The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
The cost of additive manufacturing: machine productivity, economies of scale and technology-push
Open accessAbstract
As part of the cosmos of digital fabrication technology, Additive Manufacturing (AM) systems are able to manufacture three-dimensional components and products directly from raw material and 3D design data. The layer-by-layer operating process of these systems does not require the use of tools, moulds or dies. Technology observers speculate that AM will have a profound economic impact on the manufacturing sector and indeed on wider society. By constructing a model of production cost for two different AM systems used commercially for the manufacture of end-use metal parts, Electron Beam Melting (EBM) and Direct Metal Laser Sintering (DMLS), this paper performs an inter-process comparison of cost performance. High specific costs, measured at £2.39 and £6.18 per cm3 of material deposited respectively, are identified as a central impediment to more widespread technology adoption of such additive systems. The research demonstrates differing levels of system productivity, suggesting that the observed deposition rates are not sufficient for the adoption of EBM and DMLS in high volume manufacturing applications. Despite the absence of amortisable tooling costs, the analysis also reveals that economies of scale are achievable in AM. The results reached are further discussed in the light of the varying strategic requirements posed by the market-pull and technology-push modes of innovation which are both found in the AM industry.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · An Integrated Approach to Communication Theory and Research · doi:10.4324/9780203710753-35 · Cited by 37,322
Competitive Strategy: Techniques for Analyzing Industries and Competitors
(1980) · Journal of Sustainable Competitive Intelligence · doi:10.24883/iberoamericanic.v2i2.38 · Cited by 16,592
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 13,723
Mass customization: The new frontier in business competition
(1999) · Journal of Manufacturing Systems · doi:10.1016/s0278-6125(99)90108-5 · Cited by 2,322
Additive manufacturing and its societal impact: a literature review
Huang, S. H., Liu, P., Mokasdar, A., & Hou, L. (2013) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-012-4558-5 · Cited by 1,862
Microeconomics of technology adoption
Foster, A. D., & Rosenzweig, M. R. (2010) · Annual Review of Economics · doi:10.1146/annurev.economics.102308.124433 · Cited by 1,055
Laser sintering of polyamides and other polymers
Goodridge, R. D., Tuck, C. J., & Hague, R. J. M. (2012) · Progress in Materials Science · doi:10.1016/j.pmatsci.2011.04.001 · Cited by 835
Self-citationMass customization: The new frontier in business competition
Niblock, M. (1993) · Long Range Planning · doi:10.1016/0024-6301(93)90218-5 · Cited by 664
Economics of additive manufacturing for end-usable metal parts
Atzeni, E., & Salmi, A. (2012) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-011-3878-1 · Cited by 630
The Productivity Dilemma: Roadblock to Innovation in the Automobile Industry
Black, G., & Abernathy, W. J. (1979) · Southern Economic Journal · doi:10.2307/1057440 · Cited by 610
Brem, A., & Voigt, K.-I. (2009) · Technovation · doi:10.1016/j.technovation.2008.06.003 · Cited by 467
3D Printing Disrupts Manufacturing: How Economies of One Create New Rules of Competition
Petrick, I. J., & Simpson, T. W. (2013) · Research-Technology Management · doi:10.5437/08956308x5606193 · Cited by 443
Analysis of rapid manufacturing—using layer manufacturing processes for production
Hopkinson, N., & Dicknes, P. (2003) · Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science · doi:10.1243/095440603762554596 · Cited by 412
Environmental aspects of laser-based and conventional tool and die manufacturing
Morrow, W. R., Qi, H., Kim, I., Mazumder, J., & Skerlos, S. J. (2007) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2005.11.030 · Cited by 380
Thermodynamic Analysis of Resources Used in Manufacturing Processes
Gutowski, T. G., Branham, M. S., Dahmus, J. B., Jones, A. J., Thiriez, A., & Sekulic, D. P. (2009) · Environmental Science & Technology · doi:10.1021/es8016655 · Cited by 376
Part orientation and build cost determination in layered manufacturing
Alexander, P., Allen, S., & Dutta, D. (1998) · Computer-Aided Design · doi:10.1016/s0010-4485(97)00083-3 · Cited by 374
The Economics of Technological Diffusion
Stoneman, P. L. (2001) · Cited by 344
Durable Goods Theory for Real World Markets
Waldman, M. (2003) · Journal of Economic Perspectives · doi:10.1257/089533003321164985 · Cited by 316
Facchini, L., Magalini, E., Robotti, P., & Molinari, A. (2009) · Rapid Prototyping Journal · doi:10.1108/13552540910960262 · Cited by 290
Roadmapping a disruptive technology: A case study
Walsh, S. T. (2004) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2003.10.003 · Cited by 279
Byun, H.-S., & Lee, K. H. (2006) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2005.03.001 · Cited by 205
Managing Innovation and Entrepreneurship in Technology-Based Firms
Martin, M. (1994) · Cited by 184
Economies of Scale in Industrial Plants
Haldi, J., & Whitcomb, D. (1967) · Journal of Political Economy · doi:10.1086/259293 · Cited by 180
Transparency Built‐in: Energy Consumption and Cost Estimation for Additive Manufacturing
Baumers, M., Tuck, C., Wildman, R., Ashcroft, I., Rosamond, E., & Hague, R. (2013) · Journal of Industrial Ecology · doi:10.1111/j.1530-9290.2012.00512.x · Cited by 177
Self-citationRuffo, M., & Hague, R. (2007) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1243/09544054jem894 · Cited by 152
Self-citationRapid manufacturing facilitated customization
Tuck, C. J., Hague, R., Ruffo, M., Ransley, M., & Adams, P. (2008) · International Journal of Computer Integrated Manufacturing · doi:10.1080/09511920701216238 · Cited by 149
Self-citationEnergy Inputs to Additive Manufacturing: Does Capacity Utilization Matter?
Baumers, M., Tuck, C. J., Wildman, R. D., Ashcroft, I., & Hague, R. (2011) · doi:10.26153/tsw/15275 · Cited by 148
Self-citationProductivity, Technology and Economic Growth: What is the Relationship?
Carlaw, K. I., & Lipsey, R. G. (2003) · Journal of Economic Surveys · doi:10.1111/1467-6419.00201 · Cited by 135
The Age of Diminished Expectations: U. S. Economic Policy in the 1990s
Leonard, J. E., & Krugman, P. (1992) · Southern Economic Journal · doi:10.2307/1059864 · Cited by 119
MEGAMISTAKES: Forecasting and the Myth of Rapid Technological Change
Schnaars, S. P. (1989) · Medical Entomology and Zoology · Cited by 103
A neural network-based build time estimator for layer manufactured objects
Angelo, L. D., & Stefano, P. D. (2011) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-011-3284-8 · Cited by 87
A Method to Eliminate Anchors/Supports from Directly Laser Melted Metal Powder Bed Processes
Mumtaz, K., Vora, P., & Hopkinson, N. (2011) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · doi:10.26153/tsw/15277 · Cited by 33
Wong, H., & Eyers, D. R. (2010) · Springer eBooks · doi:10.1007/978-3-642-04313-0_10 · Cited by 14
Cited by
Applications of additive manufacturing in the construction industry – A forward-looking review
Delgado Camacho, D., Clayton, P., O'Brien, W. J., Seepersad, C., Juenger, M., Ferron, R., & Salamone, S. (2018) · Automation in Construction · doi:10.1016/j.autcon.2017.12.031 · Cited by 538
Sustainability of additive manufacturing: An overview on its energy demand and environmental impact
Peng, T., Kellens, K., Tang, R., Chen, C., & Chen, G. (2018) · Additive Manufacturing · doi:10.1016/j.addma.2018.04.022 · Cited by 426
Defining and assessing industry 4.0 maturity levels – case of the defence sector
Bibby, L., & Dehe, B. (2018) · Production Planning & Control · doi:10.1080/09537287.2018.1503355 · Cited by 417
Why manufacturers adopt additive manufacturing technologies: The role of sustainability
Niaki, M. K., Torabi, S. A., & Nonino, F. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.03.019 · Cited by 298
Metadata
- Authors
- Baumers, M., Dickens, P., Tuck, C., & Hague, R.
- Venue
- Technological Forecasting and Social Change
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 102
- Pages
- 193-201
- ISSN
- 0040-1625 (ISSN-L)
- OpenAlex
- W2010360743
- Cited by
- 658
- References
- 33
- FWCI
- 43.48
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.