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Computational Modeling of Relevant Automotive Rotary Spray Painting Process

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Automotive Painting Technology

Abstract

The intent of this chapter is to provide a non-exhaustive but useful guide to the capabilities of computational modeling to help understand the multiple rotary phenomena coexisting in the automotive rotary spray painting process. This manufacturing process has been extensively used to coat automobile bodies in assembly plants. For the last three decades, auto makers as well as spray painting equipment manufacturers have dedicated substantial efforts to understand rotary atomization and to develop more efficient and versatile atomizers. Despite these efforts, it is accepted that the current level of understanding is not sufficient to accurately assess the operation of commercially available rotary bell spray painting systems. The reasons for this lack of understanding are two fold: the inherent complex nature of the rotary bell painting process and the traditional experience-based development of these types of systems. In addition, there is a limitation in what experimentation and theoretical studies alone can provide to enhance both the desired understanding and the efficiency of the paint application process. Based on this realization, efforts have been oriented toward using computational modeling as a new tool to develop this understanding. However, the use of computational modeling has proven to be not an easy task due to the high speed of translation and rotation of the atomizer in real scenarios, the different scales of the phenomena going from micrometer at the rotary cup paint film level to meter at the painted part and spray booth level, the complicated rheology of the paint material (especially for dispersed-type paints), etc.

The research efforts leading to the results presented herein were in its majority financially supported by Toyota, Honda and Nissan. We are very grateful to these companies for their contribution and vision. Without both their financial support and the advice of their plant site engineers, this work would not have been completed successfully.

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Notes

  1. 1.

    This amount does not include other costs that are consequences of the generated overspray such as overspray capturing, booth and equipment periodical cleaning, paint sludge collection, recycling and disposal, VOCs oxidation, etc., which easily exceed US$ 100 million per plant per year.

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Authors and Affiliations

  1. Institute of Research for Technology Development, College of Engineering, University of Kentucky, 40506-0503, Lexington, KY, USA

    Abraham J. Salazar

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  1. Abraham J. Salazar
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Correspondence to Abraham J. Salazar .

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Editors and Affiliations

  1. Asahi Sunac Corporation, Asahimae-cho 5050, Owariasahi, 488-8688, Aichi, Japan

    Kimio Toda

  2. University of Kentucky, College of Engineering, Institute of Research for Technology Dev, --, Lexington, 40506-0503, Kentucky, USA

    Abraham Salazar

  3. University of Kentucky, College of Engineering, Institute of Research for Technology Dev, --, Lexington, 40506-0503, Kentucky, USA

    Kozo Saito

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Salazar, A.J. (2013). Computational Modeling of Relevant Automotive Rotary Spray Painting Process. In: Toda, K., Salazar, A., Saito, K. (eds) Automotive Painting Technology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5095-1_3

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  • DOI: https://doi.org/10.1007/978-94-007-5095-1_3

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