Journal
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
Volume 225, Issue B12, Pages 2228-2239Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954405411406044
Keywords
additive manufacturing; rapid manufacturing; laser sintering; electricity; power; energy; energy consumption; power monitoring
Funding
- Additive Manufacturing Research Group
- Loughborough University
- M E Philips, Department of Mechanical Engineering, The University of Texas at Austin
- EPSRC [EP/I033335/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/I033335/1] Funding Source: researchfish
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The term additive manufacturing (AM) describes a collection of production techniques enabling the layer-by-layer manufacture of components using digital data and raw material as inputs. The AM technology variant most frequently used in the production of end use parts is laser sintering (LS). It has been suggested that efficient usage of the energy inputs is one of the advantages of the technology. This paper presents a comparative assessment of the electricity consumptions of two major polymeric LS platforms: the Sinterstation HiQ + HS from 3D Systems and the EOSINT P 390 from EOS GmbH. The energy inputs to a build consisting of two prosthetic parts were recorded during power-monitoring experiments conducted on both platforms. This paper injects clarity into the ongoing research on the AM energy consumption by applying a novel classification system; it is argued that the AM energy usage can be divided into the job-dependent, time-dependent, geometry-dependent, and Z-height-dependent energy consumption values. The recorded mean real power consumption conforms to the values that have been reported for similar platforms. The measured energy consumption rates are higher than reported elsewhere. It is also shown that the purely time-dependent energy consumption is the main energy drain. Furthermore, the presentation of results in the context of previous literature highlights the caveats attached to summary metrics of the AM input usage.
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