Advertisement

Analysis of Correlation Between Surface Roughness of Aluminum Alloy and Human Psychological Perception

  • Wengqing Fu
  • Xiaozhou Zhou
  • Chengqi XueEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1026)

Abstract

As modern products move toward embedded and flat design, the surface materials of products are becoming more and more important in the product experience. However, there has been a strong lack of studies to quantify and link surface materials of products to the human response. Here, we explore the correlation between perception to product surface properties of customers and controllable product surface properties. Analysis reveals five emotional dimensions related to perception of surface physical properties: “uncomfortable - comfortable”, “cheap - luxury”, “exotic - ordinary”, “plain-beauitful” and “artificial - natural”. Simultaneously, we deeply explored the relationship between these dimensions and surface roughness of the material. Through the “soft” judgment of psychological attributes and the “hard measurement” of the product surface properties, we have achieved a quantitative assessment of affective surface engineering. These help designers and engineers choose more active material embedded in the product.

Keywords

Affective surface engineering Kansei Quantitative 

Notes

Acknowledgments

This work was supported by Science and Technology on Avionics Integration Laboratory and Aeronautical Science Fund (No. 20185569008) and “the Fundamental Research Funds for the Central Universities”.

References

  1. 1.
    Sakamoto, M., Watanabe, J.: Exploring tactile perceptual dimensions using materials associated with sensory vocabulary. J. Front. Psychol. 8, 569 (2017)CrossRefGoogle Scholar
  2. 2.
    Choi, J.: Material selection by the evaluation of diffuse interface of material perception and product personality. J. Int. J. Interact. Des. Manuf. 11, 967–977 (2017)CrossRefGoogle Scholar
  3. 3.
    Tiest, W.M.B.: Tactual perception of material properties. J. Vis. Res. 50, 2775–2782 (2010)CrossRefGoogle Scholar
  4. 4.
    Chen, X., Barnes, C.J., Childs, T.H.C., et al.: Materials’ tactile testing and characterisation for consumer products’affective packaging design. J. Mater. Des. 30, 4299–4310 (2009)CrossRefGoogle Scholar
  5. 5.
    Okamoto, S., Nagano, H., Yamada, Y.: Psychophysical dimensions of tactile perception of textures. J. IEEE Trans. Hap. 6, 81–93 (2013)CrossRefGoogle Scholar
  6. 6.
    Rosen, B.G., Eriksson, L., Bergman, M.: Kansei, surfaces and perception engineering. J. Surf. Topog. Metrol. Prop. 4, 033001 (2016)CrossRefGoogle Scholar
  7. 7.
    Bergman, M., Rosen, B.G., Eriksson, L., et al.: Surface design methodology – challenge the steel. J. Phys.: Conf. Ser. 483, 012013 (2014)Google Scholar
  8. 8.
    Bergman, M., Rosen, B.G., Eriksson, L., et al.: Surface design methodology—the cleanability investigation. In: The 5th Kanesi Engineering and Emotion Research. Linköping University Electronic Press, vol. 100, pp. 705–722. Linköping University Electronic Press, Sweden (2014)Google Scholar
  9. 9.
    ASME 2009 Bioprocessing Equipment. American Society of Mechanical Engineers, New YorkGoogle Scholar
  10. 10.
    Schelleng, R.D., Gilman, P.S., Jatkar, A.D., et al.: Research on mechanically alloyed aluminum-alloy products for aerospace applications. J. Metals. 36, 24–25 (1984)Google Scholar
  11. 11.
    Zuo, H.: The selection of materials to match human sensory adaptation and aesthetic expectation in industrial design. J. Metu J. Fac. Archit. 27, 301–319 (2010)CrossRefGoogle Scholar
  12. 12.
    Guest, S., Dessirier, J.M., Mehrabyan, A., et al.: The development and validation of sensory and emotional scales of touch perception. J. Attent. Percept. Psychophys. 73, 531–550 (2011)CrossRefGoogle Scholar
  13. 13.
    Wang, W.M., Li, Z., Tian, Z.G., et al.: Extracting and summarizing affective features and responses from online product descriptions and reviews: a Kansei text mining approach. J. Eng. Appl. Artif. Intell. 73, 149–162 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Mechanical EngineeringSoutheast UniversityNanjingChina

Personalised recommendations