A Computational Fluid Dynamics Methodology to Predict Automotive Painting Process Using Simcenter STAR-CCM+

Abstract

<div class="section abstract"><div class="htmlview paragraph">Simulation tools play a significant role in the automotive industry due to their cost-reducing capabilities in new model development. Computational Fluid Dynamics (CFD) is extensively utilized in various applications, such as vehicle aerodynamics and engine thermal management. However, its application in manufacturing engineering is not yet widespread. One crucial process in automotive manufacturing is the application of the base coat, which provides protection for the final paint layer. This process involves three key steps: bodywork immersion, electrophoretic deposition (E-coat), and bodywork removal from the bath. Each of these steps can be evaluated using appropriate CFD models. During the immersion step, the primary objective is to minimize the presence of trapped air. In the E-coat step, the focus is on controlling the paint layer thickness on the Body-in-white (BIW). Lastly, the drainage analysis aims to minimize the retention of bath fluid, thereby preventing contamination in subsequent baths. In this study, we propose a methodology utilizing Simcenter STAR-CCM+ as the CFD code and a generic car geometry to evaluate these three painting stages. Our methodology demonstrates the effectiveness of Simcenter STAR-CCM+ in predicting the behavior of the BIW throughout the painting process. By simulating the evolution of physical phenomena, our methodology provides valuable information regarding the presence of trapped air during the dipping stage, the thickness of the paint layer during E-coat, and the volume of retained liquid during drainage. This approach offers a promising means to reduce prototype investments by anticipating the behavior of the BIW during the virtual painting process. As a result, potential quality issues can be identified and rectified by making necessary component changes. Moreover, this methodology can be employed to optimize the painting process itself, including the adjustment of parameters related to the generated electric field and the movement of the BIW within the bath. These optimizations aim to enhance energy efficiency and accommodate changes in line speed, maintenance of anodes, and alterations in chemical characteristics of the bath. In conclusion, the use of CFD simulations, specifically employing the presented methodology with Simcenter STAR-CCM+, proves to be highly beneficial in evaluating and optimizing the three critical stages of the automotive painting process. This approach enables the identification and mitigation of quality problems, offers cost savings in prototype development, and facilitates process adjustments for improved efficiency and adaptability.</div></div>