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OM Chapter 10 MCQ - Exam 3

Terms in this set (114)

Approving the effort that occurs during the production process is known as acceptance sampling.
FALSE.



Acceptance sampling occurs before or after the production process.
Statistical Process Control is the measurement of rejects in the final product.
FALSE.




SPC is the evaluation of the process.
The optimum level of inspection occurs when we catch at least 98.6 percent of the defects.
FALSE




The optimum level of inspection is when the sum of inspection costs and the cost of passing defectives are equal.
The optimum level of inspection minimizes the sum of inspection costs and the cost of passing defectives.
TRUE




This represents the optimum balance between inspection and failure costs.
Processes that are in control eliminate variations.
FALSE





In control, processes are free of non-random variation.
High-cost, low-volume items often require careful inspection since we make them so infrequently.
TRUE




These are good candidates for inspection.
Low-cost, high-volume items often require more intensive inspection.
FALSE




These are not good candidates for inspection.
A lower control limit must by definition be a value less than an upper control limit.
TRUE




The lower limit must be smaller than the upper limit.
Attributes need to be measured, variable data can be counted.
FALSE




Attributes need to be counted, variable data is measured.
The amount of inspection we choose can range from no inspection at all to inspecting each item numerous times.
TRUE



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



These interact to set the optimum amount of inspection.
The purpose of statistical process control is to ensure that historical output is random.
FALSE



It is to ensure that non-random variation is detected and corrected.
A process that exhibits random variability would be judged to be out of control.
FALSE



All processes exhibit random variability.
If a point on a control chart falls outside one of the control limits, this suggests that the process output is non-random and should be investigated.
TRUE




A point outside the control limits suggests non-random variation.
n x-bar control chart can only be valid if the underlying population it measures is a normal distribution.
FALSE




The sample average typically is normally distributed regardless of the underlying distribution of the process.
Concluding a process is out of control when it is not is known as a Type I error.
TRUE



A Type I error involves erroneously concluding that a process is 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.
FALSE




If the sample size is sufficiently large, an R of zero could indicate an out of control process.
Range charts are used mainly with attribute data.
FALSE




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




P-charts are used with attribute data.
A p-chart is used to monitor the fraction of defectives in the output of a process.
TRUE



P-charts involve the fraction of defectives.
A c-chart is used to monitor the total number of defectives in the output of a process.
FALSE



A c-chart is used to monitor the number of defects per unit, not defective units.
A c-chart is used to monitor the number of defects per unit for process output.
TRUE



A c-chart monitors the number of defects per unit for process output.
Tolerances represent the control limits we use on the charts.
FALSE



Tolerances are specification limits, not control limits.
"Process capability" compares "process variability" to the "tolerances."
TRUE



Process variability influences how much output falls outside of tolerances.
Control limits used on process control charts are specifications established by design or customers.
FALSE



Control limits are independent of specifications.
Control limits tend to be wider for more variable processes.
TRUE



Process with inherently more variability will naturally have wider control limits.
Patterns of data on a control chart suggest that the process may have non-random variation.
TRUE



Ideally, the data on a control chart will have no pattern.
The output of a process may not conform to specifications even though the process may be statistically "in control."
TRUE



A process can be free of non-random variation and still not meet specifications.
Run tests are useful in helping to identify nonrandom variations in a process.
TRUE



Runs tests are useful to identify non-randomness in patterns.
Run tests give managers an alternative to control charts; they are quicker and cost less.
FALSE



Runs tests are not alternatives to control charts.
Statistical process control focuses on the acceptability of process output.
FALSE




Statistical process control focuses on the variability of processes.
A run test checks a sequence of observations for randomness.
TRUE




Runs tests can be used to detect nonrandomness in sequences of observations.
Even if the process is not centered, the process capability index (indicated by Cpk) is very useful.
FALSE



If the process is not centered, Cpk is not useful.
The process capability index (indicated by Cpk) can be used only when the process is centered.
FALSE



Cpk can be used whether or not the process is centered.
Quality control is assuring that processes are performing in an acceptable manner.
TRUE




Control is used to monitor the performance of processes.
The primary purpose of statistical process control is to detect a defective product before it is shipped to a customer.
FALSE




The primary purpose of SPC is to detect nonrandomness.
The Taguchi Cost Function suggests that the capability ratio can be improved by extending the spread between LCL and UCL.
FALSE




The Taguchi cost function suggests that reducing variation is key.
The variation of a sampling distribution is tighter than the variation of the underlying process distribution.
TRUE




The sampling distribution exhibits less variation than the underlying process.
The sampling distribution can be assumed to be approximately normal even when the underlying process distribution is not normally distributed.
TRUE




This is especially true as the sample size grows.
Approximately 99.7% of sample means will fall within two standard deviations of the process mean if the process is under control.
FALSE




Approximately 99.7% of sample means will fall within three standard deviations of the process mean.
The best way to assure quality is to use extensive inspection and control charts.
FALSE




The best way to assure quality is to make sure processes are highly capable.
Control limits are based on multiples of the process standard deviation.
FALSE




Control limits are based on multiples of the standard deviation of the sample statistic.
Attribute data are counted, variable data are measured.
TRUE



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




The number of defective parts in a sample is an example of attribute data.
Larger samples will require wider x-bar control limits because there is more data.
FALSE




Large samples will lead to narrower control limits.
When a process is not centered, its capability is measured in a slightly different way. The symbol for this case is Cpk.
TRUE




Cpk is used when the process is not centered.
Range control charts are used to monitor process central tendency.
FALSE




Range charts monitor variability.
An "up and down" run test uses the median as a reference point and measures the percentage above and below the median.
FALSE




An up-and-down runs test looks only at runs of increasing or decreasing values.
"Assignable variation" is variation due to a specific cause, such as tool wear.
TRUE




Assignable variation is specific cause variation.
Variation in a sample statistic collected from a process may be either random variation or assignable variation - or both.
TRUE




Total variation can consist of both random and assignable variation.
"Quality of conformance" is concerned with whether a product or service conforms to its specifications.
TRUE




Specification conformance is quality of conformance.
The larger the process variation, the tighter the specifications should be.
FALSE



Greater variation would lead to wider specifications.
Type I and Type II errors refer to the magnitude of variation from the standard.
FALSE




These refer to decisions regarding whether the process is in or out of control.
The greater the capability ratio, the higher the rejects.
FALSE




Greater capability reduces rejects.
Non-random variation is likely whenever all observations are between the LCL and UCL.
FALSE




If all observations are between the LCL and UCL, then the process would be considered in control
Which of the following quality control sample statistics indicates a quality characteristic that is an attribute?
E.



proportion
Proportions would be control with attribute control charts.
A time-ordered plot of representative sample statistics is called a:
C.




Control Chart

Control charts are time-ordered plots of sample statistics.
A control chart used to monitor the process mean is the:
C.




x-bar chart

The x-bar chart monitors the process mean.
A control chart used to monitor the fraction of defectives generated by a process is the:
A.




p-chart

The p-chart monitors the fraction defective.
A p-chart would be used to monitor _______.
C.



the fraction defective

The p-chart monitors the fraction defective.
A c-chart is used for:
E.




number of defects per unit
C-charts monitor the number of defects per unit.
A control chart used to monitor the number of defects per unit is the:
D.




c-chart

C-charts monitor the number of defects per unit.
A point which is outside of the lower control limit on an R-chart:
C.



should be investigated because an assignable cause of variation might be present

Points outside of the control limits should be investigated as signals of non-random variation being present.
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
C.



I and II

Even capable, in control processes can have observations outside of control limits or tolerances.
Which of the following relationships must always be incorrect?
C.




Tolerances > control limits > process variability

Process variability will always be greater than control limits.
Which of the following is not a step in the quality control process?
C.




eliminate each of the defects as they are identified

Eliminating defects is not part of quality control.
The probability of concluding that assignable variation exists when only random variation is present is:
(I) the probability of a Type I error
(II) known as the alpha risk
(III) highly unlikely
(IV) the sum of probabilities in the two tails of the normal distribution
D.



I, II, and IV

Incorrect signals can be on either side of the distribution.
_______ variation is a variation whose cause can be identified.
A.




Assignable

Assignable variation has a special cause.
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
C.




II and III

Plots outside of control limits should be investigated.
A shift in the process mean for a measured characteristic would most likely be detected by a:
B.




x-bar chart

X-bar charts monitor the process mean.
The range chart (R-chart) is most likely to detect a change in:
D.




variability

The range chart monitors variability.
The optimum level of inspection is where the:
D.




total cost of inspection and defectives is minimum

At the optimum level these costs are, in total, minimized.
The purpose of control charts is to:
D.




distinguish between random variation and assignable variation in the process

Control charts are used to signal assignable variation.
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.
E.




I, II and III

When using Cpk these concerns should be addressed.
A time-ordered plot of sample statistics is called a(n) ______ chart.
C.




Control

A control chart is a time-ordered plot of sample statistics.
The number of runs up and down for the data above is:
C.




5

Count the number of up and down runs.
The number of runs with respect to the sample median is:
A.




3

Count the number of runs above or below the median.
The following data occurs chronologically from left to right:

The number of runs with respect to the sample median is:
A.




2

The sample median is 15.2.
The number of runs up and down is:
C.




4

Count the number of up and down runs.
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:
...
What is the sample mean service life for sample 2?
D.




515 hours
Average the four observations.
What is the mean of the sampling distribution of sample means when service life is in control?
D.




500 hours

Average the sample means.
What is the standard deviation of the sampling distribution of sample means for whenever service life is in control?
C.




10 hours

Use the central limit theorem.
If he uses upper and lower control limits of 520 and 480 hours, what is his risk (alpha) of concluding service life is out of control when it is actually under control (Type I error)?
B.




0.0456

These are two-sigma limits.
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?
C.




sample 3

Sample 3's sample mean is below the lower control limit.
What is the sample mean package weight for Thursday?
A.



19 ounces

Average the four values.
What is the mean of the sampling distribution of sample means when this process is under control?
C.



20 ounces

When the process is in control, this is its mean value.
What is the standard deviation of the sampling distribution of sample means for whenever this process is under control?
D.



1 ounce

Use the central limit theorem.
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)?
B.



0.0456

These are two-sigma limits.
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?
A.




Monday

This day's sample average is outside of the control limits.
What is the sample mean for machine #1?
B.





16

Average the four values.
What is the estimate of the process mean for whenever it is under control?
C.




20

Average the sample averages.
What is the estimate of the sample average range based upon this limited sample?
B.




4.33

Average the sample ranges.
What are the x-bar chart three sigma upper and lower control limits?
D.




23.16 and 16.84

Use control chart factors of a sample size of four.
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.




machine #1

This machine's sample average fell outside the control limits.
What is the sample proportion of failures (p) for Prof. D?
E.




.16
Divide the number of failures by the sample size.
What is the estimate of the mean proportion of failures for these instructors?
A.



.10

Average the sample proportions.
What is the estimate of the standard deviation of the sampling distribution for an instructor's sample proportion of failures?
B.



.03

Use the formula for the standard deviation of the sample proportion.
What are the .95 (5% risk of Type I error) upper and lower control limits for the p-chart?
C.




.1588 and .0412

These are two-sigma limits.
Using .95 control limits, (5% risk of Type I error), which instructor(s), if any, should he conclude is (are) out of control?
B. Prof. B
C. Prof. D
D. both Prof. B and Prof. D

These fall outside the control limits.
What is the sample proportion of defectives for machine #1?
A.




.023

Divide the number of defectives by the sample size.
What is the estimate of the process proportion of defectives for whenever it is under control?
D.




.02

Average the sample proportions.
What is the estimate of the standard deviation of the sampling distribution of sample proportions for whenever this process is under control?
D.




.0044

Use the formula for the standard deviation of the sample proportions.
What are the control chart upper and lower control limits for an alpha risk of .05?
B.



.0287 and .0113

These are two-sigma limits.
For upper and lower control limits of .026 and .014, which machine(s), if any, appear(s) to be out-of-control for process proportion of defectives?
C.



machines #3 and #4

The sample proportions of these samples fall outside the control limits.
Studies on a bottle-filling machine indicates 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?
D.



16.0 ounces plus or minus 0.30 ounces

Use the Cpk formula to solve for the specification interval.
Studies on a machine that molds plastic water pipe indicate that when it is injecting 1-inch diameter pipe, the process standard deviation is 0.05 inches. The one-inch pipe has a specification of 1-inch plus or minus 0.10 inch. What is the process capability index (Cpk) if the long-run process mean is 1 inch?
B.



0.67

Use the Cpk formula to assess this process' capability.
The specification limit for a product is 8 cm and 10 cm. A process that produces the product has a mean of 9.5 cm and a standard deviation of 0.2 cm. What is the process capability, Cpk?
C.



0.83

Cpk is used here since the process mean isn't centered in the specification interval.
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?
B.



1.67

Cpk is used here since the process mean isn't centered in the specification interval.
Organizations should work to improve process capability so that quality control efforts can become more ________.
D.



unnecessary

Increasing process capability reduces the necessity for quality control.
A process results in a few defects occurring in each unit of output. Long-run, these defects should be monitored with ___________.
B.



c-charts

C-charts are used to monitor the number of defects per unit.
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 _______ chance of a Type I error.
E.



5%
These would be two-sigma limits
When a process is in control, it results in there being, on average, 16 defects per unit of output. C-chart limits of 4 and 28 would lead to a _______ chance of a Type I error.
D.



0.3%

These would be three-sigma limits.
The basis for a statistical process control chart is a(the) __________.
B.



sampling distribution

Control charts reflect the sampling distribution of an in control process.
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