- Email: [email protected]
Quality and yield improvement of ductile iron casting by simulation technique
Materials Today: Proceedings xxx (xxxx) xxx
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Quality and yield improvement of ductile iron casting by simulation technique Bahubali B. Kabnure a,⇑, Vasudev D. Shinde a, Deepak C. Patil b a b
Department of Mechanical Engineering, D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji 416115, India Department of Mechanical Engineering, KLE Dr. MSS College of Engineering and Technology, Belagavi 590008, India
a r t i c l e
i n f o
Article history: Received 20 August 2019 Received in revised form 6 September 2019 Accepted 10 September 2019 Available online xxxx Keywords: Ductile iron Casting modeling Simulation Optimization of gating system Yield optimization
a b s t r a c t Foundries contribute to production of major automotive parts. These foundries now a days suffering from poor quality and productivity due to different parameters of the casting process. Casting quality depends on the solidification process after pouring. Computerized casting modeling and solidification simulation is being extensively used by foundries to design the casting process for manufacturing of castings before castings are prepared or before equipment is constructed or improved. The basic objective of using computerized casting modeling and solidification simulation is to increase the quality of the casting manufactured, both in the existing produced casting and first ever castings made and to reduce cost expenses. The shop floor trials can be reduced effectively by casting solidification simulation and defect free castings can be assured. The casting simulation approaches are based on finite element method (FEM), finite difference method (FDM), finite volume method (FVM). In this paper an attempt has been made to use finite difference method (FDM) and finite volume method (FVM) for casting solidification simulation and optimization of casting gating system to assure maximal yield. Modeling and simulation of Flange is analyzed in this study. The material for the flange is ductile iron and produced using shell molding process. Ductile iron has wide range of mechanical properties suitable for production of automotive parts. The 3D model of flange and gating system is created using CATIA and it is simulated using Solid CAST and Auto CAST-X software’s. The simulation software results will predict the location and level of shrinkage. Optimization of gating system will improve casting yield. This will suggest the modifications needed in gating system. Ó 2019 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the First International Conference on Recent Advances in Materials and Manufacturing 2019.
1. Introduction The casting process design is important for producing quality castings. It is unavoidable that many defects occur in casting process. Shrinkage is one of the major defect in ductile iron castings. Gating system is used to compensate shrinkage caused by casting solidification [1]. The casting simulation tool helps to optimize the casting process design and improve the yield of the casting [2]. Prediction of casting problems before an actual casting is poured has been solved successfully by casting process simulation. Now a days casting simulation is widely used by foundries to reduce the defects. But very few foundries have taken full benefits of casting solidification simulation. Most of the foundries have not ⇑ Corresponding author.
gained the facilities that this technique can offer. The computerized modeling and solidification simulation of the casting became useful in reducing the time and improve quality in the casting. Quality in terms of defect and improvement in the yield with lower pricing and higher productivity will lead to successful in the global competition. The computer model provides the detailed drawing of the pattern. The simulation technique reduces the number of trials for defect free casting [3]. In the traditional method the foundry men use their experience or some identified rules to design the gating system for any casting. Some engineers use gating design formulae for this purpose. Then the pattern and mold is prepared and molten metal is poured. If defect arises with this system, the gating system is modified according to the position and level of the defect. This trial and run method continues till the defect in the casting is reduced. Due to this traditional trial-and-error
E-mail address: [email protected] (B.B. Kabnure). https://doi.org/10.1016/j.matpr.2019.09.022 2214-7853/Ó 2019 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the First International Conference on Recent Advances in Materials and Manufacturing 2019.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
2
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
method the relation between foundry and customer may spoil as it takes more and consume more time and labor [4]. The modeling software helps to reduce the time for drawing of the gating system and casting layout. This will reduce the cost and time for the modification required in the gating system optimization. Computer modeling and simulation offers the potential of evaluating process designs in much less time, and at much less cost, than by conventional method [5]. Due to these benefits of modeling simulation techniques, it is mandatory for the foundries to make use of these technologies. According to one survey by the engineers it has been found that maximum organizations use internet for solving the problems. Around 71% companies using CAD/CAM, 65% are using planning software’s and only 18% are using simulations [6]. The computer solidification simulation systems available today are software programs which use various mathematical models of heat transfer and solidification to analyze and predict the likely defects [7]. The different simulation software solutions available are substituting traditional methods in the foundry with numerous simulation techniques like finite element methods. Skilled operator or engineer is required for operating the modeling and simulation software’s as it comprises of creating 3D model, applying boundary conditions and performing trials on the software. Plotting of the results and its analysis require good knowledge of the process and defects. There are very few simulation software’s that will give the cast report of the whole process. AutoCAST gives the detailed costing of the process in the final report generated after simulation. The software is capable of optimizing the gating system by performing trials in the background. This will give the optimized gating system that will give the defect free casting [8].
2. Methodology The casting modeling and simulation will be performed in different stages as shown in Fig. 1. The first step towards the casting simulation is to collect the data and the drawing of the required component. The details for the flange are tabulated in Table 1. The material of the flange casting is ductile iron having tensile strength 500 N/mm2 with 7% elongation. Ductile Iron gives wide range properties for automobile parts [9]. The casting process involves a preparation of shells molds of cope and drag. The molding material used is resin coated sand. The furnace used for melting purpose is of medium frequency induction furnace having capacity of 300 kg with furnace temperature of 1490–1500 °C. The pouring temperature for molten metal is in the range of 1380–1420 °C. CAD model of the casting is then created using CATIA V5R19 software. The 3D CAD model of flange with its photograph is shown in Fig. 2.
Table 1 Flange casting processing parameters. Title
Details
Casting Material (grade) Molding Method Pouring Temperature Pouring Time Density of Material No of cavities in the mold box Total weight of Casting Bunch Type of Gating System
Ductile Iron (SG500/7) Shell Molding 1380–1420 °C 7–8 s 7150 kg/m3 6 6.18 kg Parting Line gating system
Fig. 1. Methodology for Casting Simulation.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
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Fig. 2. Photograph & CAD Model of Flange.
3. Numerical simulation of flange using SolidCAST
3.2. Processing
3.1. Pre processing
Processing involves creating meshing model of the casting bunch with finite difference method and then simulating the meshed model. The mesh size is defined initially in this stage. Mesh size decides the complexity of performing heat transfer calculations. Smaller the mesh size complex is the heat transfer calculations. The processing time depends on Casting and mold dimensions, mesh size applied and the computer configuration and processing speed.
Preprocessing in simulation software involves importing CAD model into simulation environment, applying boundary conditions to the process. CI GI 4.0 material applied for the flange and the mesh size selected is 1 mm. Pouring time is specified as 7 s. The CAD model of existing layout is shown in Fig. 3.
3.3. Post processing
Fig. 3. Exiting Layout of Casting Bunch imported in simulation environment.
Post processing involves plotting of the simulated results after performing casting solidification simulation. There are different criteria’s in the simulation tool by which the results can be plotted. The simulated results are plotted using Niyama criteria as shown in Fig. 4. Niyama criteria is ratio of temperature gradient and square root of cooling rate. Niyama predicts the solidification process in the casting. The value 0 represents poor directional solidification while the higher value represents good directional solidification. The ranges of Niyama values for various materials are: C I: 0 to 0.750 and for Steel: 0 to 1. According to Niyama the
Fig. 4. Shrinkage location predicted by software.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
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shrinkage possibility is maximum if the value of Niyama is low and vice versa. It the Niyama value is above critical value, then there is very low possibility of shrinkage [10]. In the result shown in Fig. 4, the Niyama value at critical region is 0.457 which is below 0.750. Hence there is possibility of shrinkage at that region. The actual shrinkage in casting as shown in Fig. 5 matches with the shrinkage plotted by simulated results shown in Fig. 4. Now the gating system needs to be modified and optimised in order to get defect free casting with better yield.
ged. The modified neck dimensions are 5 mm 40 mm. The new modified layout is shown in Fig. 6. The new modified layout is simulated with the same procedure mentioned for existing layout. The result plotted is shown in Fig. 6. At the critical region the Niyama value is 1.537. According to Niyama criteria the value is above 0.750. Therefore, the shrinkage is reduced from that critical region with the new modified gating system. 4. Numerical simulation of flange using AutoCAST
3.4. Modified and optimised gating system Neck of the ingate plays an important role in feeding the metal effectively [11]. To feed all the castings effectively, the angular distance between the castings is changed. The neck size is also chan-
The simulation software offers functions to help guide a user in producing gating and riser designs and also have functions which produce visual outputs showing possible problem areas and defects [12].
Fig. 5. Casting Bunch after pouring and Shrinkage location in actual casting.
Fig. 6. Shrinkage location predicted by software for new layout.
Fig. 7. Existing and new layout imported in AutoCAST-X1.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
5
Fig. 8. Solidified casting view of Existing and new layout.
Fig. 9. Occurrence of Shrinkage in Existing and new layout.
4.3. Shrinkage porosity
Table 2 Details of Yield Improvement. Details
Existing Layout
Optimized Layout
Casting Weight No of cavities in the mold box Total weight of Casting Bunch Total weight of Casting Bunch with gating Type of Gating System
1.03 kg 6 6.18 kg 10.64 kg
1.03 kg 6 6.18 kg 10.12 kg
Parting Line gating system 58.08%
Parting Line gating system 61.07%
Total Yield ¼ Total
weight of Good Casting weight of Metal Poured
Table 3 Defect comparison. Details
SolidCAST
AutoCAST
Method Defect Prediction
FDM Matches with Actual Casting Niyama Criteria
VEM Matches with Actual Casting Niyama Criteria
Shrinkage prediction criteria
4.1. Part & mold To ensure defect free casting the casting process is simulated using casting simulation software AutoCAST to predict the defect before pouring of the metal [13]. The AutoCAST software is based on Vector Element Method (VEM). The 3D model of the casting with gating system for existing and new layout are imported into simulation environment as shown in Fig. 7. All the design parameters have been set properly in numerical simulation software. Solidification simulation is then performed.
After performing the simulation, the results are plotted for prediction of shrinkage. The software predicts exact location of the shrinkage directly. The occurrence of shrinkage in casting for both layouts is shown in Fig. 9. The shrinkage shown by AutoCAST matches with the actual defect in the casting. The shrinkage from new layout is removed after modifying the gating system. 5. Results and discussion Casting with existing gating system simulated and the results from solidification simulation are compared with the actual casting shrinkage. From the Figs. 4 and 5, it is clear that the shrinkage shown by simulated result matches with the actual shrinkage location. Thus, simulated result validated with the experiment. After modifications in the gating system, same experimentation is done. The total weight of casting bunch with gating system in the optimized layout is reduced to 10.12 kg from 10.64. The actual weight of casting bunch excluding gating system is 6.18 kg. Hence the yield is improved with the new optimized layout. The details of the yield improvement are tabulated in Table 2. The defect prediction from SolidCAST and AutoCAST is compared and tabulated in Table 3. 6. Conclusions
4.2. Solidification simulation
According to the drawing 3D modeling of Flange casting is done. The part is imported and gating and feeding system is designed and simulated in SolidCAST and AutoCAST software. The simulated casting design is poured and defect matching is carried out. Also, optimization of gating system is carried out using simulated results in the software. Based on the above studies following conclusions are drawn:
AutoCAST provides the most comprehensive functionality ranging from part, methods design to advanced simulation, defect analysis and quality assurance, across ferrous and non-ferrous metals and multiple processes [14,15]. The simulation is performed with fine mesh and pouring time set to 7 s. The solidified view of both the layouts are shown in Fig. 8.
1. The casting shrinkage can be exactly predicted by casting simulation with use of SolidCAST and AutoCAST software. 2. Further casting simulation will be used for optimizing gating dimensions with maintaining casting quality. 3. Casting solidification simulation can be used effectively for reducing the defects in the casting.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
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B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
4. The yield of the casting is improved by 3% after optimizing the gating system. 5. From the optimized gating system, the detailed layout drawing will be available to pattern maker so as to achieve defect free casting after pouring.
Acknowledgements The authors would like thank the management and engineers of Mane Foundry, Ichalkaranji for providing the facilities for carrying out the experimental work. All the technical data including drawing of Flange is provided by the company. References [1] S.L. Nimbulkar, R.S. Dalu, Design optimization of gating and feeding system through simulation technique for sand casting of wear plate, Perspect. Sci. 8 (2016) 39–42. [2] J. Jezierski, R. Dojka, K. Janerka, Optimizing the gating system for steel castings, Metals 8 (66) (2018) 1–13. [3] B. Ravi, Casting method optimization driven by simulation, Indian Foundry Cong. 57 (2009) 70–74.
[4] B. Ravi, Computer-aided Casting Method Design, Simulation and Optimization, IIF, 2008, pp. 1–5. [5] K.D. Carlson, S. Ou, R.A. Hardin, C. Beckermann, Development of New FeedingDistance Rules Using Casting Simulation: Part 1. Methodology. [6] M. Arasu, L.R. Jefferey, Applications of virtual manufacturing techniques for yield improvement in cast iron foundries, Indian Foundry Cong. 57 (2009) 1–6. [7] G. Ghosh, H. Shamim, R. Bahera, G. Sutradhar, A computer aided crashing simulation of aluminium foam structure, Indian Foundry Cong. 57 (2009) 48– 54. [8] B. Ravi, Bridging the digital divide in casting simulation technology, Indian Foundry Cong. 57 (2009) 55–60. [9] M. Gagne, Effect of wall thickness on the graphite morphology and properties of D5-S austenitic ductile iron, AFS Trans. (2007) 1–11. [10] SOLIDCast Workbook, output criteria’s, Finite solutions, 2010, pp. 87–95. [11] S.A. Calcom, Simulating porosity in ductile iron casting, E-tips, Nr. 17, Switzerland. [12] V. Kumar, B. Ali, N. Khan, Analysis Casting Simulation and Its Importance, IOSR J. Eng. 08 (6) (2018) 72–82. [13] B.B. Kabnure, V.D. Shinde, R.R. Kolhapure, Optimization to develop multiple response microstructure and hardness of ductile iron casting by using GRA, J. Inst. Eng. India Ser. D (Springer) 99 (7) (2018) 235–243. [14] M.N. Jadhav, K.H. Inamdar, Numerical optimization of Grey C.I. casting using simulation, IOSR J. Mech. Civil Eng. (IOSR-JMCE) (2017) 47–51. [15] C.M. Chiudhari, B.E. Narkhede, S.K. Mahajan, Casting design and simulation of cover plate using autoCAST-Xsoftware for defect minimization with experimental validation, Procedia Mater. Sci. 6 (2014) 786–797.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Quality and yield improvement of ductile iron casting by simulation technique Bahubali B. Kabnure a,⇑, Vasudev D. Shinde a, Deepak C. Patil b a b
Department of Mechanical Engineering, D.K.T.E. Society’s Textile and Engineering Institute, Ichalkaranji 416115, India Department of Mechanical Engineering, KLE Dr. MSS College of Engineering and Technology, Belagavi 590008, India
a r t i c l e
i n f o
Article history: Received 20 August 2019 Received in revised form 6 September 2019 Accepted 10 September 2019 Available online xxxx Keywords: Ductile iron Casting modeling Simulation Optimization of gating system Yield optimization
a b s t r a c t Foundries contribute to production of major automotive parts. These foundries now a days suffering from poor quality and productivity due to different parameters of the casting process. Casting quality depends on the solidification process after pouring. Computerized casting modeling and solidification simulation is being extensively used by foundries to design the casting process for manufacturing of castings before castings are prepared or before equipment is constructed or improved. The basic objective of using computerized casting modeling and solidification simulation is to increase the quality of the casting manufactured, both in the existing produced casting and first ever castings made and to reduce cost expenses. The shop floor trials can be reduced effectively by casting solidification simulation and defect free castings can be assured. The casting simulation approaches are based on finite element method (FEM), finite difference method (FDM), finite volume method (FVM). In this paper an attempt has been made to use finite difference method (FDM) and finite volume method (FVM) for casting solidification simulation and optimization of casting gating system to assure maximal yield. Modeling and simulation of Flange is analyzed in this study. The material for the flange is ductile iron and produced using shell molding process. Ductile iron has wide range of mechanical properties suitable for production of automotive parts. The 3D model of flange and gating system is created using CATIA and it is simulated using Solid CAST and Auto CAST-X software’s. The simulation software results will predict the location and level of shrinkage. Optimization of gating system will improve casting yield. This will suggest the modifications needed in gating system. Ó 2019 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the First International Conference on Recent Advances in Materials and Manufacturing 2019.
1. Introduction The casting process design is important for producing quality castings. It is unavoidable that many defects occur in casting process. Shrinkage is one of the major defect in ductile iron castings. Gating system is used to compensate shrinkage caused by casting solidification [1]. The casting simulation tool helps to optimize the casting process design and improve the yield of the casting [2]. Prediction of casting problems before an actual casting is poured has been solved successfully by casting process simulation. Now a days casting simulation is widely used by foundries to reduce the defects. But very few foundries have taken full benefits of casting solidification simulation. Most of the foundries have not ⇑ Corresponding author.
gained the facilities that this technique can offer. The computerized modeling and solidification simulation of the casting became useful in reducing the time and improve quality in the casting. Quality in terms of defect and improvement in the yield with lower pricing and higher productivity will lead to successful in the global competition. The computer model provides the detailed drawing of the pattern. The simulation technique reduces the number of trials for defect free casting [3]. In the traditional method the foundry men use their experience or some identified rules to design the gating system for any casting. Some engineers use gating design formulae for this purpose. Then the pattern and mold is prepared and molten metal is poured. If defect arises with this system, the gating system is modified according to the position and level of the defect. This trial and run method continues till the defect in the casting is reduced. Due to this traditional trial-and-error
E-mail address: [email protected] (B.B. Kabnure). https://doi.org/10.1016/j.matpr.2019.09.022 2214-7853/Ó 2019 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the First International Conference on Recent Advances in Materials and Manufacturing 2019.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
2
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
method the relation between foundry and customer may spoil as it takes more and consume more time and labor [4]. The modeling software helps to reduce the time for drawing of the gating system and casting layout. This will reduce the cost and time for the modification required in the gating system optimization. Computer modeling and simulation offers the potential of evaluating process designs in much less time, and at much less cost, than by conventional method [5]. Due to these benefits of modeling simulation techniques, it is mandatory for the foundries to make use of these technologies. According to one survey by the engineers it has been found that maximum organizations use internet for solving the problems. Around 71% companies using CAD/CAM, 65% are using planning software’s and only 18% are using simulations [6]. The computer solidification simulation systems available today are software programs which use various mathematical models of heat transfer and solidification to analyze and predict the likely defects [7]. The different simulation software solutions available are substituting traditional methods in the foundry with numerous simulation techniques like finite element methods. Skilled operator or engineer is required for operating the modeling and simulation software’s as it comprises of creating 3D model, applying boundary conditions and performing trials on the software. Plotting of the results and its analysis require good knowledge of the process and defects. There are very few simulation software’s that will give the cast report of the whole process. AutoCAST gives the detailed costing of the process in the final report generated after simulation. The software is capable of optimizing the gating system by performing trials in the background. This will give the optimized gating system that will give the defect free casting [8].
2. Methodology The casting modeling and simulation will be performed in different stages as shown in Fig. 1. The first step towards the casting simulation is to collect the data and the drawing of the required component. The details for the flange are tabulated in Table 1. The material of the flange casting is ductile iron having tensile strength 500 N/mm2 with 7% elongation. Ductile Iron gives wide range properties for automobile parts [9]. The casting process involves a preparation of shells molds of cope and drag. The molding material used is resin coated sand. The furnace used for melting purpose is of medium frequency induction furnace having capacity of 300 kg with furnace temperature of 1490–1500 °C. The pouring temperature for molten metal is in the range of 1380–1420 °C. CAD model of the casting is then created using CATIA V5R19 software. The 3D CAD model of flange with its photograph is shown in Fig. 2.
Table 1 Flange casting processing parameters. Title
Details
Casting Material (grade) Molding Method Pouring Temperature Pouring Time Density of Material No of cavities in the mold box Total weight of Casting Bunch Type of Gating System
Ductile Iron (SG500/7) Shell Molding 1380–1420 °C 7–8 s 7150 kg/m3 6 6.18 kg Parting Line gating system
Fig. 1. Methodology for Casting Simulation.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
3
Fig. 2. Photograph & CAD Model of Flange.
3. Numerical simulation of flange using SolidCAST
3.2. Processing
3.1. Pre processing
Processing involves creating meshing model of the casting bunch with finite difference method and then simulating the meshed model. The mesh size is defined initially in this stage. Mesh size decides the complexity of performing heat transfer calculations. Smaller the mesh size complex is the heat transfer calculations. The processing time depends on Casting and mold dimensions, mesh size applied and the computer configuration and processing speed.
Preprocessing in simulation software involves importing CAD model into simulation environment, applying boundary conditions to the process. CI GI 4.0 material applied for the flange and the mesh size selected is 1 mm. Pouring time is specified as 7 s. The CAD model of existing layout is shown in Fig. 3.
3.3. Post processing
Fig. 3. Exiting Layout of Casting Bunch imported in simulation environment.
Post processing involves plotting of the simulated results after performing casting solidification simulation. There are different criteria’s in the simulation tool by which the results can be plotted. The simulated results are plotted using Niyama criteria as shown in Fig. 4. Niyama criteria is ratio of temperature gradient and square root of cooling rate. Niyama predicts the solidification process in the casting. The value 0 represents poor directional solidification while the higher value represents good directional solidification. The ranges of Niyama values for various materials are: C I: 0 to 0.750 and for Steel: 0 to 1. According to Niyama the
Fig. 4. Shrinkage location predicted by software.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
4
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
shrinkage possibility is maximum if the value of Niyama is low and vice versa. It the Niyama value is above critical value, then there is very low possibility of shrinkage [10]. In the result shown in Fig. 4, the Niyama value at critical region is 0.457 which is below 0.750. Hence there is possibility of shrinkage at that region. The actual shrinkage in casting as shown in Fig. 5 matches with the shrinkage plotted by simulated results shown in Fig. 4. Now the gating system needs to be modified and optimised in order to get defect free casting with better yield.
ged. The modified neck dimensions are 5 mm 40 mm. The new modified layout is shown in Fig. 6. The new modified layout is simulated with the same procedure mentioned for existing layout. The result plotted is shown in Fig. 6. At the critical region the Niyama value is 1.537. According to Niyama criteria the value is above 0.750. Therefore, the shrinkage is reduced from that critical region with the new modified gating system. 4. Numerical simulation of flange using AutoCAST
3.4. Modified and optimised gating system Neck of the ingate plays an important role in feeding the metal effectively [11]. To feed all the castings effectively, the angular distance between the castings is changed. The neck size is also chan-
The simulation software offers functions to help guide a user in producing gating and riser designs and also have functions which produce visual outputs showing possible problem areas and defects [12].
Fig. 5. Casting Bunch after pouring and Shrinkage location in actual casting.
Fig. 6. Shrinkage location predicted by software for new layout.
Fig. 7. Existing and new layout imported in AutoCAST-X1.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
5
Fig. 8. Solidified casting view of Existing and new layout.
Fig. 9. Occurrence of Shrinkage in Existing and new layout.
4.3. Shrinkage porosity
Table 2 Details of Yield Improvement. Details
Existing Layout
Optimized Layout
Casting Weight No of cavities in the mold box Total weight of Casting Bunch Total weight of Casting Bunch with gating Type of Gating System
1.03 kg 6 6.18 kg 10.64 kg
1.03 kg 6 6.18 kg 10.12 kg
Parting Line gating system 58.08%
Parting Line gating system 61.07%
Total Yield ¼ Total
weight of Good Casting weight of Metal Poured
Table 3 Defect comparison. Details
SolidCAST
AutoCAST
Method Defect Prediction
FDM Matches with Actual Casting Niyama Criteria
VEM Matches with Actual Casting Niyama Criteria
Shrinkage prediction criteria
4.1. Part & mold To ensure defect free casting the casting process is simulated using casting simulation software AutoCAST to predict the defect before pouring of the metal [13]. The AutoCAST software is based on Vector Element Method (VEM). The 3D model of the casting with gating system for existing and new layout are imported into simulation environment as shown in Fig. 7. All the design parameters have been set properly in numerical simulation software. Solidification simulation is then performed.
After performing the simulation, the results are plotted for prediction of shrinkage. The software predicts exact location of the shrinkage directly. The occurrence of shrinkage in casting for both layouts is shown in Fig. 9. The shrinkage shown by AutoCAST matches with the actual defect in the casting. The shrinkage from new layout is removed after modifying the gating system. 5. Results and discussion Casting with existing gating system simulated and the results from solidification simulation are compared with the actual casting shrinkage. From the Figs. 4 and 5, it is clear that the shrinkage shown by simulated result matches with the actual shrinkage location. Thus, simulated result validated with the experiment. After modifications in the gating system, same experimentation is done. The total weight of casting bunch with gating system in the optimized layout is reduced to 10.12 kg from 10.64. The actual weight of casting bunch excluding gating system is 6.18 kg. Hence the yield is improved with the new optimized layout. The details of the yield improvement are tabulated in Table 2. The defect prediction from SolidCAST and AutoCAST is compared and tabulated in Table 3. 6. Conclusions
4.2. Solidification simulation
According to the drawing 3D modeling of Flange casting is done. The part is imported and gating and feeding system is designed and simulated in SolidCAST and AutoCAST software. The simulated casting design is poured and defect matching is carried out. Also, optimization of gating system is carried out using simulated results in the software. Based on the above studies following conclusions are drawn:
AutoCAST provides the most comprehensive functionality ranging from part, methods design to advanced simulation, defect analysis and quality assurance, across ferrous and non-ferrous metals and multiple processes [14,15]. The simulation is performed with fine mesh and pouring time set to 7 s. The solidified view of both the layouts are shown in Fig. 8.
1. The casting shrinkage can be exactly predicted by casting simulation with use of SolidCAST and AutoCAST software. 2. Further casting simulation will be used for optimizing gating dimensions with maintaining casting quality. 3. Casting solidification simulation can be used effectively for reducing the defects in the casting.
Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022
6
B.B. Kabnure et al. / Materials Today: Proceedings xxx (xxxx) xxx
4. The yield of the casting is improved by 3% after optimizing the gating system. 5. From the optimized gating system, the detailed layout drawing will be available to pattern maker so as to achieve defect free casting after pouring.
Acknowledgements The authors would like thank the management and engineers of Mane Foundry, Ichalkaranji for providing the facilities for carrying out the experimental work. All the technical data including drawing of Flange is provided by the company. References [1] S.L. Nimbulkar, R.S. Dalu, Design optimization of gating and feeding system through simulation technique for sand casting of wear plate, Perspect. Sci. 8 (2016) 39–42. [2] J. Jezierski, R. Dojka, K. Janerka, Optimizing the gating system for steel castings, Metals 8 (66) (2018) 1–13. [3] B. Ravi, Casting method optimization driven by simulation, Indian Foundry Cong. 57 (2009) 70–74.
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Please cite this article as: B. B. Kabnure, V. D. Shinde and D. C. Patil, Quality and yield improvement of ductile iron casting by simulation technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2019.09.022