Molding Sand” Journal of
heavy
Material Processing Technology 113,(2001) 238-
200910218834.9
and
steel
equilibrium
asting”
cooling
Chinese
of
,Patent,
24439)
32.
Charnnarong
Saikaew,
Sermsak
Wiengwiset,
“Optimization of molding sand composition for
VII. BIOGRAPHIES
quality improvement of iron castings” Applied Clay
33.
Science 67-68 (2012) 26–31
Sarita Dansena Department
Parappagoudar, M. B., Pratihar, D. K., and Datta,
of mechanical Engineering
(Diploma), Government
Polytechnic Jashpur
(Chhattisgarh).
G. L. “ Forward and reverse mappings in green
sand mould system
Applied
34.
using
neural
networks”.
Soft Computing, 2008, 8, 239–260.
B.Surekha & Lalith K. Kaushik & Abhishek K.
Panduy & Pandu R. Vundavilli & Mahesh B.
Parappagoudar, “Multi-objective optimization of
green sand mould system
using
evolutionary
algorithms”, Int J Adv Manuf Technol (2012) 58:
9-17
35.
Guharaja et al. “Optimization of green sand
casting process parameters by using
method”, International
journal
of
taguchi’s
advance
manufacturing technology, 2006,30:1040-1148.
36.
Sushil Kumar & P. S. Satsangi & D. R.
Prajapati, ”Optimization of green sand casting
process parameters of a foundry by using Taguchi’s
method”. Int Journal of Advance Manufacturing
2011,55: 23-34.
37.
Zhang et al., “Optimizing casting parameters of
steel ingot based on orthogonal method “Journal of.
Cent. South Univ.Tech.15 (s2)2008, 296-300d,
38.
Haq et al , “Parameter optimization of CO2
casting process by using Taguchi’s Method”,
InternationalJour, Des Mfg 2010, 3: 41-50.
39.
B. Senthikumar et al,”Process factor optimization
for controlling pull down defects in iron castings”,
Mr. Harish Kumar Patel
is working as a Lecturer &
HOD
,Department
of
Mechanical
Engineering,
Government
Polytechnic
Jashpur(Chhattisgarh), India