Material-design-process selection methodology for aircraft structural components: application to additive vs subtractive manufacturing processes

  • C. HodonouEmail author
  • M. Balazinski
  • M. Brochu
  • C. Mascle


Machining of aircraft structural components can waste up to 90% of the raw material. Therefore, evaluation of alternative manufacturing processes for those components is crucial for reducing the economic and environmental impacts of manufacturing. As the shape and material of a component must match the manufacturing process used, it is necessary to perform a redesign for manufacturing in order to compare manufacturing processes accurately. In this paper, an integrated material-design-process selection methodology is developed. Topology optimization, design for manufacturing (DFM) and design for additive manufacturing (DFAM) are used to design components satisfying the same functional requirements but shaped using different manufacturing processes. New selection criteria such as part weight and buy-to-fly ratio are used to rank material-design-process triplets with the analytic hierarchy process (AHP). The proposed methodology is applied to redesign an aircraft component for machined Al7075-T6 and the same component for selectively melted AlSi10Mg powders. Even though the yield strength of Al7075-T6 is 40% greater than that of AlSi10Mg, optimized components for machining and selective laser melting meet the yield strength security factor while remaining competitive in terms of mass. Although the selective laser melted component is about seven times more expensive to produce than the machined one, it remains competitive considering functional and economic criteria.


Manufacturing process selection Topology optimization Design for manufacturing Design for additive manufacturing Environment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



The research presented in the present paper was financed in part by the Fonds de Recherche du Québec – Nature et Technologies funded by the intermediary of the Aluminium Research Centre – REGAL. The authors would like to thank Rio Tinto Aluminium and the Ministère de l’Enseignement Supérieur et de la Recherche Scientifique of Côte d’Ivoire for their support.


  1. 1.
    Ashby MF (2008) The CES EduPack Database of Natural and Man-made Materials. Cambridge University and Granta Design, CambridgeGoogle Scholar
  2. 2.
    Ashby MF, Brechet YJM, Cebon D, Salvo L (2004) Selection strategies for materials and processes. Mater Des 25:51–67CrossRefGoogle Scholar
  3. 3.
    Babu S, Love LJ, Peter W, Dehoff R (2016) Report on additive manufacturing for large-scale metals workshop. Oak Ridge National Laboratory, 10–11Google Scholar
  4. 4.
    Baumers M, Tuck C, Wildman R, Ashcroft I, Rosamond E, Hague R (2012) Combined build-time, energy consumption and cost estimation for direct metal laser sintering. In: Twenty third annual international solid freeform fabrication symposium - an additive manufacturing conference, pp 932–944Google Scholar
  5. 5.
    Boothroyd G, Dewhurst P, Knight WA (2002) Product design for manufacture and assembly. CRC Press placeGoogle Scholar
  6. 6.
    Doutre P-T, Morreton E, Vo TH, Marin P, Pourroy F, Prushomme G, Vignat F (2017) Comparison of some approaches to define a CAD model from topological optimization in design for additive manufacturing. In: Eynard B, Nigrelli V, Oliveri S, Peris-Fajarnes G, Rizzuti S (eds) Advances on mechanics, design Engineering and Manufacturing. Lecture Notes in Mechanical Engineering. Springer, ChamGoogle Scholar
  7. 7.
    Doutre P-T, Vo TH, Marin P, Pourroy F, Prudhomme G, Vignat F (2015) Optimisation topologique: outil clé pour la conception des pièces produites par fabrication additive? 14ème Colloque National AIP PRIMECAGoogle Scholar
  8. 8.
    Jung J -Y (2002) Manufacturing cost estimation for machined parts based on manufacturing features. J Intell Manuf 13:227–238CrossRefGoogle Scholar
  9. 9.
    Mançanares CG, Zancul ES, Da Silva JC, Miguel PAC (2015) Additive manufacturing process selection based on parts’ selection criteria. Int J Adv Manuf Technol 80:1007–1014CrossRefGoogle Scholar
  10. 10.
    Nguyen VD, Martin P (2015) Product design-process selection-process planning integration based on modeling and simulation. Int J Adv Manuf Technol 77:187–201CrossRefGoogle Scholar
  11. 11.
    Priarone PC, Giuseppe I (2017) Towards criteria for sustainable process selection: on the modelling of pure subtractive versus additive/subtractive integrated manufacturing approaches. J Clean Prod 144:57–68CrossRefGoogle Scholar
  12. 12.
    Reddy KSN, Maranan V, Simpson TW, Palmer T, Dickman CJ (2016) 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 v02AT03a030Google Scholar
  13. 13.
    Sai Nithin RK, Ferguson I, Frecker M, Simpson TW, Dickman CJ (2016) 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 v02AT03a029Google Scholar
  14. 14.
    Yim S, Rosen D (2012) Build time and cost models for additive manufacturing process selection. In: ASME 2012 international design engineering technical conferences and computers and information in engineering conference, pp 375–382Google Scholar
  15. 15.
    Zaman UK, Rivette M, Siadat A, Mousavi SM (2018) Integrated product-process design: material and manufacturing process selection for additive manufacturing using multi-criteria decision making. Robot Comput Integr Manuf 51:169–180CrossRefGoogle Scholar
  16. 16.
    Zaman UK, Siadat A, Rivette M, Baqai AA, Qiao L (2016) Integrated product-process design to suggest appropriate manufacturing technology: a review. Int J Adv Manuf Technol 91:1–22CrossRefGoogle Scholar
  17. 17.
    Zhou M, Fleury R, Shyy Y -K, Thomas H, Brennan J-M (2002) Progress in topology optimization with manufacturing constraints. In: 9th AIAA/ISSMO Symposium on multidisciplinary analysis and optimization, pp 5614Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • C. Hodonou
    • 1
    • 2
    Email author
  • M. Balazinski
    • 1
    • 2
  • M. Brochu
    • 1
    • 2
  • C. Mascle
    • 1
    • 2
  1. 1.Aluminium Research Centre-REGALÉcole Polytechnique de MontréalMontrealCanada
  2. 2.Mechanical Engineering Department, École Polytechnique de MontréalQuebecCanada

Personalised recommendations