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Exam 10: Quality Control

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Question 61

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Attribute data are counted, variable data are measured.

A) True
B) False

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Question 62

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C_pk is useful even when the process is not centered.

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B) False

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Question 63

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Larger samples will require wider x-bar control limits because there is more data.

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

High-cost, low-volume items often require careful inspection since we make them so infrequently.

Given the following process control data for a normally distributed quality variable (three samples of size four each): $\begin{array} { r} { \text { Measurements } } \\\begin{array} { l l l l l } \text { Machine } &\\\hline \# 1 & 15 & 14 & 15 & 12 \\\# 2 & 18 & 16 & 20 & 16 \\\# 3 & 16 & 17 & 16 & 17\end{array}\end{array}$ If this process is known to have a mean of 15 and a standard deviation of 3, what is the mean of the sampling distribution of sample means for whenever this process is under control? The standard deviation?

An analyst has gathered data and counted the number of runs with respect to the median. There were 60 observations and 22 runs. What can the analyst conclude given this information?

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

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: $\begin{array} { r } { \text { Service Life (hours) } }\\\begin{array} { l l l l l } \text { Sample } & \\\hline 1 & 495 & 500 & 505 & 500 \\2 & 525 & 515 & 505 & 515 \\3 & 470 & 480 & 460 & 470\end{array}\end{array}$ What is the mean of the sampling distribution of sample means when service life is in control?

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

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

Process capability compares process variability to the tolerances.

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 under 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: $\begin{array} { r } { \text { Weight (ounces) } }\\\begin{array} { l l l l l } \text { Day } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}\end{array}$ 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?

Inspection is a(n) :

A point which is outside of the lower control limit on an R-chart:

A stent for use in coronary surgery requires a special coating. Specifications for this coating call for it to be at least 0.05 millimeters but no more than 0.15 millimeters. Suppose the criterion for evaluating this process is that the appropriate capability index must be at least 1.3. With a long-run process mean of 0.09 and a standard deviation of 0.015, is this process capable?

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

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 C_pk index of 1?

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.

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