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 is the alpha risk (probability of Type I error) for upper and lower control limits of 16.5 and 13.5 respectively? 18 and 12? 19.5 and 10.5?

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

The following data occurs chronologically from left to right: \[\begin{array} { l l l l l l } 15.2 & 19.7 & 16.0 & 11.1 & 14.8 & 14.5 \end{array}\] The number of runs with respect to the sample median is:

A) 2. B) 3. C) 4. D) 5. E) none of these. A) 2. B) 3. C) 4. D) 5. E) none of these.

Given the following process control data for a quality attribute (three samples of size 400 each): \[\begin{array} { l r } \text { Sample } & \text { Defectives } \\ \hline \# 1 & 36 \\ \# 2 & 32 \\ \# 3 & 52 \end{array}\] What is the sample proportion of defectives for sample #1? #2? #3?

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

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: \[\begin{array} { r } { \text { Weight (ounces) } }\\ \begin{array} { l l l l l } \text { Day } \\ \hline \text { Monday } & 23 & 22 & 23 & 24 \\ \text { Tuesday } & 23 & 21 & 19 & 21 \\ \text { Wednesday } & 20 & 19 & 20 & 21 \\ \text { Thursday } & 18 & 19 & 20 & 19 \\ \text { Friday } & 18 & 20 & 22 & 20 \end{array}\end{array}\] What is the mean of the sampling distribution of sample means when this process is under control?

A) 18 ounces B) 19 ounces C) 20 ounces D) 21 ounces E) 22 ounces A) 18 ounces B) 19 ounces C) 20 ounces D) 21 ounces E) 22 ounces

Exam 10: Quality Control

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 1-inch pipe has a specification of 1 inch plus or minus 0.10 inch. What is the process capability index (C_pk) if the long-run process mean is 1 inch?

(Multiple Choice)

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Question 61

Given the following process control data for a normally distributed quality variable (three samples of size four each): Measurements Machine \#1 15 14 15 12 \#2 18 16 20 16 \#3 16 17 16 17 If the process is known to have a mean of 15 and a standard deviation of 3, what is the alpha risk (probability of Type I error) for upper and lower control limits of 16.5 and 13.5 respectively? 18 and 12? 19.5 and 10.5?

(Short Answer)

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Question 62

The following data occurs chronologically from left to right: 15.2 19.7 16.0 11.1 14.8 14.5 The number of runs with respect to the sample median is:

(Multiple Choice)

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Question 63

_______ variation is a variation whose cause can be identified.

(Multiple Choice)

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Question 64

The sampling distribution can be assumed to be approximately normal even when the underlying process distribution is not normally distributed.

(True/False)

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Question 65

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 If the process is known to produce 11 percent defectives on average, what are the upper and lower control limits for an alpha risk of .10? .05? .01?

(Short Answer)

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Question 66

Control limits are based on multiples of the process standard deviation.

(True/False)

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Question 67

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 What is the sample proportion of defectives for sample #1? #2? #3?

(Short Answer)

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Question 68

Processes that are in control eliminate variations.

(True/False)

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Question 69

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: Service Life (hours) Sample 1 495 500 505 500 2 525 515 505 515 3 470 480 460 470 What is the sample mean service life for sample 2?

(Multiple Choice)

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Question 70

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

(True/False)

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Question 71

The following chart depicts 16 sample means that were taken at periodic intervals and plotted on a control chart. Does the output appear to be random?

(Essay)

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Question 72

Low-cost, high-volume items often require more intensive inspection than other types of items.

(True/False)

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Question 73

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: Instructor Number of Failures Prof. A 13 Prof. B 0 Prof. C 11 Prof. D 16 Using .95 control limits (5 percent risk of Type I error), which instructor(s), if any, should he conclude is (are) out of control?

(Multiple Choice)

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Question 74

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

(True/False)

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Question 75

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

(Multiple Choice)

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Question 76

The best way to assure quality is to use extensive inspection and control charts.

(True/False)

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Question 77

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: Weight (ounces) Day Monday 23 22 23 24 Tuesday 23 21 19 21 Wednesday 20 19 20 21 Thursday 18 19 20 19 Friday 18 20 22 20 What is the mean of the sampling distribution of sample means when this process is under control?

(Multiple Choice)

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Question 78

Run tests give managers an alternative to control charts; they are quicker and cost less.

(True/False)

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Question 79

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, C_pk?

(Multiple Choice)

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Question 80

The following data occurs chronologically from left to right: 15.2 19.7 16.0 11.1 14.8 14.5 The number of runs with respect to the sample median is:

_______ variation is a variation whose cause can be identified.

The sampling distribution can be assumed to be approximately normal even when the underlying process distribution is not normally distributed.

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 If the process is known to produce 11 percent defectives on average, what are the upper and lower control limits for an alpha risk of .10? .05? .01?

Control limits are based on multiples of the process standard deviation.

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 What is the sample proportion of defectives for sample #1? #2? #3?

Processes that are in control eliminate variations.

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

The following chart depicts 16 sample means that were taken at periodic intervals and plotted on a control chart. Does the output appear to be random?

Low-cost, high-volume items often require more intensive inspection than other types of items.

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

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

The best way to assure quality is to use extensive inspection and control charts.

Run tests give managers an alternative to control charts; they are quicker and cost less.

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, C_pk?

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

The following data occurs chronologically from left to right: 15.2 19.7 16.0 11.1 14.8 14.5 The number of runs with respect to the sample median is:

_______ variation is a variation whose cause can be identified.

The sampling distribution can be assumed to be approximately normal even when the underlying process distribution is not normally distributed.

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 If the process is known to produce 11 percent defectives on average, what are the upper and lower control limits for an alpha risk of .10? .05? .01?

Control limits are based on multiples of the process standard deviation.

Given the following process control data for a quality attribute (three samples of size 400 each): Sample Defectives \#1 36 \#2 32 \#3 52 What is the sample proportion of defectives for sample #1? #2? #3?

Processes that are in control eliminate variations.

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

The following chart depicts 16 sample means that were taken at periodic intervals and plotted on a control chart. Does the output appear to be random?

Low-cost, high-volume items often require more intensive inspection than other types of items.

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

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

The best way to assure quality is to use extensive inspection and control charts.

Run tests give managers an alternative to control charts; they are quicker and cost less.

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?

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 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, C_pk?