Multi-objective optimization with modified Taguchi approach to specify optimal robot spray painting process parameters

Robot spray painting process can improve the quality, productivity and provide clean environment in addition to minimize the labour and cost. This process is being used in automobiles, home appliances, etc. There is a need to specify optimal spray painting process parameters to improve the quality of paint coating considering the performance indicators as thickness variation, surface roughness and film adhesion. Compared to the Taguchi orthogonal array and gray rational analysis, a simple modified Taguchi approach is adopted here to identify optimal spray painting process parameters (such as distance, pressure and speed) and obtain minimum thickness variation, minimum surface roughness and maximum film adhesion. Empirical relation for thickness variation, surface roughness and film adhesion are presented. Test data are close-to/within the estimated range.

Keywords:

ANOVA , Automated paint , Distance , Film adhesion , Pressure , Speed , Surface roughness , Thickness variation