Skip to main content

Advertisement

Log in

Integrated design exploration of products, materials, and processes in additive manufacturing using inverse design method

  • Original Paper
  • Published:
International Journal on Interactive Design and Manufacturing (IJIDeM) Aims and scope Submit manuscript

Abstract

Additive manufacturing (AM) has multiple advantages over traditional manufacturing processes. However, AM has limitations such as the uncertainty of properties or performance of final products. This arises from the lack of understanding of physical phenomena in the AM processes. The mechanical properties and performance of AM products are typically determined experimentally which is time-consuming and expensive. Thus, there is a need for computational design tools and methods that can assist designers with efficient decision-making to achieve products with desired properties by tailoring different stages of the manufacturing process. An inverse design method for integrated design space exploration of products, materials, and manufacturing processes for AM domain is presented. The method is presented for a manufacturing process where conventional and AM processes are integrated to realize AM products. The method uses sequential information flow in the process-structure–property-performance(p–s–p–p) space of each manufacturing process to perform design space exploration and facilitates flow of information between the processes to achieve products with desired properties. The compromise Decision Support Problem (cDSP) forms the primary mathematical construct of the method to generate satisficing design solutions at each stage of the manufacturing processes to meet the end goals of the products. The method is discussed using a material extrusion process where the designer uses a non-commercial filament to manufacture AM products with desired properties. Multiple cDSP based inverse designs are formulated to make design decisions at different stages of the integrated manufacturing process. This method can be modified to include more steps in the process or expand the design space for other AM problems and processes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Huang, S.H., Liu, P., Mokasdar, A., Hou, L.: Additive manufacturing and its societal impact: a literature review. Int. J. Adv. Manuf. Technol. 67(5), 1191–1203 (2013). https://doi.org/10.1007/s00170-012-4558-5

    Article  Google Scholar 

  2. Huang, R., Riddle, M., Graziano, D., Warren, J., Das, S., Nimbalkar, S., Cresko, J., Masanet, E.: Energy and emissions saving potential of additive manufacturing: the case of lightweight aircraft components. J. Clean. Prod. 135, 1559–1570 (2016). https://doi.org/10.1016/j.jclepro.2015.04.109

    Article  Google Scholar 

  3. Yan, W., Lin, S., Kafka, O.L., Lian, Y., Yu, C., Liu, Z., Yan, J., Wolff, S., Wu, H., Ndip-Agbor, E., Mozaffar, M., Ehmann, K., Cao, J., Wagner, G.J., Liu, W.K.: Data-driven multi-scale multi-physics models to derive process-structure-property relationships for additive manufacturing. Comput. Mech. 61(5), 521–541 (2018). https://doi.org/10.1007/s00466-018-1539-z

    Article  MATH  Google Scholar 

  4. Lu, Y., Yang, Z., Eddy, D., Krishnamurty, S.: Self-improving additive manufacturing knowledge management. In: Proceedings of the ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, (2018), https://doi.org/10.1115/DETC2018-85996.

  5. Rosen, D.W.: A set-based design method for material-geometry structures by design space mapping. In: Proceedings of the ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, https://doi.org/10.1115/DETC2015-46760(2015).

  6. Yadroitsev, I.: Selective laser melting: direct manufacturing of 3D-objects by selective laser melting of metal powders: LAP LAMBERT Academic Publishing (2009)

  7. Chohan, J.S., Singh, R.: Pre and post processing techniques to improve surface characteristics of FDM parts: a state of art review and future applications. Rapid Prototyp. J. 23(3), 495–513 (2017). https://doi.org/10.1108/RPJ-05-2015-0059

    Article  Google Scholar 

  8. Ning, F., Cong, W., Qiu, J., Wei, J., Wang, S.: Additive manufacturing of carbon fiber reinforced thermoplastic composites using fused deposition modeling. Compos. B Eng. 80, 369–378 (2015). https://doi.org/10.1016/j.compositesb.2015.06.013

    Article  Google Scholar 

  9. Alafaghani, A., Qattawi, A., Alrawi, B., Guzman, A.: Experimental optimization of fused deposition modelling processing parameters: a design-for-manufacturing approach. Proc. Manuf. 10, 791–803 (2017). https://doi.org/10.1016/j.promfg.2017.07.079

    Article  Google Scholar 

  10. Mohamed, O.A., Masood, S.H., Bhowmik, J.L.: Optimization of fused deposition modeling process parameters: a review of current research and future prospects. Adv. Manuf. 3(1), 42–53 (2015). https://doi.org/10.1007/s40436-014-0097-7

    Article  Google Scholar 

  11. Thrimurthulu, K., Pandey, P.M., Venkata Reddy, N.: Optimum part deposition orientation in fused deposition modeling. Int. J. Mach. Tools Manuf. 44(6), 585–594 (2004). https://doi.org/10.1016/j.ijmachtools.2003.12.004

    Article  MATH  Google Scholar 

  12. Christiyan, K.G.J., Chandrasekhar, U., Venkateswarlu, K.: A study on the influence of process parameters on the Mechanical Properties of 3D printed ABS composite. IOP Conf. Ser. Mater. Sci. Eng. 114, 012109 (2016)

    Article  Google Scholar 

  13. Ahn, S.H., Montero, M., Odell, D., Roundy, S., Wright, P.K.: Anisotropic material properties of fused deposition modeling ABS. Rapid Prototyp. J. 8(4), 248–257 (2002). https://doi.org/10.1108/13552540210441166

    Article  Google Scholar 

  14. Rayegani, F., Onwubolu, G.C.: Fused deposition modelling (FDM) process parameter prediction and optimization using group method for data handling (GMDH) and differential evolution (DE). Int. J. Adv. Manuf. Technol. 73(1), 509–519 (2014). https://doi.org/10.1007/s00170-014-5835-2

    Article  Google Scholar 

  15. Masood, S.H., Mau, K., Song, W.Q.: Tensile properties of processed FDM polycarbonate material. Mater. Sci. Forum 654–656, 2556–2559 (2010). https://doi.org/10.4028/www.scientific.net/MSF.654-656.2556

    Article  Google Scholar 

  16. Nikzad, M., Masood, S.H., Sbarski, I.: Thermo-mechanical properties of a highly filled polymeric composites for Fused Deposition Modeling. Mater. Des. 32(6), 3448–3456 (2011). https://doi.org/10.1016/j.matdes.2011.01.056

    Article  Google Scholar 

  17. Boparai, K.S., Singh, R., Fabbrocino, F., Fraternali, F.: Thermal characterization of recycled polymer for additive manufacturing applications. Compos. B Eng. 106, 42–47 (2016). https://doi.org/10.1016/j.compositesb.2016.09.009

    Article  Google Scholar 

  18. Singh, R. and Singh, S.: Development of Nylon based FDM filament for rapid tooling application. J. Instit. Eng. (India) Ser. C, 95(2), 103–108 (2014). https://doi.org/10.1007/s40032-014-0108-2.

  19. Raveverma, P., Ibrahim, M., Sa’ude, N., Yarwindran, M., Nasharuddin, M.: Mechanical behaviour study on SBR/EVA composite for FDM feedstock fabrication, AIP Conference Proceedings, 1831(1), 020011 (2017). https://doi.org/10.1063/1.4981152.

  20. Osman, M.A., Atia, M.R.A.: Investigation of ABS-rice straw composite feedstock filament for FDM. Rapid Prototyp. J. 24(6), 1067–1075 (2018). https://doi.org/10.1108/RPJ-11-2017-0242

    Article  Google Scholar 

  21. Sodeifian, G., Ghaseminejad, S., Yousefi, A.A.: Preparation of polypropylene/short glass fiber composite as Fused Deposition Modeling (FDM) filament. Results Phys. 12, 205–222 (2019). https://doi.org/10.1016/j.rinp.2018.11.065

    Article  Google Scholar 

  22. Shofner, M.L., Lozano, K., Rodríguez-Macías, F.J., Barrera, E.V.: Nanofiber-reinforced polymers prepared by fused deposition modeling. J. Appl. Polym. Sci. 89(11), 3081–3090 (2003). https://doi.org/10.1002/app.12496

    Article  Google Scholar 

  23. Zhong, W., Li, F., Zhang, Z., Song, L., Li, Z.: Short fiber reinforced composites for fused deposition modeling. Mater. Sci. Eng., A 301(2), 125–130 (2001). https://doi.org/10.1016/S0921-5093(00)01810-4

    Article  Google Scholar 

  24. Fullwood, D.T., Niezgoda, S.R., Adams, B.L., Kalidindi, S.R.: Microstructure sensitive design for performance optimization. Prog. Mater Sci. 55(6), 477–562 (2010). https://doi.org/10.1016/j.pmatsci.2009.08.002

    Article  Google Scholar 

  25. Kalidindi, S.R., Niezgoda, Stephen, R., Giacomo L.I., Fast, T.: A novel framework for building materials knowledge systems. Comput. Mater. Continua, 17(2): 103–126 (2010).

  26. McDowell, D.L., Microstructure-sensitive computational structure-property relations in materials design. In: Computational materials system design, Springer, Cham. pp. 1–25 (2018). https://doi.org/10.1007/978-3-319-68280-8_1.

  27. Orlande, H.R.B.: Inverse problems in heat transfer: new trends on solution methodologies and applications, J. Heat Transfer, 134(3) (2012). https://doi.org/10.1115/1.4005131.

  28. Nellippallil, A.B., Rangaraj, V., Gautham, B.P., Singh, A.K., Allen, J.K., Mistree, F.: An inverse, decision-based design method for integrated design exploration of materials, products, and manufacturing processes. J. Mech. Des., 140(11), (2018). https://doi.org/10.1115/1.4041050.

  29. Nellippallil, A.B., Mohan, P., Allen, J.K., and Mistree, F.: Inverse Thermo-Mechanical Processing (ITMP) design of a steel rod during hot rolling process. In: Proceedings of the ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering, https://doi.org/10.1115/DETC2019-97390(2019).

  30. Ahmed, S., Goh, C.-H., Allen, J.K., Mistree, F., Zagade, P., Gautham, B.P.: Hot forging of automobile steel gear blanks: an exploration of the solution space, In: Proceedings of the ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, https://doi.org/10.1115/DETC2014-34197(2014).

  31. Shukla, R., Kulkarni, N.H., Gautham, B.P., Singh, A.K., Mistree, F., Allen, J.K., Panchal, J.H.: Design exploration of engineered materials, products, and associated manufacturing processes. JOM 67(1), 94–107 (2015). https://doi.org/10.1007/s11837-014-1216-4

    Article  Google Scholar 

  32. Schoinochoritis, B., Chantzis, D., Salonitis, K.: Simulation of metallic powder bed additive manufacturing processes with the finite element method: a critical review. Proc. Instit. Mech. Eng. Part B J. Eng. Manuf. 231(1), 96–117 (2015). https://doi.org/10.1177/0954405414567522

    Article  Google Scholar 

  33. Markl, M., Körner, C.: Multiscale modeling of powder bed-based additive manufacturing. Annu. Rev. Mater. Res. 46(1), 93–123 (2016). https://doi.org/10.1146/annurev-matsci-070115-032158

    Article  Google Scholar 

  34. Mistree, F., Hughes, O. and Bras, B.: The compromise decision support problem and the adaptive linear programming algorithm, in structural optimization: status and promise. Am. Instit. Aeronaut. Astronaut., 247–286, (1993).

  35. Rolander, N., Rambo, J., Joshi, Y., Allen, J.K., Mistree, F.: An approach to robust design of turbulent convective systems. J. Mech. Des. 128(4), 844–855 (2006). https://doi.org/10.1115/1.2202882

    Article  Google Scholar 

  36. Nguyen, N., Mistree, F.: Design of horizontal pressure vessels using the decision support problem technique. J. Mech. Transmissions, Automat. Design 108(2), 203–210 (1986). https://doi.org/10.1115/1.3260803

    Article  Google Scholar 

  37. Chen, W., Meher-Homji, C.B., Mistree, F.: Compromise: an effective approach for condition-based maintenance management of gas turbines. Eng. Optim. 22(3), 185–201 (1994). https://doi.org/10.1080/03052159408941333

    Article  Google Scholar 

  38. Kulkarni, N., Gautham, B.P., Zagade, P., Panchal, J., Allen, J.K., Mistree, F.: Exploring the geometry and material space in gear design. Eng. Optim. 47(4), 561–577 (2015). https://doi.org/10.1080/0305215X.2014.908868

    Article  Google Scholar 

  39. Deka, A., Nellippallil, A.B., Hall, J.: Goal-Oriented Inverse Design (GoID) of feedstock filament for fused deposition modeling. In: Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, https://doi.org/10.1115/DETC2021-70503(2021).

  40. Bras, B., Mistree, F.: Robust design using compromise decision support problems. Eng. Optim. 21(3), 213–239 (1993). https://doi.org/10.1080/03052159308940976

    Article  Google Scholar 

  41. Singh, R., Singh, S., Mankotia, K.: Development of ABS based wire as feedstock filament of FDM for industrial applications. Rapid Prototyp. J. 22(2), 300–310 (2016). https://doi.org/10.1108/RPJ-07-2014-0086

    Article  Google Scholar 

  42. Sood, A.K.: Study on Parametric Optimization of Fused Deposition Modelling (FDM) Process, PhD Dissertation, National Institute of Technology, Rourkela (2011).

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: Angshuman Deka; Methodology: Angshuman Deka, Anand Balu Nellippallil; Formal analysis and investigation: Angshuman Deka; Writing—original draft preparation: Angshuman Deka; Writing—review and editing: Angshuman Deka, Anand Balu Nellippallil, John Hall; Supervision: John Hall.

Corresponding author

Correspondence to John Hall.

Ethics declarations

Conflicts of interest

Not applicable.

Code availability

DSIDES: University of Oklahoma (USA) server.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deka, A., Nellippallil, A.B. & Hall, J. Integrated design exploration of products, materials, and processes in additive manufacturing using inverse design method. Int J Interact Des Manuf 16, 717–731 (2022). https://doi.org/10.1007/s12008-022-00873-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12008-022-00873-6

Keywords

Navigation