Casting Simulation – Best Practices

Transactions of 58th IFC, Ahmedabad (2010)

Casting Simulation – Best PracticesDr. B. Ravi

Professor, Mechanical Engineering DepartmentIndian Institute of Technology Bombay

Mumbai - 400 076E-mail: [email protected]

AbstractGuidelines for effective implementation and the best practices for efficient use of casting simulation technologyare presented here. These are based on a comprehensive review of about 200 industrial projects carried out bysimulation consultants associated with IIT Bombay. The projects are of two types: (a) quality or yield improvementof existing castings, and (b) rapid development of new castings. The guidelines cover all major metals and processes,and deal with five stages of simulation projects: data gathering, methods design, numerical simulation, methodsoptimization, and project closure. Major concerns: how to obtain accurate results, reduce total lead time, andensure data security are addressed, and illustrated with industrial examples. This compilation is expected to beuseful to consultants taking up such projects, as well as to foundries already using or planning to use castingsimulation technology.

Key Words : Casting, computer-aided design, methods, simulation, optimisation, quality, yield.

1. Introduction

Once considered a luxury, computer-aided design andsimulation of castings is becoming an integral part offoundry operations, necessary to achieve consistentlyhigh quality castings with optimal yield1. New andexpanding foundries are planning casting simulation asan essential facility like melting and moulding units.Others are outsourcing this task to either simulationcentres or to independent consultants. A recent surveyof 215 foundries all over India2 revealed that use of CAD/CAM and simulation reduced the average lead time forfirst good sample casting by 30%: from 10 weeks to 7weeks, and halved the average rejection rate: from 8.6%to 4.1%. Other reported benefits included higher yield,cost reduction and customer satisfaction (Fig. 1).

Casting simulation can, however, be an agonizingexperience for novices. The programme may not acceptthe user inputs, other data may not be comprehensibleor available, the computer can hang up or take a verylong time to produce the results, and the results maynot match shop floor observations. Even regularconsultants sometimes experience such problems. Apoor knowledge of solidification physics and inadequatetraining in simulation technology becomes a handicap in

successful utilization of simulation technology. Thus afoundry setting up a simulation facility may end up onlyshowcasing it to visitors. This sets a poor example forothers, who delay their learning curve of exploring thisimportant tool. As the simulation programmes get moresophisticated every year, it becomes even more difficultto adopt and adapt the technology in their foundries.

In this paper, we present guidelines and the bestpractices for effective implementation and efficientutilization of casting simulation technology. This is basedon our experience of guiding over 50 foundries inimplementing casting simulation, and supervising over200 casting simulation projects for others (Fig. 2). Anotherrich source of knowledge is from interactions with 1200senior and middle-level foundry engineers who attendedour professional course on ‘casting design and simulation’every September since 2000, and ten casting simulationclinics conducted all over India during 2008-20093.

We first outline situations which necessitate simulation(not all castings need to be simulated). Then guidelinesfor establishing a casting simulation facility are presented.The simulation protocol (step-by-step procedure) isdescribed next, highlighting all important inputs requiredalong the way. Best practices for obtaining accurate


Fig. 1 : Benefits and concerns of IT applications in Indian Foundry Industry

Fig. 2 : Some of the casting simulation projects (left to right : Steel, SGI, CI, and Aluminium)


results, minimizing the total lead time, We first outlinesituations which necessitate simulation (not all castingsneed to be simulated). Then guidelines for establishing acasting simulation facility are presented. The simulationprotocol (step-by-step procedure) is described next,highlighting all important inputs required along the way.Best practices for obtaining accurate results, minimizingthe total lead time, and ensuring data security arepresented. We conclude with future developments in thisarea, and how foundries can prepare themselves to benefitfrom the same. Although most of our experience is withAutoCAST, the casting methods design and simulationsoftware developed at IIT Bombay, the guidelines havebeen generalized to cover all simulation programmes,metals, processes, casting shapes and sizes.

2. When is the Simulation Necessary?

Casting simulation should be used when it can beeconomically justified for at least one of the followingthree reasons:

• Quality enhancement by predicting and eliminatinginternal defects like porosity

• Yield improvement by reducing the volume of feedersand gating channels per casting

• Rapid development of a new casting by reducingthe number of foundry trials

The corresponding cost benefits can be estimated.

• Quality improvement reduces the (avoidable) costsassociated with producing defective castings,including their transport, and warranty or penalties.

• Yield improvement reduces the effective meltingcost per casting, and increases the net productioncapacity of the foundry (without adding melting ormoulding units).

• Faster development of castings through virtual trialseliminates the wastage of production resources, andimproves the rate of conversion from enquiries toorders, giving foundries an opportunity to select highervalue orders.

Not all defects can be accurately simulated. Solidificationshrinkage defects (macro, micro and centerlineshrinkage) can be predicted fairly accurately. Flow-relateddefects (cold shuts and blow holes) can be simulated

but may not always match actual observations. Coolingstress related defects (cracks), micro-structure andmechanical properties are difficult to simulate, andextensive calibration experiments may be needed forpractical use.

From the above it is clear that it is advisable to start withsolidification simulation, which requires relatively lessinputs, gives fairly reliable results, has a high impact onquality (shrinkage accounts for nearly half of all defects)as well as yield (feeder size optimization), and thus givesa high benefit to cost ratio.

There are at least three other secondary (long term)benefits, which accrue after using simulation for sometime (few months to years). The corresponding costbenefits are relatively more difficult to estimate, and thesereasons are not normally used for justifying setting up asimulation facility.

• Manufacturability improvement by part re-design inconsultation with OEM

• Methods knowledge management by re-usingsimulation projects

• Brand image enhancement by using the simulationfacility as a marketing tool

High capacity foundries (over 5,000 tonnes/year) with alarge number of jobbing orders (more than 100 per year)require in-house casting simulation facilities, preferablyone for each foundry unit (Fig. 3). Two or more mediumcapacity foundries, who have fewer jobbing orders, canshare common facilities. Small foundries with less thanten new projects per year should set up co-operative

Fig. 3 : Types of casting simulation users based on various factors


simulation centres in their cluster, or approach castingsimulation consultants.

New, large and complex-shape castings in aluminium,steel and SG iron for demanding applications (such asautomobile, machine tool, aerospace, and medical)usually have a higher rate of rejections and penalties.Even SME foundries producing such castings shouldconsider having their own simulation facility.

3. Setting up a Simulation Facility

Three types of resources are required for setting up acasting simulation facility: hardware, software, and‘human-ware’. The choice of the hardware depends onthe software. The choice of the software depends on therequirements of the foundry (discussed above) andpersonnel available for running the software. This is bestascertained by a benchmark project.

The benchmark should be an older casting with a knownhistory of problems (internal defects). The software shouldbe used to exactly model various methods layoutsattempted in the foundry, and the simulated resultcompared with the known location of defects. The softwareshould be able to correctly predict all major defects. Falsepositives (simulated defect not observed in actual casting)may be acceptable, but there should be no false negatives(simulation did not catch an observed defect). Thesimulation should be carried out in front of the methodsengineer who would be running the software later, so he

can evaluate the user interface, various inputs requiredby the programme, and the time and skill involved.

The most popular casting simulation programmesavailable in India include: AutoCAST-X, MAGMA,ProCAST and SolidCAST. Some of these are availableon hire (monthly, quarterly or annually), which is usefulfor benchmarking. Major modules of a typical castingsimulation software are shown in Fig.4 (not all modulesare available in all programmes).

The programmes employ different methods for castingsimulation are shown in Fig.5 :

(i) Finite Difference Method (ex. SolidCAST),

(ii) Finite Volume Method (ex. MAGMASoft),

(iii) Finite Element Method (ex. ProCAST), and

(iv) Vector Element Method (ex. AutoCAST).

While the underlying physics is the same, they differ interms of the discretisation (division) of space and timecontinuum, handling of various material properties (ex.latent heat), boundary conditions (metal-mould interfacialheat transfer coefficient), and the numerical techniqueemployed.

The FDM and FVM use cubic or brick-shaped elements,FEM uses tetragonal or hexagonal elements, and VEMuses a combination of cubic and pyramidal elements.The FEM can model the casting shape more accurately(using fewer elements), but may require manual effort to

Fig. 4 : Different modules in Casting Simulation System


correctly generate the element mesh, which cansometimes take more time than the computation itself.

A separate 3D CAD programme is needed for solidmodeling of as-cast parts, the main input for simulationprogrammes. Popular CAD programmes includeAutoCAD, CATIA, I-DEAS, Pro-Engineer, SolidWorks,SolidEdge, and UG-NX. Most of them offer similarfeatures, and their prices have reduced owing to a largemarket and fierce competition. The main differenceremains in terms of user interface. Since solid modelingcan take a lot of time, especially for complex-shapecastings, it is best to acquire one which has an intuitiveuser interface, and familiar to the tool designer workingin the foundry. Solid models can also be requested fromthe OEM customer, or outsourced from a local CAD/CAMagency, reducing the load on the foundry designer.

Computer hardware power has significantly increased overthe last few years. Today, notebook computers are fasterthan desktop computers available 10 years back. Still,coupled simulation (flow + solidification + stress),especially for complex shape castings with thin wallsusing a fine mesh can take 40-80 hours. Multi-CPUcomputers with 4 GB or more RAM can reduce the

computation time, if the software is designed for parallelcomputation and addressing larger memory. A largedisplay monitor (19" or more) is useful for bettervisualization and discussions with team members.

A frequently asked question is: “How to select aSimulation Engineer for a foundry?”. The followingqualifications are required in increasing order: computerskills, knowledge of solidification physics, and methodsexperience. Computer skills are the easiest to developwithin a few days. Solidification physics can be learnt byreading and continuing education over a few weeks.Methods experience, however, takes years toaccumulate. Hence senior methods engineers having ascientific attitude and basic computer skills make thebest simulation experts. Ideally, at least 2-3 personsshould be trained in simulation, including a seniormethods engineer and a younger tool or CAD engineer.

4. Simulation Protocol (Flow Chart)

There are five distinct stages in casting simulationprojects: data gathering, methods design, numericalsimulation, methods optimization, and project conclusion(Fig. 6). Keys tasks and basic guidelines for each stageare described here.

Fig. 5 : User interface of popular casting simulation programmes (AutoCAST, MAGMA, ProCAST and SolidCAST)


Data gathering: This is the most important stage, sinceincorrect or incomplete data will lead to inaccuratesimulation and wrong conclusions. The problem must bedefined first, to ascertain the need and type of simulation.Here we focus on two types of projects: (a) quality oryield improvement of an existing casting, and (b) rapiddevelopment of a new casting. The following inputs arerequired before simulation:

• CAD model of casting: It should be a 3D solid (notsurface) model of the as-cast part. The model mustbe saved in an exchange standard like STL, whichcan be either in ASCII (text) or Binary format. Theformer is easy to verify manually, by opening it in atext editor.

• Cast metal properties: These include: density, thermalconductivity, specific heat, latent heat, volumetricshrinkage, viscosity and surface tension of cast metal,as a function of temperature. Properties of all majoralloys are usually available in the programmedatabase.

• Mould property and process parameters: Temperature-dependent values of density, thermal conductivity, andspecific heat of mould materials (including cores, chillsand insulation); and process parameters like pouringtime and temperature are needed.

• Methods design data: For quality assurance or yieldimprovement of an existing casting, the methodsdesign used in the foundry is required. This includesdetails about mould parting, cores, feeders, gatingsystem, cavity layout, and feed-aids. Photographs ofthe full casting and cut sections or radiographs showinginternal defects should be collected. In the case ofnew casting development, the suggested methodsdesign may be provided as a starting point.

Methods design and modelling: In this stage, themethods design is solid modeled to convert the as-castpart model into a 3D model of the mould containing partcavities as well as feeders, gating channels, cores andfeed-aids. If the methods design is not available, thenthe simulation engineer has to first design the aboveelements based on his experience and foundry practice.This requires both methods knowledge as well as CADskills. Also, after each round of simulation, the methodsdesign has to be modified based on the results, and thesolid model of the mould has to be created again. Inmost of the simulation programmes available today, thereis no provision of methods design or solid modeling ofmould elements.

Some have provision for solid modeling of simple shapesof feeders and gating channels. The AutoCASTprogramme includes both methods design and solidmodeling of mould elements, saving considerable timeand effort required by simulation engineers, and reducingthe possibility of related errors.

Numerical simulation: This is the main stage in castingsimulation, wherein some more critical inputs are requiredfrom the user. The first is the correct generation of FEMmesh. The element size must be optimal, and the meshmust cover the entire model without gaps. The secondset of inputs involves factors for various boundaryconditions, like the interfacial heat transfer coefficients.There are mainly three types of interfaces: metal-mould,mould-environment, and metal-environment (ex. openriser). Since the heat transfer can be by a combinationof conduction, convection and radiation, each with theirown constitutive equations, most simulation programmescombine them in equivalent forms, and use an overallheat transfer coefficient.

Fig. 6 : Major stages in Casting Simulation and Optimization


The simulation run depends on the functional module:solidification only, mould filling only, coupled filling +solidification, solidification + cooling + stress, etc, forthe specific metal and process. A separate post-processing module converts the data into colour-codedvalues for visualization of results. Temperatures areusually coded as yellow-red for high values and blue forlow values. This makes it easy for the user to interpretthe results to identify defects, for example hot spots andcold shuts.

Methods optimization: This stage involves improvingthe methods design to eliminate defects and improve yield(Fig. 7). For existing castings, the simulation results arefirst compared with observed defects to ascertain thecause of defects (undersize feeder, oversize neck,incorrect gate, small cavity gap, etc.). Then the methodsdesign (feeders and gating) is modified, solid modeled,imported into the simulation programme, and afternecessary pre-processing, the casting is simulatedagain. In extreme cases, even part design may need tobe changed (ex. padding) to eliminate the defectscompletely. Part, tooling and methods engineers cancollaboratively discuss and design the casting using web-based video conferencing, saving travel time and cost.

Project closure: After finalizing the methods design, allrelevant results need to be properly documented andarchived. This includes generating a methods report,analysis report, images of major steps and results. Aslide presentation or animation can be created forexplaining to others. All input and output data, as well asthe various reports are stored in a designated folder andbacked up. They are communicated to the team members

for implementation. Follow-up studies include checkingif the recommended methods design was implementedon the shop floor, and comparing the results of predictedand actual results. Any discrepancies must be noted inthe project file for future reference and corrective action(ex. customisation of database).

5. Getting Reliable Results

Computers are characterized as GIGO: garbage in,garbage out. Colourful pictures produced by simulationcan be misleading, if the inputs were incorrect. Bestpractices to ensure a close match between simulatedresults and actual casting are listed here.

• As-cast part model should be imported for simulation(Fig. 8). Machined part models (especially with drilledholes) will give wrong results. They need to beconverted to as-cast models by filling machinedfeatures, and adding various allowances: shrinkage,machining, draft.

• The as-cast part model should be represented by afine facetted water-tight surface. When part model fileis exported in STL format, curved surfaces areapproximated with a triangulated mesh. Coarsetriangulation truncates and reduces the castingvolume. An extremely fine triangulation can producedegenerate triangles (two edges merging with eachother), later leading to errors in FEM mesh generation.

• Optimal element size should be used for meshgeneration in FEM-based simulation programmes.Large elements may lead to instable computation andinaccurate results. The element size should be lessthan 50% of the minimum wall thickness. Also,

Fig. 7 : Quality and yield improvement of a ductile iron casting produced by Disamatic process


castings with large temperature gradients need to havea smaller mesh size for reliable results. If the castingmodel contains errors (such as missing faces anddangling edges), the FEM mesh cannot be generatedautomatically, and the errors or the mesh need to befixed manually. Some programmes (includingAutoCAST) use intelligent algorithms to fix the mesherrors automatically.

• The interfacial heat transfer coefficient is the mostimportant source of error in FEM-based simulationprogrammes. Its value changes depending on the castand mould materials (including feed-aids andcoatings), instant of time (from the beginning to endof solidification and beyond), shape of casting (internalversus external corners), location (top versus sideversus bottom surfaces), and process (ex. mouldheating, tilt pouring, etc.). The VEM-based simulationis less sensitive to inaccurate values of interfacial heattransfer coefficient.

• Thin wall castings produced in metal moulds shouldbe simulated using coupled filling + solidificationprogrammes for predicting flow-related defects likecold shuts and misruns. Separate simulation of mouldfilling and casting solidification is much faster, butrecommended only when solidification time is morethan twice the filling time, as in the case of thick wallcastings filled under gravity. Some programmes likeAutoCAST use the results of filling simulation to

automatically modify the initial conditions ofsolidification simulation, giving fairly accurate resultswith the advantage of much faster computation thancoupled simulation.

• Some elements in alloy composition can have asignificant effect on casting flow and solidificationcharacteristics. However, merely changing the alloycomposition will not simulate its effect, unless thecorresponding values of thermo-physical propertiesare also provided. This is not easy, since they needto be experimentally determined as a function oftemperature. Their effect can be reverse engineeredby comprehensive benchmarking (comparingsimulated and observed results).

• Simulation engineers often try to eliminate every singlemicro-porosity by providing bigger or additional feedersand feed-aids. This is not necessary if the qualityrequirements are not stringent, or if the defectiveregion is later machined with sufficient allowance.

• Finally, one must not jump to hasty conclusions ifthe simulated and observed results do not match. Inmost of such cases, what was simulated is not thesame as what was produced. Even minor alterationsin methods design implemented on the shop floor (forexample, neck size, gate position or pouringtemperature) can significantly alter the results.

Fig. 8 : Results of casting simulation with and without drilled holes can be quite different


6. Reducing the Lead Time

Foundries using a FEM-based simulation programmeoften complain that it takes more time than shop-floortrials. This defeats one of the key reasons for usingsimulation. AutoCAST reduces the total cycle time toless than one hour by using VEM and by automatingand integrating various steps. Best practices for reducingthe total lead time for simulation using either FEM – orVEM-based software, without loss of accuracy of results,are presented here.

• The size of part model file (in megabytes), not itsphysical size (in mm), affects the computation timefor mesh generation and simulation. More number offeatures (holes, pockets, bosses, ribs, etc.) and curvedsurfaces increase the model file size. Since eachcurved surface is approximated by a number oftriangles, even a small fillet can lead to a largeincrease in the file size (Fig. 9). Hence small fillets(with radius less than 20% of the local wall thickness),and tiny features (like engraved company name) canbe safely removed from CAD model, withoutsignificantly affecting the results (especiallysolidification).

• The computation can be speeded up by reducing thenumber of elements into which the casting and themould are divided. Large element size however, carriesthe risk of wrong results. Small elements, which alsorequire a corresponding smaller time step (in FDM,FVM and FEM), will lead to longer computation time.One way to reduce the total lead time is to use largersize elements for initial iterations, and a fine meshfor the final simulation to confirm the results.

• Another way to reduce the number of elements is touse the smallest mould enclosing the casting. Use oflarger mould will only increase the computation time(since the mould also has to be divided into elements)without any significant increase in the accuracy ofresults. We have found that the temperature gradientsin the mould become flat after a distance of 2-3 timesthe local wall thickness of a hollow casting. Hencethe maximum mould size will need be casting sizeplus 5-6 times casting wall thickness.

• In the case of symmetric castings requiring multiplefeeders, and multi-cavity moulds, considerable timemay be saved by modeling, simulating and optimizinga single feeder, or a single cavity first. Then this feederor cavity design can be duplicated to create a multi-feeder casting or multi-cavity mould. The total layoutwill need to be simulated and modified just once ortwice before freezing the final design.

• The total lead time can be significantly reduced byfewer iterations of methods design, solid modeling offeeders and gates, simulation and interpretation ofresults. The secret is to start with a ‘good-first’methods design, which will require only minor fine-tuning (instead of major re-design every time) to arriveat the optimal design. This can be achieved byconsulting an experienced methods engineer, or byusing a methods design programme before castingsimulation.

• Since the gating design often depends on feeders,the feeder design should be optimized first, followedby gating, thus saving significant time.

Fig. 9 : Removal of small fillets can significantly reduce the model file size by 50-90%


• Simulation engineers often start with oversize feedersto reduce the number of iterations. This may lead tosub-optimal yield. One should start from an undersizefeeder, and increase its size in steps until the hotspot in the casting shifts to feeder, with sufficientmargin of safety. This ensures faster optimization ofcasting yield. Both AutoCAST and SolidCAST allowautomatic optimization of feeders, saving valuable usertime.

7. Ensuring Data Security

Data related to casting simulation projects is typically ofthree types:

(a) Input data: The part solid model occupies the largestspace– a few megabytes to hundred megabytes ormore, depending on its complexity and triangulationduring export.

(b) Output data: The simulation results – temperatureor velocity at every element, are stored in one ormore files, which can occupy several hundredmegabytes space.

(c) Interpreted results and reports: These may begenerated by the programme or by the user,including screen images, animations, methodsreport, analysis report, and slide presentation; thesemay occupy only a few megabytes space (exceptanimations).

Whether simulation is carried out by the methods engineerof a company within its premises, or by an independentconsultant in a different location, data security is alwaysa major issue of concern. This is more so, if the foundryis developing the casting for a new product and has signednon-disclosure agreements with the OEM customer. Otherreasons for safe storage of casting simulation datainclude: its reuse for taking up similar projects in future,settling disputes in the event of defective castings, andtraining novice engineers in different methods designlayouts. Relevant best practices are listed here.

• Hundreds of simulation projects will accumulate withina few months, and it will become difficult to distinguishbetween them unless the projects and their files arenamed properly. This is a bigger challenge forsimulation consultants, who deal with different

foundries and handle a larger variety of projects. Forexample, many CAD programmes export their solidmodels with the same name (ex. PART.STL). Thisshould be renamed appropriately (ex. Cummins-Valve110.STL) to distinguish it from other models. Theproject file, methods report, analysis report, andpresentation slides should all be similarly named.

• The simulation computer should be equipped with ahigh capacity hard disk (500 GB or more). Still, if theoutput data per project is huge, then the hard diskmay overflow within no time. In that case, the outputdata may be deleted, and only the input data andreports may be saved.

• Another way to reduce space is to compress (zip) alldata files before archiving, which reduces its size toless than one tenth of the original. To open the project,the data files have to be unzipped, which iscumbersome if needed many times. AutoCASTautomatically compresses the project into a singlefile during saving, and unzips it during opening. Thismakes it easy to store, transfer, email, and open theproject any number of times.

• In case of confidential projects, the files can beencrypted or password-protected during compression,so that only the authorized user can open the files.

• If a simulation project is outsourced to an independentconsultant, then it may be explicitly mentioned if thedata is to be kept confidential, and for how long. Ifnecessary, a non-disclosure agreement may besigned between the foundry and the consultant. Incase of highly confidential castings, the consultantmay be requested to delete all relevant files after thecompletion of the simulation project.

• A good anti-virus programme and firewall should beinstalled to protect the computer and data againstmalicious attacks. A major source of virus these daysis from flash or pen drives. Simulation consultantsshould try to get the input data from their customerthrough e-mail or on a CD, which has lower chancesof virus proliferation.

• Data can be lost from deletion by oversight or due tohard disk crash. It should be regularly backed up in a


separate (portable) hard disk, which have become quiteinexpensive these days. This should be done at leastonce a week, preferably after every project in case ofsimulation consultants. The portable disk shouldideally be stored in a safe place, away from thesimulation computer to protect against fire or theft.

• No data storage system is completely foolproof. Hardcopies of the simulation project reports should beprinted out, and maintained in separate (physical)files.

8. Concluding Remarks and Future

Indian foundries have now understood the importance ofcasting simulation as an integral part of their operations.The penetration of casting simulation in the country isexpected to rapidly rise from its current level of 5-10%(including in-house facilities and outsourced services),though it might take a decade or more to reach nearlyfull penetration like in Germay and USA. A large numberof simulation engineers and consultants will be requiredto fill the gap.

The guidelines presented in this paper will help foundriesproperly plan and effectively implement casting simulationsoftware in their works. The best practices will helpsimulation engineers and consultants to properly adaptthe software depending on the requirements, and to makeefficient use of the simulation facilities.

Simulation programmes are continuing to evolve, andbecoming more powerful. Some of them now offerautomatic optimization of methods design (like feedersize). Multi-physics simulation (coupled flow, solidificationand stress), and microstructure and mechanical propertyprediction will become more reliable with new researchbeing carried out.

In future, casting simulation programmes will increasinglyuse Internet to provide software training, upgrading,license management and technical support. Time-basedlicenses will keep the initial software costs down.

Further developments will make it possible to performonline casting simulation and to consult experts througha web browser at a negligible cost. Online educationcontent will enable working foundry engineers to update,test and certify their knowledge of casting design andsimulation.

As simulation technology becomes even moresophisticated in the next few years, foundries who lagbehind will find it very difficult to catch up with the newworld. It is important to start with small steps, and startas early as possible, to ensure a gradual and comfortablelearning curve. In this context, professional bodies likethe Institute of Indian Foundrymen can promote castingsimulation centres in foundry clusters (such as the onein Belgaum). Leading technical institutes need to providecontinuing education and critical technical support. Indiantechnocrats who have taken IT to the entire world nowneed to ensure Indian industries too benefit from advancedIT tools, including CAD and simulation, to gain a globalcompetitive edge.

References

1. B. Ravi, Metal Casting: Computer-aided Design andAnalysis, PHI, New Delhi, ISBN: 81-203-2726-8,2005-2008, 4th Print.

2. B. Ravi, “Casting Simulation and Optimisation:Benefits, Bottlenecks, and Best Practices,” IndianFoundry Journal, 54(1), 47-52, 2008.

3. B. Ravi, “Bridging the Digital Divide in CastingSimulation Technology,” Proceedings of 57th IndianFoundry Congress, Kolkata, The Institute of IndianFoundrymen, 13-14 Feb 2009.

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Casting Simulation – Best Practices