Numerical Simulation of Spheroidal Graphite Iron Casting for Shrinkage Analysis- A Case Study

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1 Numerical Simulation of Spheroidal Graphite Iron Casting for Shrinkage Analysis- A Case Study Amol S. Karape PG Student, Department of Mechanical engineering Walchand College of Engineering Sangli, India Prof. Dr.K.H. Inamdar Professor, Department of Mechanical engineering Walchand College of Engineering Sangli, India Abstract- In sand casting process number of defects occur due to the wrong methoding of gating system, improper location of feeder and material properties. Spheroidal graphite iron is one of widely used material in automobile sector. Due to its superior mechanical properties of this material. Shrinkage is main problem in spheroidal graphite iron material. Production of this type of material need to simulate and visualize it for mould filling, solidification, cooling and internal defects. In this paper numerical simulation technique was used to study methoding related defects in sand casting. Numerical simulation of Casting is useful in getting high quality castings and reducing product cost and rejection. The numerical simulation trial was taken on existing system and results showed that shrinkage is on casting. After modification of gating system and proper location of feeder, the simulation results showed that new gating system with exothermic sleeve gives maximum efficiency as well as free from shrinkage defect. Also casting quality and yield was improved by 0.27%. Keywords Simulation; exthemoic sleeve; spheroidal graphite iron; casting defect; yield. I. INTRODUCTION Casting is a manufacturing process where a solid is melted, heated to proper temperature (sometimes treated to modify its chemical composition), and is then poured into a cavity or mould, which contains it in the proper shape during solidification. Thus, in a single step, simple or complex shapes can be made from any metal that can be melted. Spheroidal graphite irons have superior mechanical properties than a comparable grey iron with the same composition, because the carbon is in the shape of spheroidal graphite. This is achieved by inoculating low sulphur molten iron having low silicon content with magnesium or cerium or both, followed by addition of silicon. Subsequent cooling can produce a variety of matrix structures with ferrite and perlite being the most common. Compared to grey cast iron, Spheroidal graphite irons have higher ductility, tensile strength, modulus of elasticity. The productivity of ductile iron foundries engaging in mass production of castings for the automobile and other engineering sectors depends on the number of cavities per mold. A denser packing of cavities, however, results in slower heat transfer from adjacent cavities, leading to delayed solidification, possible shrinkage defects, and lower mechanical properties [8]. The development of computer technology, an effort is done to predict casting defects directly as a consequence of the physical phenomena that are involved. A modelling approach based on an improved description of the physical processes has become a more realistic practical and straightforward option. Shrinkage related defects result from the interplay of phenomena such as fluid flow, heat transfer with solidification, feeding flow and its free surfaces, deformation of the solidified layers and so on. [2]. II. LITERATURE REVIEW Vivek S. Gondkar and K.H.Inamdar [1] studied that, casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals is however, a very complex phenomenon that is difficult to simulate correctly by conventional computational technique. Use of simulation software, shrinkage defects optimized. Reis et al. [2] the process modeling of shape casting is geometrically complex and computationally very challenging. Besides the threedimensional complex shapes with multiple domains, the defects of interest to industry arise as a consequence of the interaction amongst a range of phenomena. Conventionally, the key phenomena and defect prediction are modelled through empirical relations applied to the simulation results. Such approaches are neither comprehensive nor reliable. The 3-D model that is capable of predicting the formation of shrinkage defects explicitly as a function of the interacting continuum phenomena, i.e. free surface flow, heat transfer, and solidification, in complex three-dimensional geometries which allows to identify the distinction between surface depression, surface connected cavities and internal cavities. Dr.B.Ravi [3] casting simulation has become a powerful tool to visualize mould filling, solidification and E-ISSN : Page 142

2 cooling, and to predict the location of internal defects such as shrinkage porosity, sand inclusions, and cold shuts. It can be used for troubleshooting existing castings, and for developing new castings without shop-floor trials. Simulation is the process of imitating a real phenomenon using a set of mathematical equations implemented in a computer program. lu et al. [4] concluded that, the casting defects that appear the inside surface of a wet-type cylinder liner (WTCL), such as macro-segregation and shrinkage porosities, and coarse-grained zone are major defects that cannot be entirely eliminated by machining in the range of machining allowance. The use pro-cast simulation analyze filling stage, casting temperature field mold field temperature simulation and Comparison of the results of the simulation and those of defect observation indicates that casting defects occur nearly at the same location. Shang et al. [5] studied micro-porosity in Al Si castings is one of the most detrimental defects responsible for high scrap loss in the production of commercial castings and severely prevents their widespread uses in many critical load bearing conditions. The damaging effects of microporosity are lack of pressure tightness, limited strength, variable fracture toughness and notable reduction in ductility as well as lower fatigue resistance. The use of criteria functions to predict quantitatively micro-porosity level holds promise. To date, an ideal criteria function has yet to be obtained. In the present work, micro-porosity distribution in three prominently used hypoeutectic Al Si alloys investigated. The prediction effectiveness of single solidification parameter and existing criteria functions was evaluated by correlating thermal data of simulation studies to experimentally obtained micro-porosity values. Narwade et al. [6] observed that Solidification simulation helps in locating shrinkage porosity directly which minimizes the casting defects and ultimately gives good quality of casting with proper size of the feeder. I. Svensson and T. Sjögren [7] concluded that, some of these models for microstructure and mechanical property prediction have been implemented into a commercial casting simulation software. The presented simulated casting is a ductile iron material and the critical parts of the simulation are cooling rate, nucleation of graphite (nodule count) and the restriction of ferrite by the chemical composition. Vasudev et al. [8] Casting simulation supported by experimental validation has been adopted to generate the values of the gaps for a ductile iron cube casting of 100-mm size produced in green sand mold. The minimum value of cavitywall gap was found to be 35 mm and cavity-cavity gap was 40 mm. The cavity-cavity gap for hollow castings is found to be approximately 0.75 times the casting wall thickness. A systematic procedure to determine the best combination of standard or custom size of mold and the number of cavities for maximizing the mold yield. III. METHODOLOGY The experimental work carried out at medium scale foundry, which producing cast iron and ductile iron casting. When casting defect analysis was done on casting major shrinkage defect was found. Due shrinkage defect, casting was failed during leakage testing. Simulation is the process of imitating a real phenomenon using a set of mathematical equations implemented in a computer program. In casting simulation the mould filling and solidification analysis is done by using an algorithm or program based on vector element based, to identify the hot spots and hence defects like shrinkage porosities, hot tears, cracks, etc.the casting model (with feeders and gates) has to be created using a solid modelling system and imported into the simulation program, further analysis. B.ravi [3] has suggested casting simulation and optimization methodology as shown in Fig. 1. A. Data collection Fig.1. Casting simulation-optimization methodology The following data have been collected for the selected casting. The 3D model casting shown in Fig.2 Fig.2. 3D model of Casting Selected Product: MMTD casting Grade of Metal : SG400/15 Unit weight of casting: 7 kg Sand material: Green sand Pouring temperature (Tp): 1425 ⁰C Feeding time: 12 seconds Density of metal: 7300 kg/m 3 E-ISSN : Page 143

3 Total weight of casting in mould box: 7 X4=28 kg Number of components poured in a box: 4 Size of box: 610X760 Cope: 300mm Drag: 200 mm Total dimensions of the mould box: 610 mm x 760 mm x 500 mm Type of gating system used: Pressurized gating system Shape of mould box: Rectangular B. Simulation Results for Existing Gating System With help of relevant information, first simulation trial was taken in order to analyze the defects in existing gating system. In existing gating sand riser is provided at a center and ingate were connected to the sand riser and molten metal is poured directly into the sand riser. This is pressurized gating system with ratio 1:075:0.5 area is sprue exist area, runner area and ingate area respectively. Fig.3 shows that maximum hotspot area on casting shown. Fig.5. Hot spot absorbed by sand riser Fig.6. Liquid filling shows possible shrinkage location found on casting Fig.3. Maximum hot spot location at different section Fig.7. Shrinkage defect on casting Fig.4. Existing gating system created in 3D software E-ISSN : Page 144

4 Fig.8. Probable location of Air entrapment The simulation of existing system, in liquid filling result shows possible location shrinkage will occur in Fig.6 and shrinkage defect found at pipe of casting shown in Fig. 7 and on flange might be chance of blow hole will occur shown in Fig.8 Fig.10 Hot spot absorbed by sleeve feeder C. Simulation results for modified gating system The existing design was studied initially and first of all the simulation trial was conducted in order to do the simulation study for existing system.the results of simulation were analyzed and gating system is modified. In modified gating system, exthermoic sleeve is provided on sand riser with thickness is 10 mm and changed the area of inagtes. Modified gating system shown in Fig.9 Fig.11 Liquid fraction absent in casting Fig.9. Modified gating system with exthermoic sleeve Fig.12. Shrinkage porosity absorbed in sleeve feeder The simulation results shows as far as modified design is concern, the hot spot is observed in the sleeve feeder shown E-ISSN : Page 145

5 in Fig.10 and there is no shrinkage porosity during the solidification Fig.12. The blow holes are observed after solidification in one of the casting in the mould box. In next trial, this blow hole defect has been eliminated by introducing one more flow off pin at appropriate location. D. Defect elimination After the first trial carried out for Existing gating system, the Shrinkage have been observed on the pipe of the casting as shown in the Fig.7. By providing the exothermic sleeve on feeder to improve the efficiency of the feeder, the shrinkage defect has been eliminated and defect free design was suggested for the casting for good quality IV. CONCLUSIONS Computer trials were successfully carried out to reduce the defects of the component Thus by carrying out trials with the help of computer simulation, a lot of metal, time, labor and cost were saved. After modification in the gating system, the defects were removed and also yield improved is 0.27 % with the sound casting of MMTD. Acknowledgment The authors would like to thank the company Gnat Foundry Private Limited, Kolhapur and Vinyak S. Patil Manager and production department for their involvement in the study. The authors also gratefully acknowledge supported by the company Gnat Foundry Private Limited. References [1] Vivek S.Gondkar and K.H. Inamdar, Optimization of Casting Process Parameters through Simulation, IJAIEM, vol.13, pp , June2014. [2] A. Reis, Z. Xu, R.V. Tol and R. Neto, Modelling feeding flow related shrinkage defects in aluminum castings, Journal of Manufacturing Process, vol.14, pp.1-7,2012. [3] Dr.B.ravi, Casting simulation and optimization: benefits, bottlenecks, Indian foundry journal, pp.3-5, [4] Su-Ling Lu, Fu-Ren Xiao, Shuang-Jie Zhang, Yong-Wei Mao and Bo Liao, Simulation study on the centrifugal casting wet-type cylinder liner based on ProCAST, Applied Thermal Engineering, vol.73, pp , [5] L.H.Shang, F.Paray, J.E.Gruzleski, S.Bergeron, C.Mercadante and C.A.Loong, Prediction of micro-porosity in Al Si castings in low pressure permanent mould casting using criteria functions, International Journal of Cast Metals Research, vol.17, pp , [6] A.R. Narwade1, C. M. Choudhari and B. E. Narkhede, Feeder Design And Analysis By Casting Simulation Software, International Journal Of Informative & Futuristic Research, vol.1, pp , May [7] I. Svensson And T. Sjögren, On Modeling And Simulation Of Mechanical Properties Of Cast Irons With Different Morphologies Of Graphite, International Journal Of Metals Cast, Pp.67-77, [8] Vasudev D. Shinde, Durgesh Joshi, B. Ravi, and K. Narasimhan, Optimization of Mold Yield in MultiCavity Sand Castings, Journal of Materials Engineering and Performance, vol.21, 2012 [9] P N Rao, Manufacturing technology, 5 th ed., vol.1. Macgraw hill,2013. [10] P. Beeley, Foundry Technology, 2 nd Edition, 2001 E-ISSN : Page 146