Brightness, transparency, and color impact critically the aesthetics of polymeric surfaces. They can significantly change the perception of common damages such as scratch and mar. Particularly, subtle mar damage is more dependent on surface perceptual properties. In this study, we investigate the impact of these attributes on scratch and mar visibility resistance of commercialized polymeric model systems frequently used in automotive industry. Twenty subjects were involved in a psychophysical test based on pairwise comparison, and results were treated using multidimensional scaling (MDS) analysis. A tied ordinal weighted Euclidian MDS model was used to visualize the relational structures of mar perception space. Results show that scratch visibility resistance tends to decrease with dark, more transparent, and green surfaces. Mar perception was reasonably conceptualized by a two-dimensional MDS space. MDS results show that Brightness, transparency and color have a decreasing level of impact on mar perception. Mar visibility resistance decreased with dark, less transparent, and green stimuli. However, transparency effect is still dependent on the sample background. To the best of our knowledge, this is the first MDS study applied to the analysis of mar perception on polymeric surfaces, or any surface damage perception in general. The presented MDS-based model can be utilized to study the effect of other attributes on surface perception. This approach offers a new avenue for the assessment of scratch and mar perception and the development of polymeric materials with better visibility resistance.


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    Title :

    A Multidimensional Scaling Analysis of Surface Perceptual Parameters on Scratch and Mar Visibility Resistance in Polymers


    Additional title:

    Sae Int. J. Mater. Manf
    Sae International Journal of Materials and Manufacturing


    Contributors:


    Publication date :

    2017-04-11


    Size :

    13 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English


    Keywords :


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