Influence of Background Color on Visual Inspector Performance in 3-Dimension Simulation Model

Abstract:

This research is aimed to study the influence of the background color which affects efficiency in visual inspection. The visual search simulation program was set to test the search for the letters X and Y assigned to represent defects and mixed up with other background letters in 4 different colors: white, yellow, red and blue. The test were conducted with 48 samples who passed the selection standard by having normal eyesight, more than 50% accuracy in defect search while the average search time was less than 50%. The samples were separated into 4 groups for defect search with 4 colors background. The result was shown that the different background colors affect the average search time for defect search in each screen and the accuracy of the search for different defects. The white background provided the inspector the highest defect search efficiency with the level of statistical significance at .05.

• Periodical: Applied Mechanics and Materials (Volumes 110-116)
• Pages: 2805-2810
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.110-116.2805
• Online since: October 2011
• Authors: Anucha Watanapa, S. Kaewkuekool, S. Suksakulchai
• Keywords: Background Color, Defect, Efficiency, Visual Inspection, Visual Search

References

[1] Morral, J., The Analysis of an Inspection Task in the Steel Industry, In Drury, C.G., and Fox, J.G., (Eds)., Human Reliability in Quailty Control, Taylor and Francis, London, (1975).

[2] Boomfield, J.R., Theoretical Approaches to Visual Search, Human Reliability in Quality Control, Taylor and Francis, London, (1975).

[3] Hata, S Vision systems for Manufacturing in Japan' IECON, 90, 16th Annual Conference of IEEE Industrials Electronic Society, 1990, pp.792-797.

DOI: 10.1109/iecon.1990.149241

[4] Baker, C.A., Morris, D.F., and Steedman W.C., Target Recognition on Complex Displays, Human Factors, Vol. 2, 1960, PP. 51-61.

[5] Vora, J., Nair, S., Gramopadhye, A.K., Duchoski, A.T., Using virtual reality technology for aircraft visual inspection training: presence and comparison studies, Applied Ergonomics, vol 33, 2002, p.559–570‏.

DOI: 10.1016/s0003-6870(02)00039-x

[6] Drury, C.G., and Gramopadhye, A.K., Training for Visual Inspection, The Proceedings of Third Federal Aviation Administration Meeting on Human Factors in Aircraft Maintenance and Inspection : Training Issues, Atlantic City, New Jersey, (1990).

[7] Xiaochun Jiang, Mohammad T. Khasawneh, Reena Master, Shannon R. Bowling, Anand K. Gramopadhye, Brian.J. Melloy, Larry Grimes, Measurement of human trust in a hybrid inspection system based on signal detection theory, International Journal of Industrial Ergonomics., vol 34, 2004, pp.407-419.

DOI: 10.1016/j.ergon.2004.05.003

[8] Drury C.G., and Prabhu, P.V., , Feedforward and Feedback in Aircraft in Inspection, Technical Report Submitted to FAA, (Office of Aviation Medicine , Department of Transportation, Washinton D.C. ), (1992).

[9] Gramopadhye, A.K., Drury, C.G., and Prabhu, P.V., Training Strategies for Visual Inspection, Human Factors and Ergonomics in Manufacturing, Vol. 7, No. 3, 1997, pp.171-196.

DOI: 10.1002/(sici)1520-6564(199722)7:3<171::aid-hfm2>3.0.co;2-0

[10] Watanapa, A., Kaewkuekool, S., Improve Inspector Performance by Computer Based Feedback Training, International Multiconferences of Engineers and Computer Scientists2007, Hong Kong. March, 21-23, (2007).

[11] Watanapa, A‏., Kaewkuekool, S., A Comparison of Visual Inspection Training Strategies to Improve Thai Inspector , HAAMAHA 2007 Managing Enterprise of the Future , Poznan, Poland july 9-12, (2007).

[12] Tinker Miles A, Legibility of print, Lowa state University Press, Lowa, 1969, pp.64-66.