International Journal of Metalcasting

, Volume 13, Issue 1, pp 2–17 | Cite as

Re-Thinking Design Methodology for Castings: 3D Sand-Printing and Topology Optimization

  • Jiayi Wang
  • Santosh Reddy Sama
  • Guha ManogharanEmail author


Additive manufacturing of sand molds and cores for metal castings, often called 3D sand-printing (3DSP), is an efficient “freeform” fabrication process that enables rapid production of sand metal castings. The ability to create highly complex molds and cores for advanced metal casting geometries via 3DSP provides unparalleled design freedom, particularly for low-volume production. However, there is a need to thoroughly understand the opportunities and restrictions of 3DSP in a systematic approach similar to well-established design guidelines for traditional sand casting. This study presents a knowledge-based design framework for 3DSP with the goal of developing new part design guidelines under such 3DSP framework. In particular, constrained topology optimization approach for the part redesign is developed for 3DSP. The presented design framework is compared with traditional sand-casting rules and validated through a case study on an existing metal component. Advantages of the developed 3DSP design framework are illustrated and validated through a case study where a 30% improvement in factor of safety and a 50% reduction in weight of a mechanical part is achieved. Other advantages, such as reduced lead time and production cost, are also observed. This research provides the first known investigation into systematic implementation of simultaneous constraints of 3DSP sand-casting rules mechanical strength through the integration of topology optimization and novel design rules to castings via 3D-printed molds. 3DSP also eliminates multiple design constraints in conventional mold-making and core-box fabrication. Findings from this study can be applied for a wide range of alloy systems, part geometries and loading conditions for sand castings in industrial applications.


additive manufacturing 3D sand-printing sand casting topology optimization metal castings 



This research work is funded by America Makes project: Additive Manufacturing for Metal Casting (AM4MC). We would like to thank The University of Northern Iowa Metal Casting Center (UNI MCC) for the 3D printing of sand molds and casting of the product. We also want to thank the Penn State FAME laboratory for assistance with the post-processing of cast parts.


  1. 1.
    B.P. Conner et al., Making sense of 3-D printing: creating a map of additive manufacturing products and services. Addit Manuf 1, 64–76 (2014)CrossRefGoogle Scholar
  2. 2.
    ASTM, Standard Terminology for Additive Manufacturing Technologies, in ASTM F2792-10e1 (ASTM International, West Conshohocken, PA, 2012)Google Scholar
  3. 3.
    T. Wohlers, Wohlers Report 2016: Gloabal Reports (Wohlers Associates Inc., Belgium, 2016)Google Scholar
  4. 4.
    T. Campbell, C. Williams, O. Ivanova, B. Garrett, Could 3D Printing Change the World? Technologies, Potential, and Implications of Additive Manufacturing, Strategic Foresight Report (Atlantic Council, Washington, DC, 2011). Retrieved December 1, 2017 from
  5. 5.
    Y. Huang, M.C. Leu, J. Mazumder, A. Donmez, Additive manufacturing: current state, future potential, gaps and needs, and recommendations. J. Manuf. Sci. Eng. 137(1), 014001 (2015)CrossRefGoogle Scholar
  6. 6.
    S.L. Ford, Additive manufacturing technology: Potential implications for US manufacturing competitiveness. J. Int. Commerce Econ. 6, 40 (2014)Google Scholar
  7. 7.
    B. Dutta, F.H.S. Froes, The Additive Manufacturing (AM) of Titanium Alloys, in Titanium Powder Metallurgy (Butterworth-Heinemann, Boston, 2015), pp. 447–468Google Scholar
  8. 8.
    W.E. Frazier, Metal additive manufacturing: a review. J. Mater. Eng. Perform. 23(6), 1917–1928 (2014)CrossRefGoogle Scholar
  9. 9.
    W.A. Haviland, Maya Settlement Patterns: A Critical Review (Middle American Research Institute, Tulane University, New Orleans, LA, 1966)Google Scholar
  10. 10.
    M. Chhabra, R. Singh, Rapid casting solutions: a review. Rapid Prototyp. J. 17(5), 328–350 (2011)CrossRefGoogle Scholar
  11. 11.
    E.S. Almaghariz et al., Quantifying the role of part design complexity in using 3D sand printing for molds and cores. Int. J. Metalcast. 10(3), 240–252 (2016)CrossRefGoogle Scholar
  12. 12.
    G. Manogharan, Hybrid Manufacturing: Analysis of Integrating Additive and Subtractive Methods (Industrial Engineering, North Carolina State University, Raleigh, NC, 2014)Google Scholar
  13. 13.
    L.A. Schmit, Structural Design by Systematic Synthesis, in Proceedings of the 2nd Conference on Electronic Computation (ASCE, New York, 1960), pp. 105–122Google Scholar
  14. 14.
    O. Sigmund, K. Maute, Topology optimization approaches. Struct. Multidiscip. Optim. 48(6), 1031–1055 (2013)CrossRefGoogle Scholar
  15. 15.
    M.P. Bendsøe, O. Sigmund, Material interpolation schemes in topology optimization. Arch. Appl. Mech. 69(9), 635–654 (1999)Google Scholar
  16. 16.
    J.-H. Zhu, W.-H. Zhang, L. Xia, Topology optimization in aircraft and aerospace structures design. Arch. Comput. Methods Eng. 23(4), 595–622 (2016)CrossRefGoogle Scholar
  17. 17.
    M. Zhou, R. Fleury, Y.-K. Shyy, H. Thomas, J. Brennan, Progress in Topology Optimization with Manufacturing Constraints, in Proceedings of the 9th AIAA MDO Conference AIAA-2002-4901, 2002Google Scholar
  18. 18.
    X. Wang et al., Topological design and additive manufacturing of porous metals for bone scaffolds and orthopaedic implants: a review. Biomaterials 83, 127–141 (2016)CrossRefGoogle Scholar
  19. 19.
    S. Yang, Y.F. Zhao, Additive manufacturing-enabled design theory and methodology: a critical review. Int. J. Adv. Manuf. Technol. 80(1–4), 327–342 (2015)CrossRefGoogle Scholar
  20. 20.
    Z. Doubrovski, J.C. Verlinden, J.M. Geraedts, Optimal design for additive manufacturing: opportunities and challenges, in ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, (American Society of Mechanical Engineers, 2011), pp. 635–646Google Scholar
  21. 21.
    K.A. James, G.J. Kennedy, J.R. Martins, Concurrent aerostructural topology optimization of a wing box. Comput. Struct. 134, 1–17 (2014)CrossRefGoogle Scholar
  22. 22.
    L. Krog, A. Tucker, M. Kemp, R. Boyd, Topology Optimization of Aircraft Wing Box Ribs, in 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, 2004, pp. 1–11Google Scholar
  23. 23.
    J.W. Chang, Y.S. Lee, Topology optimization of compressor bracket. J. Mech. Sci. Technol. 22(9), 1668–1676 (2008)CrossRefGoogle Scholar
  24. 24.
    P. Wu, Q. Ma, Y. Luo, C. Tao, Topology optimization design of automotive engine bracket. Energy Power Eng. 8(04), 230 (2016)CrossRefGoogle Scholar
  25. 25.
    X. Li, L. Wang, Based on topology optimization method the cab mount bracket lightweight design. Appl. Mech. Mater. 152154, 1292–1297 (2012)CrossRefGoogle Scholar
  26. 26.
    J. Seppälä, A. Hupfer, Topology Optimization in Structural Design of a LP Turbine Guide Vane: Potential of Additive Manufacturing for Weight Reduction, in ASME Turbo Expo 2014: Turbine Technical Conference and Exposition (American Society of Mechanical Engineers, 2014), pp. V07AT28A004–V07AT28A004Google Scholar
  27. 27.
    R. Rezaie, M. Badrossamay, A. Ghaie, H. Moosavi, Topology optimization for fused deposition modeling process. Proc. CIRP 6, 521–526 (2013)CrossRefGoogle Scholar
  28. 28.
    W. Carter et al., The GE Aircraft Engine Bracket Challenge: An Experiment in Crowdsourcing for Mechanical Design Concepts, in Solid Freeform Fabrication Symposium (University of Texas at Austin, Austin, Texas, 2014), pp. 1402–1411Google Scholar
  29. 29.
    V. Maranan, T.W. Simpson, T. Palmer, C.J. Dickman, Application of Topology Optimization and Design for Additive Manufacturing Guidelines on an Automotive Component, in ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (American Society of Mechanical Engineers, 2016), pp. V02AT03A030–V02AT03A030Google Scholar
  30. 30.
    Q. Xia, T. Shi, M.Y. Wang, S. Liu, A level set based method for the optimization of cast part. Struct. Multidiscip. Optim. 41(5), 735–747 (2010)CrossRefGoogle Scholar
  31. 31.
    R. Tavakoli, P. Davami, Optimal riser design in sand casting process by topology optimization with SIMP method I: poisson approximation of nonlinear heat transfer equation. Struct. Multidiscip. Optim. 36(2), 193–202 (2008)CrossRefGoogle Scholar
  32. 32.
    Z. Li, Z. Mao, W. Li, Optimization design of riser based on particle swarm algorithm. Zhuzao (Foundry) 54(2), 176–178 (2005)Google Scholar
  33. 33.
    L. Harzheim, G. Graf, A review of optimization of cast parts using topology optimization: II—topology optimization with manufacturing constraints. Struct. Multidiscip. Optim. 31(5), 388–399 (2006)CrossRefGoogle Scholar
  34. 34.
    G. Allaire, F. Jouve, G. Michailidis, Casting Constraints in Structural Optimization Via a Level-Set Method, in 10th World Congress on Structural and Multidisciplinary Optimization (, Orlando, Florida, 2013)Google Scholar
  35. 35.
    J.P. Leiva, B.C. Watson, I. Kosaka, An Analytical Directional Growth Topology Parameterization to Enforce Manufacturing Requirements, in Proceedings of 45th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference, Palm Springs, CA, 2004Google Scholar
  36. 36.
    A.R. Gersborg, C.S. Andreasen, An explicit parameterization for casting constraints in gradient driven topology optimization. Struct. Multidiscip. Optim. 44(6), 875–881 (2011)CrossRefGoogle Scholar
  37. 37.
    K.-T. Zuo, L.-P. Chen, Y.-Q. Zhang, J. Yang, Manufacturing-and machining-based topology optimization. Int. J. Adv. Manuf. Technol. 27(5), 531–536 (2006)CrossRefGoogle Scholar
  38. 38.
    J.K. Guest M. Zhu, Casting and Milling Restrictions in Topology Optimization Via Projection-Based Algorithms, in Proceedings of the ASME 2012 International Design Engineering Technical Conference & Computers and Information in Engineering Conference, Chicago, IL, USA, August, 2012, pp. 12–15Google Scholar
  39. 39.
    O. Schmitt, J. Friederich, S. Riehl, P. Steinmann, On the formulation and implementation of geometric and manufacturing constraints in node–based shape optimization. Struct. Multidiscip. Optim. 53(4), 881–892 (2016)CrossRefGoogle Scholar
  40. 40.
    Q. Xia, T. Shi, M.Y. Wang, S. Liu, Simultaneous optimization of cast part and parting direction using level set method. Struct. Multidiscip. Optim. 44(6), 751–759 (2011)CrossRefGoogle Scholar
  41. 41.
    M. Langelaar, Topology optimization of 3D self-supporting structures for additive manufacturing. Addit. Manuf. 12, 60–70 (2016)CrossRefGoogle Scholar
  42. 42.
    A.T. Gaynor, J.K. Guest, Topology Optimization for Additive Manufacturing: Considering Maximum Overhang Constraint, in 15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Atlanta, GA, 2014, pp. 16–20Google Scholar
  43. 43.
    M. Leary, L. Merli, F. Torti, M. Mazur, M. Brandt, Optimal topology for additive manufacture: a method for enabling additive manufacture of support-free optimal structures. Mater. Des. 63, 678–690 (2014)CrossRefGoogle Scholar
  44. 44.
    D. Brackett, I. Ashcroft, R. Hague, Topology Optimization for Additive Manufacturing, in Proceedings of the Solid Freeform Fabrication Symposium, Austin, TX, 2011, vol 1, pp. 348–362Google Scholar
  45. 45.
    E. Komi, P. Kokkonen, J. Virta, P. Puukko, S. Metsä-Kortelainen, Simulation, Optimisation and Design of a 3D Printed Sand Mould for a Cast Metal Component (VTT Technical Research Centre of Finland Ltd, 2016). Retrieved December 1, 2017 from
  46. 46.
    ExOne, Webinar: A Case Study in Optimizing Casting Design Using 3 D Printing (AFS Metalcasting Television, 2017). Retrieved December 1, 2017 from
  47. 47.
    W. Wang, H.W. Stoll, J.G. Conley, Rapid Tooling Guidelines for Sand Casting (Springer, New York, NY, 2010)CrossRefGoogle Scholar
  48. 48.
    ASM International, Casting Design and Performance (ASM International, Materials Park, OH, 2009)Google Scholar
  49. 49.
    D. Snelling, Q. Li, N. Meisel, C.B. Williams, R.C. Batra, A.P. Druschitz, Lightweight metal cellular structures fabricated via 3D printing of sand cast molds. Adv. Eng. Mater. 17(7), 923–932 (2015)CrossRefGoogle Scholar
  50. 50.
    D. Snelling, C. Williams, A. Druschitz, A Comparison of Binder Burnout and Mechanical Characteristics of Printed and Chemically Bonded Sand Molds, in SFF Symposium, Austin, TX, 2014Google Scholar
  51. 51.
    P.M. Hackney, R. Wooldridge, 3D sand printing for automotive mass production applications. Int. J. Rapid Manuf. 6(2–3), 134–154 (2017)CrossRefGoogle Scholar
  52. 52.
    I. Ferguson, M. Frecker, T.W. Simpson, C.J. Dickman, Topology Optimization Software for Additive Manufacturing: A Review of Current Capabilities and a Real-World Example, in ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (American Society of Mechanical Engineers, Charlotte, NC, 2016), pp. V02AT03A029–V02AT03A029Google Scholar
  53. 53.
    M.P. Bendsoe, O. Sigmund, Topology Optimization: Theory, Methods, and Applications (Springer, New York, NY, 2004)CrossRefGoogle Scholar
  54. 54.
    SolidThinking, SolidThinking Inspire (Altair Engineering, Troy, MI, 2016)Google Scholar
  55. 55.
    Alcoa Fastening Systems & Rings, Airplane Bearing Bracket Challenge (2015). Retrieved January 12, 2016 from
  56. 56.
    Y. Hahn, J.I. Cofer, Study of Parametric and Non-Parametric Optimization of a Rotor-Bearing System, in ASME Turbo Expo 2014: Turbine Technical Conference and Exposition (American Society of Mechanical Engineers, Düsseldorf, Germany, 2014), pp. V07AT28A001–V07AT28A001Google Scholar
  57. 57.
    T. Seifert, H. Riedel, Mechanism-based thermomechanical fatigue life prediction of cast iron. Part I: models. Int. J. Fatigue 32(8), 1358–1367 (2010)CrossRefGoogle Scholar

Copyright information

© American Foundry Society 2018

Authors and Affiliations

  1. 1.School of Engineering Design, Technology, and Professional ProgramsThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of Mechanical and Nuclear EngineeringThe Pennsylvania State UniversityUniversity ParkUSA

Personalised recommendations