Question 1

Patterns of data on a control chart suggest that the process may have nonrandom variation.

Accepted Answer

A) True 
 B)False

Question 2

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

Accepted Answer

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

Question 3

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

Accepted Answer

A)  3. 
B)  4. 
C)  5. 
D)  6. 
E)  none of these. 
A)  3. 
B)  4. 
C)  5. 
D)  6. 
E)  none of these.

Question 4

Acceptance sampling, when it is used, is used:
(I) before production.
(II) during production.
(III) after production.

Accepted Answer

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

Question 5

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

Accepted Answer

A)  5 hours 
B)  6.67 hours 
C)  10 hours 
D)  11.55 hours 
E)  20 hours 
A)  5 hours 
B)  6.67 hours 
C)  10 hours 
D)  11.55 hours 
E)  20 hours

Question 6

Statistical process control focuses on the acceptability of process output.

Accepted Answer

A) True 
 B)False

Question 7

An operator collected the following time series data from a process: $$\begin{array} { l l l l l l l l } 
4.0 & 4.4 & 4.3 & 4.5 & 4.6 & 4.2 & 4.1 & 4.5
\end{array}$$ (A) Determine the number of A/B runs.
(B) Determine the number of up/down runs.

Accepted Answer

There are six above-

Question 8

A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are under 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: $$\begin{array} { l c } 
\text { Machine } & \text { Total Defectives } \
\hline   \# 1 & 23 \
\# 2 & 15 \
\# 3 & 29 \
\# 4 & 13
\end{array}$$ What is the estimate of the standard deviation of the sampling distribution of sample proportions for whenever this process is under control?

Accepted Answer

A)  .016 
B)  .00016 
C)  .04 
D)  .0044 
E)  .00002 
A)  .016 
B)  .00016 
C)  .04 
D)  .0044 
E)  .00002

Question 9

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. If, when the coating process is in control, the long-run average is 0.09 millimeters, what metric would be used to assess this process's capability?

Accepted Answer

The answer of A stent for use in coronary surgery...

Question 10

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, what is his risk (alpha) of concluding this process is out of control when it is actually in 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 11

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

Accepted Answer

A) True 
 B)False

Question 12

A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are under 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: $$\begin{array} { l c } 
\text { Machine } & \text { Total Defectives } \
\hline   \# 1 & 23 \
\# 2 & 15 \
\# 3 & 29 \
\# 4 & 13
\end{array}$$ 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?

Accepted Answer

A)  machine #3 
B)  machine #4 
C)  machines #3 and #4 
D)  machines #2 and #3 
E)  none of the machines 
A)  machine #3 
B)  machine #4 
C)  machines #3 and #4 
D)  machines #2 and #3 
E)  none of the machines

Question 13

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 under 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 are the .95 (5 percent risk of Type I error) upper and lower control limits for the p-chart?

Accepted Answer

A)  .95 and .05 
B)  .13 and .07 
C)  .1588 and .0412 
D)  .16 and .04 
E)  .1774 and .0226 
A)  .95 and .05 
B)  .13 and .07 
C)  .1588 and .0412 
D)  .16 and .04 
E)  .1774 and .0226

Question 14

The optimum level of inspection minimizes the sum of inspection costs and the cost of passing defectives.

Accepted Answer

A) True 
 B)False

Question 15

The output of a process may not conform to specifications even though the process may be statistically "in control."

Accepted Answer

A) True 
 B)False

Question 16

The basis for a statistical process control chart is a(the):

Accepted Answer

A)  process capability. 
B)  sampling distribution. 
C)  control limit. 
D)  sample range. 
E)  sample mean. 
A)  process capability. 
B)  sampling distribution. 
C)  control limit. 
D)  sample range. 
E)  sample mean.

Question 17

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 sample mean for machine #1?

Accepted Answer

A)  15 
B)  16 
C)  17 
D)  21 
E)  23 
A)  15 
B)  16 
C)  17 
D)  21 
E)  23

Question 18

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?

Accepted Answer

A)  3.33 
B)  1.67 
C)  5.00 
D)  2.50 
E)  1.33 
A)  3.33 
B)  1.67 
C)  5.00 
D)  2.50 
E)  1.33

Question 19

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

Accepted Answer

A) True 
 B)False

Question 20

A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are under 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: $$\begin{array} { l c } 
\text { Machine } & \text { Total Defectives } \
\hline   \# 1 & 23 \
\# 2 & 15 \
\# 3 & 29 \
\# 4 & 13
\end{array}$$ What are the control chart upper and lower control limits for an alpha risk of .05?

Accepted Answer

A)  .0272 and .0128 
B)  .0287 and .0113 
C)  .029 and .013 
D)  .0303 and .0097 
E)  .0332 and .0068 
A)  .0272 and .0128 
B)  .0287 and .0113 
C)  .029 and .013 
D)  .0303 and .0097 
E)  .0332 and .0068

Patterns of data on a control chart suggest that the process may have nonrandom variation.

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

Consider the following information: Observations 1 2 3 4 5 6 Num. of defects 10 18 13 15 9 12 The number of runs up and down for the preceding data is:

Acceptance sampling, when it is used, is used: (I) before production. (II) during production. (III) after production.

Statistical process control focuses on the acceptability of process output.

An operator collected the following time series data from a process: 4.0 4.4 4.3 4.5 4.6 4.2 4.1 4.5 (A) Determine the number of A/B runs. (B) Determine the number of up/down runs.

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

The optimum level of inspection minimizes the sum of inspection costs and the cost of passing defectives.

The output of a process may not conform to specifications even though the process may be statistically "in control."

The basis for a statistical process control chart is a(the):

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 C_pk for this process?

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

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

Patterns of data on a control chart suggest that the process may have nonrandom variation.

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

Consider the following information: Observations 1 2 3 4 5 6 Num. of defects 10 18 13 15 9 12 The number of runs up and down for the preceding data is:

Acceptance sampling, when it is used, is used: (I) before production. (II) during production. (III) after production.

Statistical process control focuses on the acceptability of process output.

An operator collected the following time series data from a process: 4.0 4.4 4.3 4.5 4.6 4.2 4.1 4.5 (A) Determine the number of A/B runs. (B) Determine the number of up/down runs.

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

The optimum level of inspection minimizes the sum of inspection costs and the cost of passing defectives.

The output of a process may not conform to specifications even though the process may be statistically "in control."

The basis for a statistical process control chart is a(the):

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?

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

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

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 C_pk for this process?