Evaluating the cost competitiveness of metal additive manufacturing – A case study with metal material extrusion
Permanent lenke
https://hdl.handle.net/10037/30713Dato
2023-06-25Type
Journal articleTidsskriftartikkel
Peer reviewed
Sammendrag
Metal additive manufacturing (MAM) is a rapidly advancing manufacturing process with the potential to
replace or supplement existing conventional manufacturing processes. MAM is currently associated with a
high investment cost and is mostly seen in centralized manufacturing configurations with low-volume and
high-value products. This paper evaluates the cost competitiveness of MAM by investigating a novel lowcost MAM process – metal material extrusion (Metal MEX). Metal MEX, unlike other MAM processes such as
powder bed fusion (PBF), has a lower investment cost, faster production rate, and simpler operations, which
has opened new opportunities for distributed low-cost production through MAM. A cost model of the metal
MEX process - Atomic Diffusion Additive Manufacturing (ADAM) that focused on the production costs was
presented. The cost model was further used to evaluate the cost competitiveness of metal MEX through a
case study. Three production scenarios were compared to CNC machining, where it was shown that metal
MEX, under specific production conditions, has the capability to be cost-competitive with CNC machining.
Based on the proposed cost model and case study, a conceptual cost framework is presented, giving key
insight into how a MAM cost advantage can be generated by incorporating the benefits of MAM.
Er en del av
Sæterbø, M. (2024). A Decision Support Framework for Metal Additive Manufacturing Adoption in Small and Medium-Sized Enterprises. (Doctoral thesis). https://hdl.handle.net/10037/35740Forlag
ElsevierSitering
Sæterbø, Solvang. Evaluating the cost competitiveness of metal additive manufacturing – A case study with metal material extrusion. CIRP - Journal of Manufacturing Science and Technology. 2023Metadata
Vis full innførselSamlinger
Copyright 2023 The Author(s)