Question 1

A process that exhibits random variability would be judged to be out of control.

Accepted Answer

A) True 
 B)False

Question 2

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.

Accepted Answer

A)  I and II 
B)  I and III 
C)  II and III 
D)  II only 
E)  I, II, and III 
A)  I and II 
B)  I and III 
C)  II and III 
D)  II only 
E)  I, II, and III

Question 3

A control chart used to monitor the process mean is the:

Accepted Answer

A)  p-chart. 
B)  R-chart. 
C)  x-bar chart. 
D)  c-chart. 
E)  Gantt chart. 
A)  p-chart. 
B)  R-chart. 
C)  x-bar chart. 
D)  c-chart. 
E)  Gantt chart.

Question 4

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are under control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $$\begin{array} {r } 
{ \text { Measurements } } \
\begin{array} { l l l l l } 
\text { Machine } &   \
\hline   \# 1 & 17 & 15 & 15 & 17 \
\# 2 & 16 & 25 & 18 & 25 \
\# 3 & 23 & 24 & 23 & 22
\end{array}\end{array}$$ 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?

Accepted Answer

A)  machine #1 
B)  machine #2 
C)  machine #3 
D)  all of the machines 
E)  none of the machines 
A)  machine #1 
B)  machine #2 
C)  machine #3 
D)  all of the machines 
E)  none of the machines

Question 5

Given the following process control data for a quality attribute (three samples of size 400 each): $$\begin{array} { l r } 
\text { Sample } & \text { Defectives } \
\hline \# 1 & 36 \
\# 2 & 32 \
\# 3 & 52
\end{array}$$ If the process is known to produce 11 percent defectives on average, using three-sigma control limits, do any of the sample proportions indicate an out-of-control process proportion of defectives?

Accepted Answer

No, all ar

Question 6

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

Accepted Answer

A) True 
 B)False

Question 7

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are under control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $$\begin{array} {r } 
{ \text { Measurements } } \
\begin{array} { l l l l l } 
\text { Machine } &   \
\hline   \# 1 & 17 & 15 & 15 & 17 \
\# 2 & 16 & 25 & 18 & 25 \
\# 3 & 23 & 24 & 23 & 22
\end{array}\end{array}$$ What are the x-bar chart three-sigma upper and lower control limits?

Accepted Answer

A)  22 and 18 
B)  23.29 and 16.71 
C)  23.5 and 16.5 
D)  23.16 and 16.84 
E)  24 and 16 
A)  22 and 18 
B)  23.29 and 16.71 
C)  23.5 and 16.5 
D)  23.16 and 16.84 
E)  24 and 16

Question 8

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 the process is known to have a mean of 15 and a standard deviation of 3, using three-sigma control limits, do any of the sample means indicate an out-of-control process mean?

Accepted Answer

No, all ar

Question 9

A time-ordered plot of sample statistics is called a(n) ______ chart.

Accepted Answer

A)  statistical 
B)  inspection 
C)  control 
D)  simo 
E)  limit 
A)  statistical 
B)  inspection 
C)  control 
D)  simo 
E)  limit

Question 10

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are under control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $$\begin{array} {r } 
{ \text { Measurements } } \
\begin{array} { l l l l l } 
\text { Machine } &   \
\hline   \# 1 & 17 & 15 & 15 & 17 \
\# 2 & 16 & 25 & 18 & 25 \
\# 3 & 23 & 24 & 23 & 22
\end{array}\end{array}$$ What is the estimate of the sample average range based upon this limited sample?

Accepted Answer

A)  13.0 
B)  4.33 
C)  5.4 
D)  4.2 
E)  2.0 
A)  13.0 
B)  4.33 
C)  5.4 
D)  4.2 
E)  2.0

Question 11

Control limits used on process control charts are specifications established by design or customers.

Accepted Answer

A) True 
 B)False

Question 12

Which of the following relationships must always be incorrect?

Accepted Answer

A) Tolerances > process variability > control limits B) Process variability > tolerances > control limits C) Tolerances > control limits > process variability D) Process variability > control limits > tolerances E) Process variability < tolerances < control limits A) Tolerances > process variability > control limits B) Process variability > tolerances > control limits C) Tolerances > control limits > process variability D) Process variability > control limits > tolerances E) Process variability < tolerances < control limits

Question 13

Given the following process control data for a quality attribute (three samples of size 400 each): $$\begin{array} { l r } 
\text { Sample } & \text { Defectives } \
\hline \# 1 & 36 \
\# 2 & 32 \
\# 3 & 52
\end{array}$$ If the process proportion of defectives is unknown, what is the alpha risk (probability of Type I error) for upper and lower control limits of .115 and .085 respectively? .13 and .07? .145 and .055?

Accepted Answer

The answer of Given the following process control data for...

Question 14

Construct the appropriate two-sigma control chart for the sample observations listed below. $$\begin{array} { l l l l l l l l l l r r } 
\text { Observation } & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 \
\hline \text { Num. defects per unit } & 9 & 4 & 3 & 5 & 6 & 3 & 4 & 2 & 3 & 2 & 3
\end{array}$$

Accepted Answer

The answer of Construct the appropriate two-sigma control chart for...

Question 15

A quality analyst wants to construct a control chart for determining whether three machines, all producing the same product, are under control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: $$\begin{array} {r } 
{ \text { Measurements } } \
\begin{array} { l l l l l } 
\text { Machine } &   \
\hline   \# 1 & 17 & 15 & 15 & 17 \
\# 2 & 16 & 25 & 18 & 25 \
\# 3 & 23 & 24 & 23 & 22
\end{array}\end{array}$$ What is the estimate of the process mean for whenever it is under control?

Accepted Answer

A)  16 
B)  19 
C)  20 
D)  21 
E)  23 
A)  16 
B)  19 
C)  20 
D)  21 
E)  23

Question 16

Tolerances represent the control limits we use on the charts.

Accepted Answer

A) True 
 B)False

Question 17

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 the process is known to have a mean of 15 and a standard deviation of 3, what are the three-sigma upper and lower control limits for an x-bar chart?

Accepted Answer

@#LAT-DLM& Lower lim

Question 18

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: $$\begin{array} { r } 
 { \text { Service Life (hours) } }\
\begin{array} { l l l l l } 
\text { Sample } & \
\hline 1 & 495 & 500 & 505 & 500 \
2 & 525 & 515 & 505 & 515 \
3 & 470 & 480 & 460 & 470
\end{array}\end{array}$$ 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)?

Accepted Answer

A)  0.0026 
B)  0.0456 
C)  0.3174 
D)  0.6826 
E)  0.9544 
A)  0.0026 
B)  0.0456 
C)  0.3174 
D)  0.6826 
E)  0.9544

Question 19

The Taguchi loss function suggests that the capability ratio can be improved by extending the spread between LCL and UCL.

Accepted Answer

A) True 
 B)False

Question 20

The purpose of control charts is to:

Accepted Answer

A)  estimate the proportion of output that is acceptable. 
B)  weed out defective items. 
C)  determine if the output is within tolerances/specifications. 
D)  distinguish between random variation and assignable variation in the process. 
E)  provide meaningful work for quality inspectors. 
A)  estimate the proportion of output that is acceptable. 
B)  weed out defective items. 
C)  determine if the output is within tolerances/specifications. 
D)  distinguish between random variation and assignable variation in the process. 
E)  provide meaningful work for quality inspectors.

A process that exhibits random variability would be judged to be out of control.

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.

A control chart used to monitor the process mean is the:

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

A time-ordered plot of sample statistics is called a(n) ______ chart.

Control limits used on process control charts are specifications established by design or customers.

Which of the following relationships must always be incorrect?

Construct the appropriate two-sigma control chart for the sample observations listed below. Observation 1 2 3 4 5 6 7 8 9 10 11 Num. defects per unit 9 4 3 5 6 3 4 2 3 2 3

Tolerances represent the control limits we use on the charts.

The Taguchi loss function suggests that the capability ratio can be improved by extending the spread between LCL and UCL.

The purpose of control charts is to:

Introduction to Operations Management

Competitiveness, Strategy, and Productivity

Forecasting

Product and Service Design

Extension: Reliability

Strategic Capacity Planning for Products and Services

Extension: Decision Theory

Process Selection and Facility Layout

Work Design and Measurement

Extension: Learning Curves

Location Planning and Analysis

Extension: The Transportation Model

Management of Quality

Extension: Acceptance Sampling

Aggregate Planning and Master Scheduling

MRP and ERP

Inventory Management

Jit and Lean Operations

Extension: Maintenance

Supply Chain Management

Scheduling

Project Management

Management of Waiting Lines

Linear Programming

Filters

Exam 10: Quality Control

A process that exhibits random variability would be judged to be out of control.

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.

A control chart used to monitor the process mean is the:

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

A time-ordered plot of sample statistics is called a(n) ______ chart.

Control limits used on process control charts are specifications established by design or customers.

Which of the following relationships must always be incorrect?

Construct the appropriate two-sigma control chart for the sample observations listed below. Observation 1 2 3 4 5 6 7 8 9 10 11 Num. defects per unit 9 4 3 5 6 3 4 2 3 2 3

Tolerances represent the control limits we use on the charts.

The Taguchi loss function suggests that the capability ratio can be improved by extending the spread between LCL and UCL.

The purpose of control charts is to:

Introduction to Operations Management

Competitiveness, Strategy, and Productivity

Forecasting

Product and Service Design

Extension: Reliability

Strategic Capacity Planning for Products and Services

Extension: Decision Theory

Process Selection and Facility Layout

Work Design and Measurement

Extension: Learning Curves

Location Planning and Analysis

Extension: The Transportation Model

Management of Quality

Extension: Acceptance Sampling

Aggregate Planning and Master Scheduling

MRP and ERP

Inventory Management

Jit and Lean Operations

Extension: Maintenance

Supply Chain Management

Scheduling

Project Management

Management of Waiting Lines

Linear Programming

Filters