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A cost model for the economic evaluation of in-situ monitoring tools in metal additive manufacturing

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  • Colosimo, Bianca Maria
  • Cavalli, Simona
  • Grasso, Marco

Abstract

The paper presents a cost model to evaluate the economic impact of defects and process instability in metal Additive Manufacturing (AM). The proposed model formulation adopts the main framework of previous seminal studies and extends it by considering the contribution of scrap fractions and in-situ monitoring performances on process and material costs, including pre- and post-processing operations. Three real industrial case studies (from dental, aerospace, and machinery sectors) were assessed to determine how the model can be used in the real industrial practice to (i) enhance the economic advantages of metal AM technologies by tackling process instability issues, (ii) assess the effectiveness of in-situ monitoring in the development of next generation metal AM systems, and (iii) define the performance specifications of in-situ monitoring solutions that yield sustainable cost savings in specific industrial applications. A further experimentation is presented to validate the cost model with respect to a benchmark reference.

Suggested Citation

  • Colosimo, Bianca Maria & Cavalli, Simona & Grasso, Marco, 2020. "A cost model for the economic evaluation of in-situ monitoring tools in metal additive manufacturing," International Journal of Production Economics, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:proeco:v:223:y:2020:i:c:s0925527319303597
    DOI: 10.1016/j.ijpe.2019.107532
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    References listed on IDEAS

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    1. Runze Huang & Matthew E. Riddle & Diane Graziano & Sujit Das & Sachin Nimbalkar & Joe Cresko & Eric Masanet, 2017. "Environmental and Economic Implications of Distributed Additive Manufacturing: The Case of Injection Mold Tooling," Journal of Industrial Ecology, Yale University, vol. 21(S1), pages 130-143, November.
    2. Mellor, Stephen & Hao, Liang & Zhang, David, 2014. "Additive manufacturing: A framework for implementation," International Journal of Production Economics, Elsevier, vol. 149(C), pages 194-201.
    3. Thomas-Seale, L.E.J. & Kirkman-Brown, J.C. & Attallah, M.M. & Espino, D.M. & Shepherd, D.E.T., 2018. "The barriers to the progression of additive manufacture: Perspectives from UK industry," International Journal of Production Economics, Elsevier, vol. 198(C), pages 104-118.
    4. Baumers, Martin & Dickens, Phill & Tuck, Chris & Hague, Richard, 2016. "The cost of additive manufacturing: machine productivity, economies of scale and technology-push," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 193-201.
    5. Weller, Christian & Kleer, Robin & Piller, Frank T., 2015. "Economic implications of 3D printing: Market structure models in light of additive manufacturing revisited," International Journal of Production Economics, Elsevier, vol. 164(C), pages 43-56.
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    Cited by:

    1. Naghshineh, Bardia & Carvalho, Helena, 2022. "The implications of additive manufacturing technology adoption for supply chain resilience: A systematic search and review," International Journal of Production Economics, Elsevier, vol. 247(C).
    2. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Ding, Jin & Baumers, Martin & Clark, Elizabeth A. & Wildman, Ricky D., 2021. "The economics of additive manufacturing: Towards a general cost model including process failure," International Journal of Production Economics, Elsevier, vol. 237(C).
    4. Beltagui, Ahmad & Gold, Stefan & Kunz, Nathan & Reiner, Gerald, 2023. "Special Issue: Rethinking operations and supply chain management in light of the 3D printing revolution," International Journal of Production Economics, Elsevier, vol. 255(C).

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