2 resultados para Automotive Industry.

em Universidad de Alicante


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This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

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Materials with new visual appearances have emerged over the last few years. In the automotive industry in particular there is a growing interest in materials with new effect finishes, such as metallic, pearlescent, sparkle, and graininess effects. Typically, for solid colours the mean of three measurements with repetitions is sufficient to obtain a representative measurement for colour characterisation. However, gonio-apparent panels have non-homogeneous colours, and there are no studies that recommend the minimum number of repetitions for colour, sparkle, and graininess characterisation of this type of panel. We assume that colour panels incorporating special-effect pigments in their colour recipes will require a higher minimum number of measurements than solid colour panels. Therefore, the purpose of this study is to verify this assumption by using a multiangle BYK-mac spectrophotometer, given that it is currently the only commercial device that can measure colour, sparkle, and graininess values simultaneously. In addition, a possible methodology is given for establishing the minimum number of measurements when characterising gonio-apparent materials using a specific instrument, able to be implemented in future instruments when determining multiple appearance attributes (colour, gloss, sparkle, etc.) for many coloration technologies. Thus, we studied the minimum number of measurements needed to characterise the colour, sparkle, and graininess of three types of sample with solid, metallic, and pearlescent coatings respectively. Twenty measurements were made at twenty random positions (different target areas) of 90 samples. The minimum number of measurements for all these variables was determined on the basis of the point at which the cumulative mean value became constant. Thus, applying new statistical tools, it is clearly shown that metallic and pearlescent panels require more colour measurements than solid panels, in particular when geometries are being measured in a specular direction. As regards texture (sparkle and graininess), more measurements are needed for graininess than for sparkle, and more for metallic panels than for pearlescent panels.