Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering

Packaging Solution Optimization of Automotive Parts and Its Ocean Shipping Test

Authors
C.W. Chen, F.X. Yang, J. Xie, D.D. Yang
Corresponding Author
C.W. Chen
Available Online July 2015.
DOI
10.2991/aiie-15.2015.149How to use a DOI?
Keywords
packaging solution optimization; automotive parts; VCI anti-rust packaging; ocean shipping test
Abstract

To obtain optimized packaging solution of the exported automotive parts to avoid rust during logistics. The old packaging solution was studied. Five improved Volatile Corrosion Inhibitor (VCI) anti-rust packaging solution was designed and tested by real ocean shipping. Optimized anti-rust packaging solutions gained by analyzing and comparing their anti-rust packaging results and packaging costs via ocean shipping test. The excessive packaging was avoided, the packaging cost was reduced and the packing work efficiency was increased. The method and results were valuable reference for automotive parts anti-rust packaging design and engineering application.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-70-7
ISSN
1951-6851
DOI
10.2991/aiie-15.2015.149How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - C.W. Chen
AU  - F.X. Yang
AU  - J. Xie
AU  - D.D. Yang
PY  - 2015/07
DA  - 2015/07
TI  - Packaging Solution Optimization of Automotive Parts and Its Ocean Shipping Test
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 558
EP  - 560
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.149
DO  - 10.2991/aiie-15.2015.149
ID  - Chen2015/07
ER  -