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Exam 14: Quality Control

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Question 61

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When a process is in control, it results in there being, on average, 16 defects per unit of output. chart limits of 4 and 28 would lead to a _______ percent chance of a Type I error.

A) 68.26
B) 95.44
C) 31.74
D) 0.26
E) 4.56

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Question 62

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_______ variation is a variation whose cause can be identified.

A) Assignable
B) Controllable
C) Random
D) Statistical
E) Theoretical

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Question 63

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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: $\begin{array} { l l l c l } \text { Day } &&{ \text { Weight (ounces) } } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}$ What is the sample mean package weight for Thursday?

Processes that are in control eliminate variations.

A time-ordered plot of representative sample statistics is called a(n) :

A p-chart is used to monitor the fraction of defectives in the output of a process.

A control chart used to monitor the number of defects per unit is the:

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 above and below the sample median is:

Organizations should work to improve process capability so that inspection efforts can become more:

Which of the following is not a step in the control process?

A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are in control with regard to a particular quality attribute. Accordingly, she inspected 1,000 units of output from each machine in random samples, with the following results: $\begin{array} { c c } \text { Machine } & \text { Total Defectives } \\\hline \# 1 & 23 \\\# 2 & 15 \\\# 3 & 29 \\\# 4 & 13\end{array}$ What is the estimate of the process proportion of defectives?

A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are in control with regard to a particular quality attribute. Accordingly, she inspected 1,000 units of output from each machine in random samples, with the following results: $\begin{array} { c c } \text { Machine } & \text { Total Defectives } \\\hline \# 1 & 23 \\\# 2 & 15 \\\# 3 & 29 \\\# 4 & 13\end{array}$ What are the control chart upper and lower control limits for an alpha risk of .05?