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Exam 14: Quality Control

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Question 31

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The traditional view is that the optimum level of inspection is where the:

A) cost of inspection is minimum.
B) cost of passing defectives is minimum.
C) total cost of inspection and defectives is maximum.
D) total cost of inspection and defectives is minimum.
E) difference between inspection and defectives costs is minimum.

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Question 32

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A c-chart is used to monitor the total number of defectives in the output of a process.

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Question 33

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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 this service life 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 sample mean service life for sample 2?

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 this service life 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: $\begin{array} { c c c c c } \text { Sample } && { \text { Service Life (hours) } } \\\hline 1 & 495 & 500 & 505 & 500 \\2 & 525 & 515 & 505 & 515 \\3 & 470 & 480 & 460 & 470\end{array}$ If he uses upper and lower control limits of 520 and 480 hours, on what sample(s) (if any) does service life appear to be out of control?

An R value of zero (on a range chart) means that the process must be in control since all sample values are equal.

The amount of inspection needed is governed by the costs of inspection and the expected costs of passing defective items.

When a process is in control, it results in there being, on average, 16 defects per unit of output. c-chart limits of 8 and 24 would lead to a _______ percent chance of a Type I error.

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 above and below the sample median is:

The number of defective parts in a sample is an example of variable data because it will "vary" from one sample to another.

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: $\begin{array} { l l c c c } \text { Day } & & { \text { Weight (ounces) } } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}$ If he uses upper and lower control limits of 22 and 18 ounces, on what day(s) , if any, does this process appear to be out of control?

The greater the volume of the process being targeted for inspection, the more attractive __________ inspection is.

Attributes need to be measured, whereas variable data can be counted.

The more progressive a firm's approach to quality assurance, the less that company will need to rely on:

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 this service life 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: $\begin{array} { c c c c c } \text { Sample } &&{ \text { Service Life (hours) } } \\\hline 1 & 495 & 500 & 505 & 500 \\2 & 525 & 515 & 505 & 515 \\3 & 470 & 480 & 460 & 470\end{array}$ If he uses upper and lower control limits of 520 and 480 hours, what is his risk (alpha) of concluding that service life is out of control when it is actually under control (Type I error) ?

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: $\begin{array} { l l c c l } \text { Day } && { \text { Weight (ounces) } } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}$ What is the mean of the sampling distribution of sample means when this process is in control?

The purpose of quality control is making sure that processes are performing in an acceptable manner.

The range chart (R-chart) is most likely to detect a change in:

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 is the sample proportion of failures (p) for Prof. D?

The specifications for a product are 6 mm ± 0.1 mm. The process is known to operate at a mean of 6.05 with a standard deviation of 0.01 mm. What is the Cpk for this process?

Statistical process control charts are not really used to fix quality so much as they are used to: