Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151210
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWang, Yuanbinen_US
dc.contributor.authorZheng, Paien_US
dc.contributor.authorXu, Xunen_US
dc.contributor.authorYang, Huayongen_US
dc.contributor.authorZou, Junen_US
dc.date.accessioned2021-06-29T04:46:02Z-
dc.date.available2021-06-29T04:46:02Z-
dc.date.issued2019-
dc.identifier.citationWang, Y., Zheng, P., Xu, X., Yang, H. & Zou, J. (2019). Production planning for cloud-based additive manufacturing—A computer vision-based approach. Robotics and Computer-Integrated Manufacturing, 58, 145-157. https://dx.doi.org/10.1016/j.rcim.2019.03.003en_US
dc.identifier.issn0736-5845en_US
dc.identifier.other0000-0002-9988-6790-
dc.identifier.other0000-0002-2329-8634-
dc.identifier.other0000-0001-6294-8153-
dc.identifier.urihttps://hdl.handle.net/10356/151210-
dc.description.abstractCloud-based additive manufacturing (AM) has shown its potential in the market in recent years. When the demand increases, it becomes more important to efficiently schedule tasks to achieve lower production time and cost. Current solutions are either less efficient or over-simplified the problem in this situation. Therefore, an intelligent AM production planning system is proposed using computer vision algorithms. It firstly sorts tasks based on their heights, areas and remaining time to deadline. Then, models are projected on the printing plane and an improved vision-based method is applied to efficiently find high quality packing solutions. A comparative study has been conducted to verify the packing result and efficiency. At last, a case study has been displayed to illustrate the usefulness of the proposed method.en_US
dc.language.isoenen_US
dc.relation.ispartofRobotics and Computer-Integrated Manufacturingen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titleProduction planning for cloud-based additive manufacturing—A computer vision-based approachen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.identifier.doi10.1016/j.rcim.2019.03.003-
dc.identifier.scopus2-s2.0-85062502010-
dc.identifier.volume58en_US
dc.identifier.spage145en_US
dc.identifier.epage157en_US
dc.subject.keywordsAdditive Manufacturingen_US
dc.subject.keywordsCloud Manufacturingen_US
dc.description.acknowledgementThis work was supported by the National Natural Science Foundation of China [Grant No. 51890885].en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:MAE Journal Articles

Page view(s)

49
Updated on Dec 1, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.