Question 1

A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that the process standard deviation is two ounces. Each day last week, he randomly selected four packages and weighed each. The data from that activity appears below.
  (a) Calculate all sample means and the mean of all sample means.
(b) Calculate upper and lower control limits that allow for natural variations.
(c) Is this process in control?

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Question 2

The mean and standard deviations for a process are μ= 90 and σ = 9. For the variable control chart, a sample size of 16 will be used. Calculate the standard deviation of the sampling distribution.

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Question 3

Pierre's Motorized Pirogues and Mudboats is setting up an acceptance sampling plan for the special air cleaners he manufactures for his boats. His specifications, and the resulting plan, are shown on the POM for Windows output below. In relatively plain English (someone else will translate for Pierre), explain exactly what he will do when performing the acceptance sampling procedure, and what actions he might take based on the results.

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Question 4

A woodworker is concerned about the quality of the finished appearance of her work. In sampling units of a split-willow hand-woven basket, she has found the following number of finish defects in ten units sampled: 4, 0, 3, 1, 2, 0, 1, 2, 0, 2.
a. Calculate the average number of defects per basket
b. If 3-sigma control limits are used, calculate the lower control limit, centerline, and upper control limit.

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Question 5

A hospital-billing auditor has been inspecting patient bills. While almost all bills contain some errors, the auditor is looking now for large errors (errors in excess of $250). Among the last 100 bills inspected, the defect rate has been 16%. Calculate the upper and lower limits for the billing process for 99.7% confidence.

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Question 6

Cartons of Plaster of Paris are supposed to weigh exactly 32 oz. Inspectors want to develop process control charts. They take ten samples of six boxes each and weigh them. Based on the following data, compute the lower and upper control limits and determine whether the process is in control.

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Question 7

The width of a bronze bar is intended to be one-eighth of an inch (0.125 inches). Inspection samples contain five bars each. The average range of these samples is 0.01 inches. What are the upper and lower control limits for the x-bar and R-chart for this process, using 3-sigma limits?

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Question 8

A local manufacturer supplies you with parts, and you would like to install a quality monitoring system at his factory for these parts. Historically, the defect rate for these parts has been 1.25 percent (You've observed this from your acceptance sampling procedures, which you would like to discontinue). Develop ± 3σ control limits for this process. Assume the sample size will be 200 items.

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Question 9

Pierre's Motorized Pirogues and Mudboats is setting up an acceptance sampling plan for the special air cleaners he manufactures for his boats. His specifications, and the resulting plan, are shown on the POM for Windows output below. Pierre is a bit confused. He mistakenly thinks that acceptance sampling will reject all bad lots and accept all good lots. Explain why this will not happen.

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Question 10

An operator trainee is attempting to monitor a filling process that has an overall average of 705 cc. The average range is 17 cc. If you use a sample size of 6, what are the upper and lower control limits for the x-bar and R chart?

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Question 11

A part that connects two levels should have a distance between the two holes of 4". It has been determined that x-bar and R-charts should be set up to determine if the process is in statistical control. The following ten samples of size four were collected. Calculate the control limits, plot the control charts, and determine if the process is in control.

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Question 12

Ten samples of size four were taken from a process, and their weights measured. The sample averages and sample ranges are in the following table. Construct and plot an x-bar and R-chart using this data. Is the process in control?

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Question 13

What do the terms producer's risk and consumer's risk mean?

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Question 14

McDaniel Shipyards wants to develop control charts to assess the quality of its steel plate. They take ten sheets of 1" steel plate and compute the number of cosmetic flaws on each roll. Each sheet is 20' by 100'. Based on the following data, develop limits for the control chart, plot the control chart, and determine whether the process is in control.

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Question 15

Pierre's Motorized Pirogues and Mudboats is setting up an acceptance sampling plan for the special air cleaners he manufactures for his boats. His specifications, and the resulting plan, are shown on the POM for Windows output below. Pierre wants acceptance sampling to remove ALL defects from his production of air cleaners. Explain carefully why this won't happen.

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Question 16

The defect rate for a product has historically been about 1.6%. What are the upper and lower control chart limits for a p-chart, if you wish to use a sample size of 100 and 3-sigma limits?

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Question 17

If μ = 9 ounces, σ = 0.5 ounces, and n = 9, calculate the 3-sigma control limits.

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Question 18

Repeated sampling of a certain process shows the average of all sample ranges to be 1.0 cm. The sample size has been constant at n = 5. What are the 3-sigma control limits for this R-chart?

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Question 19

A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that when the process is operating as intended, packaging weight is normally distributed with a mean of twenty ounces, and a process standard deviation of two ounces. Each day last week, he randomly selected four packages and weighed each. The data from that activity appears below.
  (a) If he sets an upper control limit of 21 and a lower control limit of 19 around the target value of twenty ounces, what is the probability of concluding that this process is out of control when it is actually in control?
(b) With the UCL and LCL of part a, what do you conclude about this process-is it in control?

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Question 20

A small, independent amusement park collects data on the number of cars with out-of-state license plates. The sample size is fixed at n=25 each day. Data from the previous 10 days indicate the following number of out-of-state license plates:
  (a) Calculate the overall proportion of "tourists" (cars with out-of-state plates) and the standard deviation of proportions.
(b) Using ± 3σ limits, calculate the LCL and UCL for these data.
(c) Is the process under control? Explain.

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Quiz 23 Managing Quality

The mean and standard deviations for a process are μ= 90 and σ = 9. For the variable control chart, a sample size of 16 will be used. Calculate the standard deviation of the sampling distribution.

Cartons of Plaster of Paris are supposed to weigh exactly 32 oz. Inspectors want to develop process control charts. They take ten samples of six boxes each and weigh them. Based on the following data, compute the lower and upper control limits and determine whether the process is in control.

The width of a bronze bar is intended to be one-eighth of an inch (0.125 inches). Inspection samples contain five bars each. The average range of these samples is 0.01 inches. What are the upper and lower control limits for the x-bar and R-chart for this process, using 3-sigma limits?

An operator trainee is attempting to monitor a filling process that has an overall average of 705 cc. The average range is 17 cc. If you use a sample size of 6, what are the upper and lower control limits for the x-bar and R chart?

Ten samples of size four were taken from a process, and their weights measured. The sample averages and sample ranges are in the following table. Construct and plot an x-bar and R-chart using this data. Is the process in control?

What do the terms producer's risk and consumer's risk mean?

The defect rate for a product has historically been about 1.6%. What are the upper and lower control chart limits for a p-chart, if you wish to use a sample size of 100 and 3-sigma limits?

If μ = 9 ounces, σ = 0.5 ounces, and n = 9, calculate the 3-sigma control limits.

Repeated sampling of a certain process shows the average of all sample ranges to be 1.0 cm. The sample size has been constant at n = 5. What are the 3-sigma control limits for this R-chart?