Exam 16: Quality Control and Spc

Table 1-Statistical Process Control (SPC) Problem Data for Service Waiting Times Sample Number \multicolumn 3 |c| Observation Number 1 2 3 1 9.6 10.2 9.8 2 9.4 10.0 10.4 3 9.9 9.6 9.0 4 9.3 10.5 9.9 5 9.7 9.2 9.7 -Using Table 1, for the R-chart, what is the value of LCL_R?

Special cause variation tends to be easily detectable using statistical methods.

Collecting continuous data is usually easier than collecting discrete data.

A high-paced discount store in Los Angeles notices that checking errors have increased recently. They plan to use control charts with three standard deviation control limits to monitor the process. They decide to take a sample of 100 transactions over 10 days. The number of transactions with errors for each day was 5, 7, 6, 5, 6, 4, 6, 3, 10, and 8. a.What is the center line for the p-chart? b.What is the upper control limit for the p-chart? c.What is the lower control limit for the p-chart?

Discuss the three basic quality control practices used in manufacturing.

In general, discuss how to interpret control charts.

In the 1:10:100 Rule, which of the following would be correct?

A plastic cell phone case has been experiencing physical quality control problems. That is, the clear screen does not always fit (and snap into place) on the case. The dimensions of the screen have consistently been in statistical process control (SPC). A root cause quality initiative collected the following data about the plastic cell phone case. Analyze the width of the cell phone case using control charts and make a recommendation. Table 1 Cell Phone Plastic Case Widths in Centimeters Data* Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Observation \#1 6.02 5.92 5.88 5.99 6.05 5.94 6.00 \#2 5.97 5.83 5.97 6.08 6.06 5.96 5.95 \#3 5.90 5.87 5.88 6.08 5.98 5.99 5.82 Average 5.963 5.873 5.91 6.05 6.03 5.963 5.923 Range 0.12 0.09 0.09 0.09 0.08 0.05 0.18 *The sample averages and ranges helps in avoiding simple math errors and quickens the time to complete the SPC analysis. -Using Table 1 for the R-chart, what is the value of UCL_R?

An operator has determined the percentage of defectives for a machine which she operates. Based on several samples of 75 observations, she found the p-bar to be 10 percent. She wants to set up a control chart using 3 standard deviation control limits. a.What is the upper control limit for a p-chart? b.What is the lower control limit for a p-chart?

(Students must compute the range per sample and overall r-bar) $\text { Table 1-SPC Problem Data }$ $\text { Observation Number }$ Sample number 1 2 3 4 5 1 10.1 10.6 9.8 9.9 10.9 2 9.7 9.5 10.3 9.9 10.5 3 10.1 10.7 9.2 10.0 10.1 4 9.9 9.8 10.5 10.4 10.1 5 10.4 10.1 10.9 9.9 10.3 -In Table 1, the sample values represent service times in minutes. For the R-chart, what is the value of UCL_R?