Analysis of air flow around the painting line for dust reduction: an experimental and numerical study
The repair of paint work defects in the painting production process is done by running the parts through the painting process again. It is done together with the requisite quality control routines and involves a very large proportion of the operating costs. The dust defect which ranges between 40...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en en |
| Published: |
Penerbit Akademia Baru
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/87976/1/87976_Analysis%20of%20Air%20Flow%20Around%20the%20Painting_article.pdf http://irep.iium.edu.my/87976/2/87976_Analysis%20of%20Air%20Flow%20Around%20the%20Painting_scopus.pdf http://irep.iium.edu.my/87976/ http://www.akademiabaru.com/submit/index.php/cfdl/article/view/1101 |
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| Summary: | The repair of paint work defects in the painting production process is done by running
the parts through the painting process again. It is done together with the requisite
quality control routines and involves a very large proportion of the operating costs. The
dust defect which ranges between 40% to 50% is found to be the top and highest
rejection at the painting line. Hence, this paper is focused to identify the effectiveness
of applying Computational Fluid Dynamic (CFD) to identify the air flow and the
turbulence pattern to investigate the movement and the dust particle concentration
in painting line. Renormalization Group (RNG) k-ε turbulence model is used in CFD to
predict the particles’ movement and concentration. Five new models including the
current painting line design are proposed and tested. The painting line model labelled
as Model F is found to be the best model to minimize and reduce the dust particle
concentration inside the painting line environment with 96.01% of percentage particle
is flushed out at air velocity of 0.1 m/s. Along with results from numerical simulation
using CFD, the experimental data is also collected using an air flow meter in a smallscale model painting line. Both data from experiment and CFD simulation are analysed
and compared in order to measure the effectiveness of the result. The average relative
error for Model F is recorded at 4.76%. The results from this study is recommended to
be considered as one of the benchmarks for future design of automotive painting line. |
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