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Exam 14: Quality Control

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Question 51

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Control limits are based on multiples of the process standard deviation.

A) True
B) False

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Question 52

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Cpk is useful even when the process is not centered.

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B) False

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Question 53

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Range charts and p-charts are both used for variable data.

The purpose of statistical process control is to ensure that historical output is random.

If a process is performing as it should, it is still possible to obtain observations which are outside of which limits? (I) tolerances (II) control limits (III) process variability

A c-chart is used to monitor the number of defects per unit for process output.

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 sample mean for machine #1?

An x-bar control chart can only be valid if the underlying population it measures is a normal distribution.

A c-chart is used for:

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 estimate of the standard deviation of the sampling distribution for an instructor's sample proportion of failures?

Statistical process control focuses on the acceptability of process output.

A process results in a few defects occurring in each unit of output. Long-run, these defects should be monitored with:

The purpose of control charts is to:

Statistical process control is the measurement of rejects in the final product.

Consider the following information: $\begin{array} { | l | c | c | c | c | c | c | } \hline \text { Observations } & 1 & 2 & 3 & 4 & 5 & 6 \\\hline \text { Num. of defects } & 10 & 18 & 13 & 15 & 9 & 12 \\\hline\end{array}$ The number of runs up and down for the preceding data is:

Cpk can be used only when the process is centered.

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, what is his risk (alpha) of concluding this process is out of control when it is actually in control (Type I error) ?

Concluding that a process is out of control when it is not is known as a Type I error.

A shift in the process mean for a measured characteristic would most likely be detected by a:

Run tests are useful in helping to identify nonrandom variations in a process.