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Exam 14: Quality Control

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Question 21

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Studies on a bottle-filling machine indicate that it fills bottles to a mean of 16 ounces with a standard deviation of 0.10 ounces. What is the process specification, assuming the Cpk index of 1?

A) lower spec = 0.1 ounces and upper spec = 1 ounce
B) lower spec = 14.3 ounces and upper spec = 17.7 ounces
C) lower spec = 12.0 ounces and upper spec = 21.4 ounces
D) lower spec = 15.7 ounces and upper spec = 16.3 ounces
E) There is insufficient information to determine the process specification.

F) C) and D)
G) B) and E)

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Question 22

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The sampling distribution can be assumed to be approximately normal even when the underlying process distribution is not normally distributed.

A) True
B) False

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Question 23

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The variation of a sampling distribution is less than the variation of the underlying process distribution.

Low-cost, high-volume items often require more intensive inspection than other types of items.

The chair of the operations management department at Quality University wants to construct a p-chart for determining whether the four faculty teaching the basic P/OM course are in control with regard to the number of students who fail the course. Accordingly, he sampled 100 final grades from last year for each instructor, with the following results: $\begin{array} { l c } \text { Instructor } & \text { Number of Failures } \\\hline \text { Prof. A } & 13 \\\text { Prof. B } & 0 \\\text { Prof. C } & 11 \\\text { Prof. D } & 16\end{array}$ What are the .95 (5 percent risk of Type I error) upper and lower control limits for the p-chart?

Control limits used on process control charts are specifications established by design or customers.

The basis for a statistical process control chart is a(the) :

The process capability index (Cpk) may mislead if: (I) the process is not stable. (II) the process output is not normally distributed. (III) the process is not centered.

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are in control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $\begin{array} { c c c c c } \text { Machine } &&{ \text { Measurements } } \\\hline \# 1 & 17 & 15 & 15 & 17 \\\# 2 & 16 & 25 & 18 & 25 \\\# 3 & 23 & 24 & 23 & 22\end{array}$ For upper and lower control limits of 23.29 and 16.71, which machine(s) , if any, appear(s) to have an out-of-control process mean?

A design engineer wants to construct a sample mean chart for controlling the service life of a halogen headlamp his company produces. He knows from numerous previous samples that when this service life is in control it is normally distributed with a mean of 500 hours and a standard deviation of 20 hours. On three recent production batches, he tested service life on random samples of four headlamps, with these results: $\begin{array} { c c c c c } \text { Sample } & & { \text { Service Life (hours) } } \\\hline 1 & 495 & 500 & 505 & 500 \\2 & 525 & 515 & 505 & 515 \\3 & 470 & 480 & 460 & 470\end{array}$ What is the mean of the sampling distribution of sample means when the service life is in control?

A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that whenever this process is in control, package weight is normally distributed with a mean of 20 ounces and a standard deviation of two ounces. Each day last week, he randomly selected four packages and weighed each: $\begin{array} { l l c c c } \text { Day } && { \text { Weight (ounces) } } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}$ What is the standard deviation of the sampling distribution of sample means for whenever this process is in control?

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are in control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $\begin{array} { c c c c c } \text { Machine } &&{ \text { Measurements } } \\\hline \# 1 & 17 & 15 & 15 & 17 \\\# 2 & 16 & 25 & 18 & 25 \\\# 3 & 23 & 24 & 23 & 22\end{array}$ What is the estimate of the mean of the sampling distribution for the sample mean?

A plot below the lower control limit on the range chart: (I) should be ignored since lower variation is desirable. (II) may be an indication that process variation has decreased. (III) should be investigated for assignable cause.

A process that exhibits random variability would be judged to be out of control.

Range control charts are used to monitor process central tendency.

The traditional view is that the optimum level of inspection minimizes the sum of inspection costs and the cost of passing defectives.

The chair of the operations management department at Quality University wants to construct a p-chart for determining whether the four faculty teaching the basic P/OM course are in control with regard to the number of students who fail the course. Accordingly, he sampled 100 final grades from last year for each instructor, with the following results: $\begin{array} { l r } \text { Instructor } & \text { Number of Failures } \\\hline \text { Prof. A } & 13 \\\text { Prof. B } & 0 \\\text { Prof. C } & 11 \\\text { Prof. D } & 16\end{array}$ What is the estimate of the mean proportion of failures for these instructors?

The following data occurs chronologically from left to right: $\begin{array} { | l | l | l | l | l | l | } \hline 15.2 & 19.7 & 16.0 & 11.1 & 14.8 & 14.5 \\\hline\end{array}$ The number of runs up and down is:

Process capability compares process variability to the tolerances.

The amount of inspection we choose can range from no inspection at all to inspecting each item numerous times.