Solidification Analysis of Investment Cast Knee Joint Implant

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International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882

Volume 4, Issue 1, January 2015

Solidification Analysis of Investment Cast Knee Joint Implant

Mrs. M. S.Shirke1, Prof. (Dr.) V.D.Shinde

2

1Student, Textile and Engineering Institute, Ichalkaranji, Maharashtra,2Professor, Textile and Engineering Institute, Ichalkaranji, Maharashtra

ABSTRACT Nowadays in manufacturing field, time and money

saving has become a prime importance because of toughcompetition. In investment casting process, themanufacturer has to go through many trials to a sound

cast component. Main objective of investment casting process is to form intricate shapes. Knee joint implant is

one of the intricate shapes which are planted in thehuman body when the knee joint fails. Thus knee joint

implant because of its intricacy is manufactured byinvestment casting. To avoid number of trials,simulation software will be used to achieve defect free

implant casting. Main objective of this project is toknow the solidification behavior in the knee implant cast

component with different process parameters. Use ofsimulation software reduces the trial cost and helps todesign correct method with minimizing melt scrap ofdefective castings. The key process parameters underinvestigation are pouring time, pouring temperature,

mould preheating temperature and firing temperature.The output criteria such as material density, CriticalFraction Solid Time (CFST), Niyama criterion andtemperature gradient were studied for solidificationanalysis of knee implant cast component.

Keywords - Modeling software, investment casting, simulation, process parameters, Niyama criterion.

1. INTRODUCTIONCasting, one of the economical manufacturing processes

used in industries, is a complicated process, whichinvolves considerable metallurgical and mechanicalaspects [1]. The rate of solidification governs themicrostructure largely, which in turn controls themechanical properties like strength, hardness,

machinability, etc. The location, size and shape of riserin a casting depend on the geometry of the casting,mould design and thermal properties of metal, old andother process parameters [2]. Wrong designed riserresults either defective casting with shrinkage cavity or

lower yield, as directional solidification has notachieved. There are number of casting simulation

software are developed and are used in foundry

worldwide. The application of casting simulationsoftware’s are also increasing day to day in Indianfoundry as it essentially replaces or minimizes the shop

floor trials to achieve the desired internal quality at thehighest possible time[3]. Recently, due to thedevelopment of computer technology, an effort is doneto predict casting defects directly as a consequence of

the physical phenomena that are involved. A modelingapproach based on an improved description of the

physical processes has become a more realistic, practica

and straightforward option. Shrinkage related defectsresult from the interplay of phenomena such as fluid

flow, heat transfer with solidification, feeding flow andits free surfaces, deformation of the solidified layers andso on.

2. CASTING SOLIDIFICATION

SIMULATIONComputer simulation provides a clear insight regarding

the location and extent of internal defects, ensuring

castings. It requires a 3D CAD model of the methodlayout (with mold cavities, cores, feeders, and gating

channels), proper setting of boundary conditions for eachvirtual trial, and correct interpretation of results. In the

past the foundryman have strived for ways to improvethe casting process and eliminate the defects thatoccurred in the castings by trial and error and past

experiences. The time needed to produce a particular product is a time-consuming process. Problems occurred

in the casting may only be solved through trial and errorScientists throughout the years have studied the scienceof casting and metallurgy and developed theories andmathematical models to explain the properties of metalswhile going through the solidification process

Simulation programs were developed from thesemethods which are useful in predicting how the castingwill come out. Defects and problems can be discovered

before the actual casting is cast avoiding costly tests to prevent the problems. Fig.1 shows the steps involved in

simulation process.



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I.

Solid Modeling of part (3 D modeling of Gating,feeding and component part)

II. Pre-processing (assigning simulation thermal parameters)

III. Processing (processing simulations iteratively)IV. Post-processing (For analyzing temperature ,

shrinkage, thermal gradient etc.,)

Fig.1: Steps for simulation process [1]

3. SOLID MODELINGSolid modeling permits engineers to visualize

and understand the part’s actual appearance and functionwithin an assembly by displaying the critical relationship

of part layouts, interference, and clearances. The mass property data (weight, center of gravity, moments of

inertia, etc.) of parts and assemblies can be obtained.This eliminates the need for hand calculations toestimate these values from drawings or sketches. The

mechanical integrity of the design may be investigatedusing various finite element methods to determinestructural, thermal, kinematics, and vibration properties.

These capabilities allow the engineer to design, analyze,and iterate on the CAE software using the same solid

model. In solid modeling basically first a 3 dimensionalmodel is prepared and then it is converted to STL fileformat. STL file format is the loaded in to other softwarewhere the simulation process is carried out. Fig.2a

indicates the solid model of knee implant and meshing isindicated in Fig.2b. In first pattern layout Fig.3a the gateand runner system width dimensions are kept as those ofthe length of the component, the number of patternformed are 18. In the second pattern layout Fig.3b to tworunners are added parallel to each other thus we get 16

cavities of the component. In the third pattern layoutFig.3c, to increase the yield runner width is reduce thus

we have 24 component planned in this. Finally in the last

pattern layout Fig.3d we can see the combination of thirdand second pattern layout, with the same width that of

the third pattern layout, number of cavities reaches to 24Above pattern tree are formed with different designs to

increase the yield. Simulation is carried out on each ofthe layout and final design is suggested.

Fig.2a. knee prosthesis Fig.2b.Meshed knee prosthesis

4. PRE-PROCESSINGIn Pre-processing, the input parameters are

assigned for the simulation process. Process parameter

which affects investment casting product includes mould preheating temperature, firing temperature, pouringtemperature, pouring time, shell thickness. InSOLIDCast software input parameters are 3 dimensionamodel in binary STL format, assigning materials for cast

and mold part, meshing details like node size, pouringtime, pouring temperature, room temperature. In thisstudy the input parameters are same for all the type of



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pattern tree. The 3 dimensional model is drafted in adrafting software Pro-E and is converted to STL file

format so as we can use that file in SOLIDCastsimulation software. Input parameters related to casting

material considered are, detailed in table-I. We need toassign ambient temperature and pouring time which is

32.222˚C and 23 second respectively, pouring time isdefined as the time required for filling the mould cavity

by molten metal. Pouring time input is considered by

experimental method. For knee joint implant materialused is SS 316 L with chemical composition is listed intable.2Material properties of SS316 are excellent in a range ofatmospheric environments and many corrosive media -

generally more resistant. Good oxidation resistance inintermittent service to 870°C and in continuous service

to 925°C. Excellent weldability by all standard fusionand resistance methods, both with and without filler

metals. 316L stainless steel is also easier to machinecompared to 316 stainless steel due its lower carboncontent. Material temperature factor is taken by the

software as we select the material in it.

Table-I

Sr.

No.

Input parameters values

Parameters related to casting material

1. Thermal Conductivity 16.258W/m-k

2. Specific Heat 502.08 J/Kg-K

3. Density 8025.018Kg/m^3

4. Initial Temperature 1454.444˚C 5. Solidification

Temperature1371.111˚C

6. Freezing Range 27.778˚C

7. Latent Heat Of Fusion 302172J/Kg

Parameters related to mold material

9. Mold Material invest shell

10. Initial Temperature 871.111˚C

11. Thermal Conductivity 1.73 W/m-K

12. Specific Heat 836.8J/Kg-K

13. Density 2082.34Kg/m^3

14. External Heat TransferCoefficient

8.512W/m^2-K

15. Temperature In Mold 1000˚C

Table-II

SR.

NO.

COMPOSITIONS PROPORTION

1. Fe <0.03% C

2. Cr 16-18.5%

3. Ni 10-14%

4. Mo 2-3% 5. Mn <2%

6. Si <1%

7. P <0.045%

5. PROCESSINGSolidification analysis: Solidification plays an

important role in formation of defect less casting

Directional solidification is important to avoid defectslike shrinkage, misrun. Directional solidification can be

achieved with the help of correct gate and runnerdimensions. Non directional solidification can beobserved with the hot spots present in the casting. By

observing the solidification step we can determine thedefect in each pattern layout. Solidification time shows

the time, in minutes, at which each node in the castingreached full solidification, i.e., the solidus point. In al

the types of pattern layout the colour shades rangingfrom yellow to blue denotes the temperature range andsolidification. Blue colour denotes that part of materiawill be solidified first and yellow shows the hotness ofthe material and will be solidified last. The node size

which is 1.5mm common for all is input for thesolidification analysis. Viewing a plot of SolidificationTime shows the progress of solidification through thecasting. This can help to locate isolated areas of moltenmetal within the casting and to get a general idea of

progressive solidification in various areas of the castingPT-16:- In fig. 4.a layout we can observe directionalsolidification so we can get sound component. Thesimulated time taken was 25.701 minutes. PT-18: - Infig.4.b we can observe that the part is solidified first and

then the rest gating and runner system. By neatobservation the entrance point of gate get solidifies firswhere we can see hot spot. Thus there is possibility of

shrinkage defect. The simulated time taken was 32.301

minutes. PT16-24 fig.4.c we can observe the same problem as that of PT18-24, left side middle row is notfilled, due to design error. The simulated time taken was27.312 minutes. In PT18-24 fig.4.d we can see the

second line where the material gets solidifies in the gateso the cavity is not filled. So we have fewer yields in thiscase. This effect is due to less thickness of runner. Thesimulated time taken for PT18-24 was 28.381minutes.



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6. POST-PROCESSINGPost- processing indicated the output of the simulation

process. Thus the simulation is carried out and the resultis generated for all the type of pattern layout. Insimulation process filling of molten metal and its

solidification process is carried out [3]. Results are plotted on the base of criteria like solidification time,

critical fraction solid time, temperature gradient, coolingrate, material density, niyama criterion, FCC criterion.

6.1

Material DensityThe Material Density Function is the result of a

calculation in which the contraction of the casting, andresulting flow of liquid feed metal, is taken into account

during solidification. Areas that have metal removed dueto feeding liquid metal to other areas of the casting willshow up as having lower Material Density numbers. In

this way, potential shrinkage can be predicted. Materialdensity measures macro porosity in the casting. Value

ranges from 0 to 1. Lower values are worse. Usually, theCritical Value is around 0.99 to 0.995 (values below this

indicate visible shrinkage).

Fig.5. material density at particular point on each layerof different pattern layouts

The Material Density Function is a number that can varyfrom 0 to 1. It is a measure of how much of the metalremains at each point in the model. A value of 0 means

that the metal has been completely drained from that part

of the casting; a value of 1 indicates completely soundmetal. The Material Density Function therefore should

be interpreted as, if value is equal to 0 % metal then wehave 100% porosity, value if 0.909% metal then we have

10% porosity, if value ranges near 0.99% metal then 1% porosity is observed. If metal content value is nea1.0100% ten we can say that 0% porosity is observed. Ingeneral, we have found that values in the range of .995-.990 and below are areas of detectable shrinkage



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porosity in castings. The Material Density Function is ameasure of macroporosity and is most useful in ferrous

castings. In Fig 5.a show the cut plane of each layer of pattern layout (PT18) which contains 6 component

cavities. In this at each point of the component we havematerial density as 1. In Fig 5.b pattern layout (PT16)

we have 2 layer. At each layer we have 8 component, weget density value 1 at each point.Fig 5.c show the cut

plane of each layer of pattern layout (PT18-24) and have

8 components. In first layer we have 8 components and 1value for material density is obtained. In the secondlayer we have all the values as 0 which denotes that thereis no material filled in the lower side of the layer here wecan get 4 components. In the third layer again we have

density as 1 for all components. Fig 5.d show the cut plane of each layer of pattern layout (PT16-24) and have

8 components. In first layer we have 8 components and 1value for material density is obtained.In the second layer

we have all the values as 0 which denotes that there is nomaterial filled in the mould cavity. So in this total layerthe material solidifies in between and all 8 cavities

remain unfilled. In the third layer we have again materialdensity value as 1 for all the components.

6.2

Critical Fraction Solid Time

Critical Fraction Solid Time records the time, in

minutes, for each part of the casting to reach the CriticalFraction Solid Point. This is the point at which the alloyis solid enough that liquid feed metal can no longer flow.Therefore, for judging directionality of solidification,

and whether any isolated areas have formed within thecasting that cannot be fed. Critical Fraction Solid Timeis generally a better indication than Solidification Time.Plotting Critical Fraction Solid Time gives a goodindication of whether any contraction that forms will beable to be fed by liquid feed metal. The areas that appear

as isolated pools of molten metal will not be able toreceive feed metal from the risers if any contractionshould occur during cooling and solidification [5]. In

below all types of pattern layouts the isolated material isspecified. The isolated material in the pattern layout

shows the further shrinkage possibility in the casting. In

fig. 6.a which is the first pattern tree design with 18components has less isolated material in the parts. Alsoin PT16 (Fig.6b) we can derive the observation that theisolated material is less in proportion. In third type of

pattern tree (fig. 6.c) the unfilled area is more and wehave less isolated material. In last pattern tree type

PT16-24, more percent of isolated material is observed.

Fig.6. PT diagram at initial value of CFST

6.3

Temperature Gradient

Temperature Gradient is a measure of how much change

in temperature there is as you go from point to pointwithin a casting. A high temperature gradient means that

there is a large temperature change within a shortdistance within the casting. A low temperature gradientmeans a small change in temperature from one point to

the next. Temperature Gradient is calculated at eachnode within the casting as that point hits the Niyama

Point on the cooling curve. Temperature Gradient can be used to get an idea of whether there was good or poor

directional solidification at various points within thecasting. The disadvantage of Temperature Gradient isthat each casting ends up with a different range ofvalues, depending on geometry, and it is hard tocompare one casting with the next .In first pattern

layout(Fig.7.a) we can see a low temperature gradientranges from 0 to 46.66 which means variable differencein the temperature . In second (Fig.7.b)we have the samevalues to observe. In third pattern layout (Fig.7.c) thevalue range is near to 0 value thus there is very less

temperature difference. In fourth pattern layout (Fig..d)we can see the middle layer has maximum value wherethe metal is not filled while other layer are filled.



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Fig. 7. Temperature Gradient variation in each layer of pattern layout

6.4

Niyama CriterionThe Niyama Criterion is a function based on

Temperature Gradient and Cooling Rate. The criterionwas developed by Dr. Niyama, a Japanese researcher

studying shrinkage prediction in steel. Niyama foundthat the Temperature Gradient divided by the square rootof the Cooling Rate corresponded to the presence ofshrinkage porosity in steel castings. The lower the value,

the higher the probability of shrinkage. If this numberis1 or above there is little or no shrinkage porosity in thecastings. Niyama has been used extensively forshrinkage prediction in castings. The Niyama Criterionhas been extended to alloys other than steel. Niyama is

basically a prediction of directional solidification. Poor

directional solidification is represented by a value of 0,good directional solidification by higher values.Thegeneral idea is that the lower the value of Niyama, theworse the potential for shrinkage. A value of 0 is thehighest probability of shrinkage, and as the value

increases, the severity of the probable porosity

decreases. Above the critical number, probability of porosity is low. Niyama plots need interpretation,

because they give low values in many areas wheretemperature gradients are low but shrinkage might not belikely, such as at the centreline of thin-wall areas and atthe dividing line between the feeding areas of two risers.Also, Niyama is based only on heat transfer and does not

take the effect of gravity into account. The function is: N = Gs / √T

Where, N = value of Niyama function; Gs= thermalgradient [°C/cm]; T = cooling rate [°C/s]. [7]

First two pattern layout (Fig.8.a&b) shows high valuefor the niyama criterion. The third pattern layou

(Fig.8.c) shows most highest value among all. Thefourth pattern type(Fig.8.d) has the lowest values for

niyama criterion.

Fig.8: Niyama function value variation for different pattern tree

Results are plotted with the help of the output fromabove studied criterion.

Criterion PT18 PT16 PT18-24 PT16-24

Solidification

time

In minutes

32.197 25.297 26.911 27.372

Material

density in %

1 at most

thickest

area

0.95 at

most

thickest

area

0.90 at

most

thickest

area

0.89 at

most

thickest

area

Criticalfraction solid

time

Less Hotspot

More hotspot

observed

Not much

separatematerial is

observed

More hospot seen

Temperature

gradient range

are ºC/cm

0-46.66 0-46.66 0-20 0-140

Niyama

Criterion80-90.66 80-90.66 88-90.66 70-80



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7. CONCLUSIONIn the current project SolidCAST simulation software isused to study the solidification behavior in knee implant

casting.The key process parameters under investigationare pouring time, pouring temperature, mould preheatingtemperature and firing temperature. The output criteria

such as material density, Critical Fraction Solid Time(CFST), Niyama criterion and temperature gradient werestudied for solidification analysis of knee implant castcomponent. The highlights of casting solidificationsimulation analysis as follows:

1. Casting simulation technology has become anessential tool for casting defect troubleshooting andmethod optimization. It enables quality assurance

and high yield without shop-floor trials, andconsiderably reduces the lead-time for new castcomponents under development.

2.

By simulating the different casting layouts byvarying process parameters, the casting yield,

quality and cost of different design will be studied.The process options which optimal parameters wereselected to for actual pouring to achieve the soundcasting right at the first time.

3. The importance of the process input parameters

affecting the performance parameters such asmaterial density,CFST, temperature gradient &

niyama criterion can be effectively used forsolidification analysis.

REFERANCES1 B. Chudasama, 2013“Solidification Analysis and

Optimization Using Pro-Cast”, International Journal of Research in Modern Engineering and Emerging Technology, Vol. 1, 4, , pp. 09-19.

2 T. Sahroni, S. Sulaiman, B. Baharudin, 2011“Design and Simulation on Investment CastingMold for Metal Matrix Composite Material” ,

Applied Mechanics and Materials, Vols. 66-68, pp.1676-1681.

3 A. Rajic, E. Desnica, S. Stojadinovic, 2013 “Development Of Method For Reverse Engineering

In Creation Of 3d Cad Model Of Knee Implant” , Facta Universitatis Series: Mechanical Engineering, Vol. 11., pp. 45-54.

4 S. Sivarasu, S. Prasanna, L. Mathew, 2011 “ReverseEngineering Vs Conceptual Design Principles in theMaking of Artificial Knee Models”, Trends

Biomater. Artif. Organs vol. 25(2), pp. 60-62.5

H. Hermawan, D. Ramdan and Joy R. P. Djuansjah,2011“Metals for Biomedical Applications”,

Biomedical Engineering - from Theory to Applications, pp.411-430.

6 J. Fischer-Buhner, Advances in the Prevention ofInvestment Casting Defects Assisted by Computer

Simulation, the Research Institute for Precious Metals (FEM), Germany.

7

N. C. Huat, S. Hassan, S. Sabudin, S. Ariffin, 2005“Defect Analysis of Investment Casting UsingComputer Prediction” , International Conference on

Information and Communication Technology, 9-10June,pp.35-44.

8

K.Carlson, C. Beckermann, 2008 “Use of the Niyama Criterion To Predict Shrinkage-RelatedLeaks in High-Nickel Steel and Nickel-Based Alloy

Castings” , 62nd SFSA Technical and OperatingConference, pp.1-15.

Solidification Analysis of Investment Cast Knee Joint Implant

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