D.C.MONTGOMERY,J.B.KEATS,G.C.RUNGER,AND W.S.MESSINA lation runs. ance 1=04nd3 limits and。c ds 1-250)Each in for p (CUSUM)with =0.5 and h=5.Details concern- formance measure for period 251-500 for either the EPC rule or some combination of EPC and an SPC ght. was 100 t the perlorr nearly identical weigh re prior is t vious obser ationsas do the Westeru coluns imply that the /SPC che This EWMA does not have the same avera has a smalle r performance measure than the EPC hart cha he ule alone. e is some ind ication that the Sh data in nearly the same way. other SPC charts for the la cifically 7.5 Some experimenters compare statistical monitor and 10.0.We conclude that integrating an SPCrule with EPC iatio ing s ing parar of the rom t to select par he a range of shifts such as the CUSUM with =0. to Table 2 pres nts the ARL's observed in the sim uch a the e The smd ts re mos the ARL of va that theR instead to demonstrate that several widely used pr is that with the EPC rule the effect of an assignable cedures operating with nominal design parameters causes is converted from a step change in a correlated O B ter d change in I an nen esults for pensate for t largely con mance measure from equation（O）and the Table 3 esulta analo to standard error (in parentheses)based on 2000 simu- those in Table 1.ssuming that the s TABLE 1.Averages of the Performance Measures for EPC/SPC Rules Based on00Simulations rocess Mean at Observation 251.Standard Deviations Shift EPC EPC and Magnitude to Shift EWMA A=0.1 入=0.4 h=5,k=0.5 1 2.552 2.552 2.552 2.552 (0.0052) (0.0053) (0.0053) (0.0052) 2 2.538 2.679 2.594 2.594 2.594 2.593 (0.0051) (0.0064 (0.0052) (0.0052) (0.0052) (0.0052) 5 2.552 2.929 2.754 2.811 2.793 2.785 (0.0050) (0.0077 (0.0053) (0.0054) (0.0054) (0.0053) 7.5 2.544 3.298 2.062 3.033 2.929 2.943 (0.0045) (0.0098) (0.0056) 0.0059) (0.0058) (0.0057) 10 2.544 3.838 3.094 3.273 3.111 3.311 (0.0051) (0.0123) (0.0061) (0.0066) (0.0066) (0.0061) Joumal o Quality Technology Vol.26,No.2,April 1994