Diagnostic Characteristics for Bivariate Pattern Recognition Scheme in SPC

Statistical quality control charts cannot indicate explicitly whether there is any special disturbance in the manufacturing process. pattern recognition scheme can solve this problem. The simultaneous control of two or more variables is necessary when the quality of the product depends on the joint effect of these variables. Studies the combination patterns of random and random, shift and cycle, trend and cycle, and trend and shift for two variables. Proposes a T 2 control chart and uses simulation to determine pattern diagnostic characteristics for these combinations. The pattern diagnostic characteristics studied are window size, zone boundary, and zone representation. The results indicate that window size 20 is appropriate for these particular parameters, equal probability and the highest percentage alternative are adopted as the zone boundary and the zone representation, respectively. The sensitivity analysis of the pattern parameters indicates the pattern diagnostic is robust for changes in the parameter values.