The following data are based on a month of samples, each with n=6, taken from a...

 

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The following data are based on a month of samples, each with n=6, taken from a process that produces O-rings. The measurements are the last three digits. For example, X-297 is actually 1.4297 cm and R-16 is actually 0.0016 cm. Sample 123456Tag= 10 11 X = 259.591 R = 25.727 X 259 270 249 250 273 265 260 248 251 252 259 a) Set up the X and R charts. R 16 21 17 31 23 37 27 24 27 26 28 Sample 12 13 14 15 16 17 18 19 20 21 22 X 262 266 247 269 270 255 256 259 261 260 270 R 11 32 19 24 27 37 30 22 27 35 25 b) If out of control condition exists, assume that assignable causes can be found. Revise the control limits if necessary. c) If the specifications are (1.424, 1.428), find the percentage of nonconforming O-rings. d) If the process average suddenly shifts to 1.4284 cm, what would happen to the percentage nonconforming? The following data are based on a month of samples, each with n=6, taken from a process that produces O-rings. The measurements are the last three digits. For example, X-297 is actually 1.4297 cm and R-16 is actually 0.0016 cm. Sample 123456Tag= 10 11 X = 259.591 R = 25.727 X 259 270 249 250 273 265 260 248 251 252 259 a) Set up the X and R charts. R 16 21 17 31 23 37 27 24 27 26 28 Sample 12 13 14 15 16 17 18 19 20 21 22 X 262 266 247 269 270 255 256 259 261 260 270 R 11 32 19 24 27 37 30 22 27 35 25 b) If out of control condition exists, assume that assignable causes can be found. Revise the control limits if necessary. c) If the specifications are (1.424, 1.428), find the percentage of nonconforming O-rings. d) If the process average suddenly shifts to 1.4284 cm, what would happen to the percentage nonconforming?

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This question relates to statistical process control specifically to the use of Xbar and R range charts to monitor the stability of a manufacturing pr... View the full answer