Details
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020 |
| Publisher | IEEE Computer Society |
| Pages | 91-95 |
| Number of pages | 5 |
| ISBN (electronic) | 9781538672204 |
| ISBN (print) | 978-1-5386-7221-1 |
| Publication status | Published - 2020 |
| Event | 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020 - Virtual, Singapore, Singapore Duration: 14 Dec 2020 → 17 Dec 2020 |
Publication series
| Name | IEEE International Conference on Industrial Engineering and Engineering Management |
|---|---|
| Volume | 2020-December |
| ISSN (Print) | 2157-3611 |
| ISSN (electronic) | 2157-362X |
Abstract
Factory planning is an important tool for manufacturing companies to raise their efficiency and to maintain their competitiveness by changing market or customer requirements. A special challenge is the acquisition of layout data and the processing of this data in suitable planning tools. Current approaches still measure manually or have to transfer acquired data from laser scanners by hand into planning tools, which leads to a high effort and error proneness.This paper presents a holistic concept for automated and systematic data acquisition and processing for factory planning processes.
Keywords
- 3D factory layout, 3D factory planning, 3D layout scan, Automated drone flight, Point cloud processing
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Business, Management and Accounting (miscellaneous)
- Engineering(all)
- Industrial and Manufacturing Engineering
- Engineering(all)
- Safety, Risk, Reliability and Quality
Cite this
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2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020. IEEE Computer Society, 2020. p. 91-95 9309902 (IEEE International Conference on Industrial Engineering and Engineering Management; Vol. 2020-December).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Automated data acquisition and processing for factory layout planning
AU - Melcher, D.
AU - Kuster, B.
AU - Overmeyer, L.
N1 - Funding Information: The work of Dominik Melcher within the IGF project 19170 N of the Society for Transport Management and Logistics (GVB) was funded via the German Federation of Industrial Research Associations (AiF) in the programme of Industrial Collective Research (IGF) by the Federal Ministry for Economic Affairs and Energy (BMWi) based on a decision of the German Bundestag
PY - 2020
Y1 - 2020
N2 - Factory planning is an important tool for manufacturing companies to raise their efficiency and to maintain their competitiveness by changing market or customer requirements. A special challenge is the acquisition of layout data and the processing of this data in suitable planning tools. Current approaches still measure manually or have to transfer acquired data from laser scanners by hand into planning tools, which leads to a high effort and error proneness.This paper presents a holistic concept for automated and systematic data acquisition and processing for factory planning processes.
AB - Factory planning is an important tool for manufacturing companies to raise their efficiency and to maintain their competitiveness by changing market or customer requirements. A special challenge is the acquisition of layout data and the processing of this data in suitable planning tools. Current approaches still measure manually or have to transfer acquired data from laser scanners by hand into planning tools, which leads to a high effort and error proneness.This paper presents a holistic concept for automated and systematic data acquisition and processing for factory planning processes.
KW - 3D factory layout
KW - 3D factory planning
KW - 3D layout scan
KW - Automated drone flight
KW - Point cloud processing
UR - http://www.scopus.com/inward/record.url?scp=85099736917&partnerID=8YFLogxK
U2 - 10.1109/IEEM45057.2020.9309902
DO - 10.1109/IEEM45057.2020.9309902
M3 - Conference contribution
AN - SCOPUS:85099736917
SN - 978-1-5386-7221-1
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 91
EP - 95
BT - 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
PB - IEEE Computer Society
T2 - 2020 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2020
Y2 - 14 December 2020 through 17 December 2020
ER -