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Transcript of CD-ROM Chap 17-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In...
CD-ROM Chap 17-1A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
A Course In Business Statistics
4th Edition
CD-ROM Chapter 17Introduction to Quality and Statistical Process Control
CD-ROM Chap 17-2A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Chapter Goals
After completing this chapter, you should be able to:
Use the seven basic tools of quality
Construct and interpret x-bar and R-charts
Construct and interpret p-charts
Construct and interpret c-charts
CD-ROM Chap 17-3A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Chapter Overview
Quality Management and Tools for Improvement
Deming’s 14 Points
Juran’s 10 Steps to Quality
Improvement
The Basic 7 Tools
Philosophy of Quality
Tools for Quality Improvement
Control Charts
X-bar/R-charts
p-charts
c-charts
CD-ROM Chap 17-4A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Themes of Quality Management
Primary focus is on process improvement Most variations in process are due to systems Teamwork is integral to quality management Customer satisfaction is a primary goal Organization transformation is necessary It is important to remove fear Higher quality costs less
CD-ROM Chap 17-5A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
1. Create a constancy of purpose toward improvement
become more competitive, stay in business, and provide jobs
2. Adopt the new philosophy Better to improve now than to react to problems later
3. Stop depending on inspection to achieve quality -- build in quality from the start
Inspection to find defects at the end of production is too late
4. Stop awarding contracts on the basis of low bids
Better to build long-run purchaser/supplier relationships
Deming’s 14 Points
CD-ROM Chap 17-6A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
5. Improve the system continuously to improve quality and thus constantly reduce costs
6. Institute training on the job Workers and managers must know the difference between
common cause and special cause variation
7. Institute leadership Know the difference between leadership and supervision
8. Drive out fear so that everyone may work effectively.
9. Break down barriers between departments so that people can work as a team.
(continued)
Deming’s 14 Points
CD-ROM Chap 17-7A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
10. Eliminate slogans and targets for the workforce They can create adversarial relationships
11. Eliminate quotas and management by objectives
12. Remove barriers to pride of workmanship 13. Institute a vigorous program of education
and self-improvement 14. Make the transformation everyone’s job
(continued)
Deming’s 14 Points
CD-ROM Chap 17-8A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Juran’s 10 Steps to Quality Improvement
1. Build awareness of both the need for improvement and the opportunity for improvement
2. Set goals for improvement 3. Organize to meet the goals that have been
set 4. Provide training 5. Implement projects aimed at solving
problems
CD-ROM Chap 17-9A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Juran’s 10 Steps to Quality Improvement
6. Report progress 7. Give recognition 8. Communicate the results 9. Keep score 10. Maintain momentum by building
improvement into the company’s regular systems
(continued)
CD-ROM Chap 17-10A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Deming Cycle
The Deming
CycleThe key is a continuous cycle of improvement
Act
Plan
Do
Study
CD-ROM Chap 17-11A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Basic 7 Tools
1. Process Flowcharts
2. Brainstorming
3. Fishbone Diagram
4. Histogram
5. Trend Charts
6. Scatter Plots
7. Statistical Process Control Charts
CD-ROM Chap 17-12A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Basic 7 Tools
1. Process Flowcharts
2. Brainstorming
3. Fishbone Diagram
4. Histogram
5. Trend Charts
6. Scatter Plots
7. Statistical Process Control Charts
Map out the process to better visualize and understand opportunities for improvement
(continued)
CD-ROM Chap 17-13A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Basic 7 Tools
1. Process Flowcharts
2. Brainstorming
3. Fishbone Diagram
4. Histogram
5. Trend Charts
6. Scatter Plots
7. Statistical Process Control Charts
Cause 4Cause 3
Cause 2Cause 1
Problem
Fishbone (cause-and-effect) diagram:
Sub-causes
Sub-causes
Show patterns of variation
(continued)
CD-ROM Chap 17-14A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Basic 7 Tools
1. Process Flowcharts
2. Brainstorming
3. Fishbone Diagram
4. Histogram
5. Trend Charts
6. Scatter Plots
7. Statistical Process Control Charts
time
y
x
y
Identify trend
Examine relationships
(continued)
CD-ROM Chap 17-15A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The Basic 7 Tools
1. Process Flowcharts
2. Brainstorming
3. Fishbone Diagram
4. Histogram
5. Trend Charts
6. Scatter Plots
7. Statistical Process Control Charts
X
Examine the performance of a process over time
time
(continued)
CD-ROM Chap 17-16A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Introduction to Control Charts
Control Charts are used to monitor variation in a measured value from a process Exhibits trend
Can make correction before process is out of control
A process is a repeatable series of steps leading to a specific goal
Inherent variation refers to process variation that exists naturally. This variation can be reduced but not eliminated
CD-ROM Chap 17-17A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Variation
Total Process Variation
Common Cause Variation
Special Cause Variation= +
Variation is natural; inherent in the world around us
No two products or service experiences are exactly the same
With a fine enough gauge, all things can be seen to differ
CD-ROM Chap 17-18A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Sources of Variation
Total Process Variation
Common Cause Variation
Special Cause Variation= +
People Machines Materials Methods Measurement Environment
Variation is often due to differences in:
CD-ROM Chap 17-19A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Common Cause Variation
Total Process Variation
Common Cause Variation
Special Cause Variation= +
Common cause variation naturally occurring and expected the result of normal variation in
materials, tools, machines, operators, and the environment
CD-ROM Chap 17-20A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Special Cause Variation
Total Process Variation
Common Cause Variation
Special Cause Variation= +
Special cause variation abnormal or unexpected variation has an assignable cause variation beyond what is considered
inherent to the process
CD-ROM Chap 17-21A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Statistical Process Control Charts
Show when changes in data are due to: Special or assignable causes
Fluctuations not inherent to a process Represents problems to be corrected Data outside control limits or trend
Common causes or chance Inherent random variations Consist of numerous small causes of random
variability
CD-ROM Chap 17-22A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Average
Control Chart Basics
UCL = Process Average + 3 Standard Deviations LCL = Process Average – 3 Standard Deviations
UCL
LCL
+3σ
- 3σ
Common Cause Variation: range of expected variability
Special Cause Variation: Range of unexpected variability
time
CD-ROM Chap 17-23A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Average
Process Variability
UCL = Process Average + 3 Standard Deviations LCL = Process Average – 3 Standard Deviations
UCL
LCL
±3σ → 99.7% of process values should be in this range
time
Special Cause of Variation: A measurement this far from the process average is very unlikely if only expected variation is present
CD-ROM Chap 17-24A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Statistical Process Control Charts
Statistical Process Control
Charts
X-bar charts and R-charts
c-charts
Used for measured
numeric data
Used for proportions
(attribute data)
Used for number of
attributes per sampling unit
p-charts
CD-ROM Chap 17-25A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
x-bar chart and R-chart
Used for measured numeric data from a process
Start with at least 20 subgroups of observed values
Subgroups usually contain 3 to 6 observations each
CD-ROM Chap 17-26A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Steps to create an x-chart and an R-chart
Calculate subgroup means and ranges
Compute the average of the subgroup means and the average range value
Prepare graphs of the subgroup means and ranges as a line chart
CD-ROM Chap 17-27A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Steps to create an x-chart and an R-chart
Compute the upper and lower control limits for the x-bar chart
Compute the upper and lower control limits for the R-chart
Use lines to show the control limits on the x-bar and R-charts
(continued)
CD-ROM Chap 17-28A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Example: x-chart
Process measurements:
Subgroup measuresSubgroup number Individual measurements Mean, x Range, R
1
2
3
…
15
12
17
…
17
16
21
…
15
9
18
…
11
15
20
…
14.5
13.0
19.0
…
6
7
4
…Average subgroup
mean = x
Average subgroup range = R
CD-ROM Chap 17-29A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Average of Subgroup Means and Ranges
k
xx i
k
RR i
Average of subgroup means:
where:xi = ith subgroup average
k = number of subgroups
Average of subgroup ranges:
where:Ri = ith subgroup range
k = number of subgroups
CD-ROM Chap 17-30A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Computing Control Limits
The upper and lower control limits for an x-chart are generally defined as
or
UCL = Process Average + 3 Standard Deviations LCL = Process Average – 3 Standard Deviations
3
3
xLCL
xUCL
CD-ROM Chap 17-31A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Computing Control Limits
Since control charts were developed before it was easy to calculate σ, the interval was formed using R instead
The value A2R is used to estimate 3σ , where A2 is from Appendix Q
The upper and lower control limits are
)R(AxLCL
)R(AxUCL
2
2
(continued)
where A2 = Shewhart factor for subgroup size n from appendix Q
CD-ROM Chap 17-32A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Example: R-chart
The upper and lower control limits for an R-chart are
)R(DLCL
)R(DUCL
3
4
where:D4 and D3 are taken from the Shewhart table(appendix Q) for subgroup size = n
CD-ROM Chap 17-33A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
x-chart and R-chart
UCL
LCL
time
x
UCL
LCL
time
RR-chart
x-chart
CD-ROM Chap 17-34A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Using Control Charts
Control Charts are used to check for process control
H0: The process is in control i.e., variation is only due to common causes
HA: The process is out of control i.e., special cause variation exists
If the process is found to be out of control, steps should be taken to find and eliminate the special causes of variation
CD-ROM Chap 17-35A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process In Control
Process in control: points are randomly distributed around the center line and all points are within the control limits
UCL
LCL
x
x
time
CD-ROM Chap 17-36A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Not in Control
Out of control conditions: One or more points outside control limits
Nine or more points in a row on one side of the center line
Six or more points moving in the same direction
14 or more points alternating above and below the center line
CD-ROM Chap 17-37A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Not in Control
One or more points outside control limits
UCL
LCL
x
Nine or more points in a row on one side of the center line
UCL
LCL
x
Six or more points moving in the same direction
UCL
LCL
x
14 or more points alternating above and below the center line
UCL
LCL
x
CD-ROM Chap 17-38A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Out-of-control Processes
When the control chart indicates an out-of-control condition (a point outside the control limits or exhibiting trend, for example) Contains both common causes of variation and
assignable causes of variation The assignable causes of variation must be identified
If detrimental to the quality, assignable causes of variation must be removed
If increases quality, assignable causes must be incorporated into the process design
CD-ROM Chap 17-39A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
p-Chart
Control chart for proportions Is an attribute chart
Shows proportion of nonconforming items Example -- Computer chips: Count the number of
defective chips and divide by total chips inspected Chip is either defective or not defective Finding a defective chip can be classified a
“success”
CD-ROM Chap 17-40A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
p-Chart
Used with equal or unequal sample sizes (subgroups) over time Unequal sizes should not differ by more than ±25%
from average sample sizes Easier to develop with equal sample sizes
Should have np > 5 and n(1-p) > 5
(continued)
CD-ROM Chap 17-41A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Creating a p-Chart
Calculate subgroup proportions
Compute the average of the subgroup proportions
Prepare graphs of the subgroup proportions as a line chart
Compute the upper and lower control limits
Use lines to show the control limits on the p-chart
CD-ROM Chap 17-42A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
p-Chart Example
Subgroup number
Sample size
Number of successes Proportion, p
1
2
3
…
150
150
150
15
12
17
…
10.00
8.00
11.33
…Average subgroup
proportion = p
CD-ROM Chap 17-43A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Average of Subgroup Proportions
The average of subgroup proportions = p
where: pi = sample proportion for subgroup i k = number of subgroups of size n
where: ni = number of items in sample i ni = total number of items
sampled in k samples
If equal sample sizes: If unequal sample sizes:
k
pp i
i
ii
n
pnp
CD-ROM Chap 17-44A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Computing Control Limits
The upper and lower control limits for an p-chart are
or
UCL = Average Proportion + 3 Standard Deviations LCL = Average Proportion – 3 Standard Deviations
3
3
pLCL
pUCL
CD-ROM Chap 17-45A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Standard Deviation of Subgroup Proportions
The estimate of the standard deviation for the subgroup proportions is
n
)p)(1p(s
p
If equal sample sizes: If unequal sample sizes:
where: = mean subgroup
proportion n = common sample size
p
Generally, is computed separately for each different sample size
ps
CD-ROM Chap 17-46A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Computing Control Limits
The upper and lower control limits for the p-chart are
(continued)
n
)p)(1p(pLCL
n
)p)(1p(pUCL
3
3
)s(pLCL
)s(pUCL
p
p
3
3
If sample sizes are equal, this becomes
Proportions are never negative, so if the calculated lower control limit is negative, set LCL = 0
CD-ROM Chap 17-47A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
p-Chart Examples
For equal sample sizes
For unequal sample sizes
UCL
LCL
UCL
LCL
p p
ps is constant since
n is the same for all subgroups
ps varies for each
subgroup since ni varies
CD-ROM Chap 17-48A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
c-Chart
Control chart for number of nonconformities (occurrences) per sampling unit (an area of opportunity) Also a type of attribute chart
Shows total number of nonconforming items per unit examples: number of flaws per pane of glass
number of errors per page of code
Assume that the size of each sampling unit remains constant
CD-ROM Chap 17-49A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Mean and Standard Deviationfor a c-Chart
The mean for a c-chart is
k
xc i
The standard deviation for a c-chart is
cs
where: xi = number of successes per sampling unit k = number of sampling units
CD-ROM Chap 17-50A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
c-Chart Control Limits
ccLCL
ccUCL
3
3
The control limits for a c-chart are
CD-ROM Chap 17-51A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Process Control
Determine process control for p-chars and c-charts using the same rules as for x-bar and R-charts
Out of control conditions: One or more points outside control limits
Nine or more points in a row on one side of the center line
Six or more points moving in the same direction
14 or more points alternating above and below the center line
CD-ROM Chap 17-52A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
c-Chart Example
A weaving machine makes cloth in a standard width. Random samples of 10 meters of cloth are examined for flaws. Is the process in control?
Sample number 1 2 3 4 5 6 7
Flaws found 2 1 3 0 5 1 0
CD-ROM Chap 17-53A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Constructing the c-Chart
The mean and standard deviation are:
1.71437
0150312
k
xc i
1.30931.7143cs
2.2143(1.3093)1.7143c3cLCL
5.6423(1.3093)1.7143c3cUCL
The control limits are:
Note: LCL < 0 so set LCL = 0
CD-ROM Chap 17-54A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
The completed c-Chart
The process is in control. Individual points are distributed around the center line without any pattern. Any improvement in the process must come from reduction in common-cause variation
UCL = 5.642
LCL = 0
Sample number1 2 3 4 5 6 7
c = 1.714
6
5
4
3
2
1
0
CD-ROM Chap 17-55A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc.
Chapter Summary
Reviewed the philosophy of quality management Demings 14 points Juran’s 10 steps
Described the seven basic tools of quality Discussed the theory of control charts
Common cause variation vs. special cause variation
Constructed and interpreted x-bar and R-charts Constructed and interpreted p-charts Constructed and interpreted c-charts