The p chart and c chart an? commonly used when quality measurements are not prac

Question

The p chart and c chart an? commonly used when quality measurements are not practical. How do these charts differ? Which chart uses the assumption of a Poisson process to obtain its control limits? Which chart is appropriate for observing the proportion of nonconforming items? Indicate whether a p or c chart would be appropriate for controlling the following: a. The number of defective fuses in a sample of 25. b. The number of defective sectors on a disk drive. c. The number of times that a computer software program malfunctions in a month. d. The number of overripe tomatoes in a carton of 50 tomatoes. e. The number of knots on a sheet of paneling.

Explanation / Answer

1) difference between c-chart and p-chart :

In statistical quality control, the c-chart is a type of control chart used to monitor "count"-type data, typically total number of nonconformities per unit.

It is also occasionally used to monitor the total number of events occurring in a given unit of time.

The c-chart differs from the p-chart in that it accounts for the possibility of more than one nonconformity per inspection unit, and that (unlike the p-chart and u-chart) it requires a fixed sample size. The p-chart models "pass"/"fail"-type inspection only, ng down assignable causes.

Here, the number of nonconformities per unit area has the Poisson distribution.

i.e. the c-chart uses the assumptions of the Poisson distribution.

2) p- chart uses the Binomial assumptions to set up the control limits for proprtion of nonconformoties.

3)

a) The number of defective fuses in the sample of 25: P-chart

b) The number of defective sectors on a disk drive: C-chart (because, here, the the situation is about the defect per unit area.)

c) The number of times the computer software programs malfunctions in a month: P-chart

d) The number of overripe tomatoes in the carton of 50 tomatoes: P-chart

e) The number of knots on the sheet of paneling: C-chart (because, here, the the situation is about the defect per unit area.)

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