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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Response surface modeling and optimization of single axis automatic application of automotive polyurethane coatings on plastic components
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Response surface modeling and optimization of single axis automatic application of automotive polyurethane coatings on plastic components

机译:响应面建模和单轴自动优化汽车聚氨酯涂料在塑料部件上的应用

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摘要

The present paper discusses response surface methodology (RSM) as an efficient system for building a mathematical model and optimization of the process of polyurethane coating on acrylonitrile butadiene styrene using a single axis robotic applicator. In this work, RSM is used to optimize the process inputs such as part - applicator distance, paint flow rate, and paint viscosity to obtain the optimal values of process outputs; dry film thickness (DFT), rating value (R), and distinctness of image (DOI). The optimization was done to achieve high values of R and DOI with minimal DFT to reduce overall process cost. A 2~3 full factorial central composite design experimental design was employed. ANOVA showed satisfactory levels of coefficient of determination values (R~2) for all three responses. The optimized results were validated experimentally. Under optimal value of process parameters high rating value (7.76) and high distinctness of image (93.137) was achieved with low dry film thickness of 29.99 μm.
机译:本文讨论了响应表面方法学(RSM),它是一种有效的系统,用于建立数学模型并使用单轴机器人施加器优化聚氨酯在丙烯腈丁二烯苯乙烯上的涂覆工艺。在这项工作中,RSM用于优化过程输入,例如零件-涂胶机距离,涂料流速和涂料粘度,以获得过程输出的最佳值。干膜厚度(DFT),额定值(R)和图像清晰度(DOI)。进行了优化,以最小的DFT实现了较高的R和DOI值,从而降低了总体工艺成本。采用2〜3个全因子中心复合设计实验设计。方差分析显示所有三个响应的确定系数值(R〜2)令人满意。优化结果通过实验验证。在最佳工艺参数值下,以29.99μm的低干膜厚度实现了高额定值(7.76)和高图像清晰度(93.137)。

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