Part decomposition efficiency expectation evaluation in additive manufacturing process planning

Yaroslav Garashchenko and Miroslaw Rucki

International Journal of Production Research, 2021, vol. 59, issue 22, 6745-6757

Abstract: In this paper, research results are presented and discussed on the efficient use of additive manufacturing (AM) machine workspace with a specific focus on the features of part construction and decomposition, which provide savings of material and energy. Statistical analysis of the distribution of material by subspaces revealed some relationship between construction features and the effectiveness of part decomposition. The initial triangulated model was converted into a voxel model, and the latter is analyzed with the proposed algorithm. The workspace of an AM machine was divided into subspaces of the same volume with parallel steadily distributed planes perpendicular to the coordinate axes. Based on the models of typical industrial parts, it was proving that the algorithm was able to analyze the effectiveness of part decomposition. Moreover, some indexes were proposed to allow the quantitative analysis of part decomposition and packing (workspace planning task) effectiveness. The proposed index of the specific volume of utilised workspace enabled the minimising of the cost of given parts by using AM processes.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1824084 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:59:y:2021:i:22:p:6745-6757

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2020.1824084

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().