第 16章 质量管理
Quality Management
本章概要
? Total Quality Management (TQM)
? Theory of Process Management
? The Theory of Control Charts
Common Cause Variation Vs Special Cause Variation
? Control Charts for the Proportion of Nonconforming
Items
? Process Variability
? Control charts for the Mean and the Range
Themes of Quality Management
质量管理主题
1,Primary Focus on Process Improvement
2,Most Variation in Process due to System
3,Teamwork is Integral to Quality Management
4,Customer Satisfaction is a Primary Goal
5,Organization Transformation Necessary
6,Remove Fear
7,Higher Quality Costs Less
一,14个要点,
Point 1
Create Consistency of Purpose
Plan
DoStudy
Act
The Shewhart-Deming Cycle
Focus on Constant Improvement
Points 2 and 3
Point 2,Adopt New Philosophy
Better to be proactive and change before crisis occurs.
Point 3,Cease Dependence on Mass
Inspection to Achieve Quality
Any Inspection whose purpose is to
improve quality
is too late.
Points 4 and 5
Point 4,End the Practice of Awarding Business on the
Basis of Price Tag Alone
Develop long term relationship between purchaser
and supplier.
Point 5,Improve Constantly and Forever.
Reinforce the importance of the
continuous focus of the Shewhart
cycle.
Points 6 and 7
Point 6,Institute Training.
Especially important for Managers to
understand the difference between special causes
and common causes.
Point 7,Adopt and Institute Leadership
Differentiate between leadership and
supervision,Leadership is to improve the
system and achieve greater consistency of
performance.
Points 8 to 12
Points 8-12.
Drive out Fear
Break Down Barriers Between Staff Areas
Eliminate Slogans
Eliminate Numerical Quotas for Workforce
Eliminate Numerical Goals for Management
Remove Barriers to Pride of
Workmanship 300
Quality is
important
Points 13 and 14
Point 13,Encourage Education and Self-Improvement
for Everyone
Improve knowledge of people
will improve assets of
organization.
Point 14,Take Action to Accomplish Transformation
Continually strive toward improvement.
Control Charts
控制图
? Monitors Variation in Data
? Exhibits Trend - Make Correction Before
Process is Out of control
? 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
? Chance or Common Causes
? Inherent Random Variations
0
20
40
60
1 3 5 7 9 11
X
T i m e
0
20
40
60
1 3 5 7 9 11
X
T i m e
Graph of sample data plotted over timeAssignable
Cause
Variation
Random
Variation
Process
Average
???
Mean
Process Control Chart
过程控制图
UCL
LCL
Control Limits
控制限
UCL = Process Average + 3 Standard Deviations
LCL = Process Average - 3 Standard Deviations
Process
Average
UCL
LCL
X
+ 3?
- 3?
TIME
Types of Error
误差类型
? First Type,Belief that Observed Value
Represents Special Cause When in Fact
it is Due to Common Cause
? Second Type,Treating Special Cause
Variation as if it is Common Cause
Variation
Comparing Control Chart Patterns
控制图模式比较
X XX
Common Cause
Variation,No Points
Outside Control Limit
Special Cause
Variation,2 Points
Outside Control Limit
Downward Pattern:
No Points Outside
Control Limit
When to Take Corrective Action
何时采用校正措施
1,Eight Consecutive Points Above the
Center Line (or Eight Below)
2,Eight Consecutive Points that are
Increasing (Decreasing)
Corrective Action should be Taken When
Observing Points Outside the Control
Limits or When a Trend Has Been Detected:
p Chart（概率图）
? Control Chart for Proportions
? Shows Proportion of Nonconforming Items
? e.g.,Count # defective chairs & divide by
total chairs inspected
? Chair is either defective or not defective
? Used With Equal or Unequal Sample Sizes
Over Time
? Unequal sizes should not differ by more than
25% from average sample size
p Chart
Control Limits
n
)p(pp ?? 13
n
)p(pp ?? 13
k
n
n
k
i
i?
? ? 1
Average Group Size
?
?
?
?
?
k
i
i
k
i
i
n
X
1
1
Average Proportion of
Nonconforming Items # Defective
Items in
Sample i
Size of
Sample i
# of Samples
LCLp = UCLp =
p_
p Chart
Example
You are manager of a
500-room hotel,You
want to achieve the
highest level of service,
For 7 days,you collect
data on the readiness of
200 rooms,Is the
process in control?
p Chart
Hotel Data
# Not
Day # Rooms Ready Proportion
1 200 16 0.080
2 200 7 0.035
3 200 21 0.105
4 200 17 0.085
5 200 25 0.125
6 200 19 0.095
7 200 16 0.080
n
n
k p
X
n
p
i
i
k
i
i
k
i
i
k? ? ? ? ? ?
? ? ? ? ? ?
? ?
? ?
?
? ?
?
1 1
1
1400
7 200
121
1400 0864
3 0864 3 0864 1 0864
200
0864 0596,1460
.
.,,
., or,
.0268
p Chart
Control Limits Solution
16 + 7 +...+ 16
? ( )
( )
n
)p(p ?1_
p Chart
Control Chart Solution
UCL
LCL
0.00
0.05
0.10
0.15
1 2 3 4 5 6 7
P
Day
Mean p
_
Process Variability:
Red Bead Example
Four Workers (A,B,C,D) spent 3 days to collect beads,
at 50 beads per day,The expected number of red bead to
be collected per day per worker is 10 or 20%.
Worker Day 1 Day 2 Day 3 All Days
A 9 (18%) 11 (12%) 6 (12%) 26 (17.33%)
B 12 (24%) 12 (24%) 8 (16%) 32 (21.33%)
C 13 (26%) 6 (12%) 12 (24%) 31(20.67%)
D 7 (14%) 9 (18%) 8 (16%) 24 (16.0%)
Totals 41 38 34 113
Process Variability
Example Calculations
Average Day 1 Day 2 Day 3 All Days
X 10.25 9.5 8.5 9.42
p 20.5% 19% 17% 18.83%
1883
1250
113,
)(
p ??
1 6 5 91 8 8 3
50
1 8 8 311 8 8 3
31 8 8 3
1
3
..
).(.
.
n
)p(p
p
??
?
??
?
?
LCL =,1883 -,1659 =,0224
UCL =,1883 +,1659 =,3542
_
Process Variability
Example Control Chart
0 A1 B1 C1 D1 A2 B2 C2 D2 A3 B3 C3 D3
.30
.20
.10
p
UCL
LCL
_
Morals of the Example
1,Variation is an inherent part of any
process.
2,The system is primarily
responsible for worker
performance.
3,Only management can change the system.
4,Some workers will always be above average,
and some will be below.
Variable Control Charts,
R Chart(极差图 )
?Monitors Variability in Process
?Characteristic of interest is measured on interval or
ratio scale.
?Shows Sample Range Over Time
?Difference between smallest & largest values in
inspection sample
?e.g.,Amount of time required for luggage to be
delivered to hotel room
UCL D R
LCL D R
R
R
k
R
R
i
i
k
? ?
? ?
? ?
?
4
3
1
R Chart
Control Limits
Sample
Range
at Time i
# Samples
From
Table
R Chart
Example
You are manager of a
500-room hotel,You
want to analyze the
time it takes to deliver
luggage to the room.
For 7 days,you collect
data on 5 deliveries per
day,Is the process in
control?
R Chart & Mean Chart
Hotel Data
Sample Sample
Day Average Range
1 5.32 3.85
2 6.59 4.27
3 4.88 3.28
4 5.70 2.99
5 4.07 3.61
6 7.34 5.04
7 6.79 4.22
R
R
k
UCL D R
LCL D R
i
i
k
R
R
? ? ? ? ? ?
? ? ? ?
? ? ? ?
?
?
1
4
3
3 85 4 27 4 22
7 3 894
2114 3 894 8 232
0 3 894 0
.,,,
.,,
.
?
R Chart
Control Limits Solution
From
Table E.9
(n = 5)
?
?
_
R Chart
Control Chart Solution
UCL
0
2
4
6
8
1 2 3 4 5 6 7
Minutes
Day
LCL
R
_
Mean Chart (The X Chart)
? Shows Sample Means Over Time
? Compute mean of inspection sample over time
? e.g.,Average luggage delivery time in hotel
? Monitors Process Average
UCL X A R
LCL X A R
X
X
k R
R
k
X
X
i
i
k
i
i
k
? ? ?
? ? ?
? ?? ?
? ?
2
2
1 1and
Mean Chart
Sample
Range
at Time i
# Samples
Sample
Mean at
Time i
Computed
From
Table
_
_
_ _
_
_
__
__ _
_
Mean Chart
Example
You are manager of a
500-room hotel,You
want to analyze the time
it takes to deliver
luggage to the room,For
7 days,you collect data
on 5 deliveries per day,
Is the process in control?
R Chart & Mean Chart
Hotel Data
Sample Sample
Day Average Range
1 5.32 3.85
2 6.59 4.27
3 4.88 3.28
4 5.70 2.99
5 4.07 3.61
6 7.34 5.04
7 6.79 4.22
X
X
R
X
R
R
X
k
R
k
UCL A
LCL A
i
i
k
i
i
k
X
X
? ? ? ? ? ?
? ? ? ? ? ?
? ? ? ? ? ?
? ? ? ? ? ?
?
?
?
?
1
1
2
2
5 32 6 59 6 79
7 5 813
3 85 4 27 4 22
7 3 894
5 813 0 577 3 894 8 060
5 813 0 577 3 894 3 566
.,,,
.,,,
.,,,
.,,,
?
?
Mean Chart
Control Limits Solution
From
Table E.9
(n = 5)
?
?
__
_
__ _
__ _
_
_
_
Mean Chart
Control Chart Solution
UCL
LCL
0
2
4
6
8
1 2 3 4 5 6 7
Minutes
Day
X
__
本章小结
? Described Total Quality Management (TQM)
? Addressed the Theory of Process Management
(Deming抯 Fourteen points)
? Discussed The Theory of Control Charts
Common Cause Variation Vs Special Cause Variation
? Computed Control Charts for the Proportion of
Nonconforming Items
? Described Process Variability
? Computed Control charts for the Mean and the Range
Quality Management
本章概要
? Total Quality Management (TQM)
? Theory of Process Management
? The Theory of Control Charts
Common Cause Variation Vs Special Cause Variation
? Control Charts for the Proportion of Nonconforming
Items
? Process Variability
? Control charts for the Mean and the Range
Themes of Quality Management
质量管理主题
1,Primary Focus on Process Improvement
2,Most Variation in Process due to System
3,Teamwork is Integral to Quality Management
4,Customer Satisfaction is a Primary Goal
5,Organization Transformation Necessary
6,Remove Fear
7,Higher Quality Costs Less
一,14个要点,
Point 1
Create Consistency of Purpose
Plan
DoStudy
Act
The Shewhart-Deming Cycle
Focus on Constant Improvement
Points 2 and 3
Point 2,Adopt New Philosophy
Better to be proactive and change before crisis occurs.
Point 3,Cease Dependence on Mass
Inspection to Achieve Quality
Any Inspection whose purpose is to
improve quality
is too late.
Points 4 and 5
Point 4,End the Practice of Awarding Business on the
Basis of Price Tag Alone
Develop long term relationship between purchaser
and supplier.
Point 5,Improve Constantly and Forever.
Reinforce the importance of the
continuous focus of the Shewhart
cycle.
Points 6 and 7
Point 6,Institute Training.
Especially important for Managers to
understand the difference between special causes
and common causes.
Point 7,Adopt and Institute Leadership
Differentiate between leadership and
supervision,Leadership is to improve the
system and achieve greater consistency of
performance.
Points 8 to 12
Points 8-12.
Drive out Fear
Break Down Barriers Between Staff Areas
Eliminate Slogans
Eliminate Numerical Quotas for Workforce
Eliminate Numerical Goals for Management
Remove Barriers to Pride of
Workmanship 300
Quality is
important
Points 13 and 14
Point 13,Encourage Education and Self-Improvement
for Everyone
Improve knowledge of people
will improve assets of
organization.
Point 14,Take Action to Accomplish Transformation
Continually strive toward improvement.
Control Charts
控制图
? Monitors Variation in Data
? Exhibits Trend - Make Correction Before
Process is Out of control
? 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
? Chance or Common Causes
? Inherent Random Variations
0
20
40
60
1 3 5 7 9 11
X
T i m e
0
20
40
60
1 3 5 7 9 11
X
T i m e
Graph of sample data plotted over timeAssignable
Cause
Variation
Random
Variation
Process
Average
???
Mean
Process Control Chart
过程控制图
UCL
LCL
Control Limits
控制限
UCL = Process Average + 3 Standard Deviations
LCL = Process Average - 3 Standard Deviations
Process
Average
UCL
LCL
X
+ 3?
- 3?
TIME
Types of Error
误差类型
? First Type,Belief that Observed Value
Represents Special Cause When in Fact
it is Due to Common Cause
? Second Type,Treating Special Cause
Variation as if it is Common Cause
Variation
Comparing Control Chart Patterns
控制图模式比较
X XX
Common Cause
Variation,No Points
Outside Control Limit
Special Cause
Variation,2 Points
Outside Control Limit
Downward Pattern:
No Points Outside
Control Limit
When to Take Corrective Action
何时采用校正措施
1,Eight Consecutive Points Above the
Center Line (or Eight Below)
2,Eight Consecutive Points that are
Increasing (Decreasing)
Corrective Action should be Taken When
Observing Points Outside the Control
Limits or When a Trend Has Been Detected:
p Chart（概率图）
? Control Chart for Proportions
? Shows Proportion of Nonconforming Items
? e.g.,Count # defective chairs & divide by
total chairs inspected
? Chair is either defective or not defective
? Used With Equal or Unequal Sample Sizes
Over Time
? Unequal sizes should not differ by more than
25% from average sample size
p Chart
Control Limits
n
)p(pp ?? 13
n
)p(pp ?? 13
k
n
n
k
i
i?
? ? 1
Average Group Size
?
?
?
?
?
k
i
i
k
i
i
n
X
1
1
Average Proportion of
Nonconforming Items # Defective
Items in
Sample i
Size of
Sample i
# of Samples
LCLp = UCLp =
p_
p Chart
Example
You are manager of a
500-room hotel,You
want to achieve the
highest level of service,
For 7 days,you collect
data on the readiness of
200 rooms,Is the
process in control?
p Chart
Hotel Data
# Not
Day # Rooms Ready Proportion
1 200 16 0.080
2 200 7 0.035
3 200 21 0.105
4 200 17 0.085
5 200 25 0.125
6 200 19 0.095
7 200 16 0.080
n
n
k p
X
n
p
i
i
k
i
i
k
i
i
k? ? ? ? ? ?
? ? ? ? ? ?
? ?
? ?
?
? ?
?
1 1
1
1400
7 200
121
1400 0864
3 0864 3 0864 1 0864
200
0864 0596,1460
.
.,,
., or,
.0268
p Chart
Control Limits Solution
16 + 7 +...+ 16
? ( )
( )
n
)p(p ?1_
p Chart
Control Chart Solution
UCL
LCL
0.00
0.05
0.10
0.15
1 2 3 4 5 6 7
P
Day
Mean p
_
Process Variability:
Red Bead Example
Four Workers (A,B,C,D) spent 3 days to collect beads,
at 50 beads per day,The expected number of red bead to
be collected per day per worker is 10 or 20%.
Worker Day 1 Day 2 Day 3 All Days
A 9 (18%) 11 (12%) 6 (12%) 26 (17.33%)
B 12 (24%) 12 (24%) 8 (16%) 32 (21.33%)
C 13 (26%) 6 (12%) 12 (24%) 31(20.67%)
D 7 (14%) 9 (18%) 8 (16%) 24 (16.0%)
Totals 41 38 34 113
Process Variability
Example Calculations
Average Day 1 Day 2 Day 3 All Days
X 10.25 9.5 8.5 9.42
p 20.5% 19% 17% 18.83%
1883
1250
113,
)(
p ??
1 6 5 91 8 8 3
50
1 8 8 311 8 8 3
31 8 8 3
1
3
..
).(.
.
n
)p(p
p
??
?
??
?
?
LCL =,1883 -,1659 =,0224
UCL =,1883 +,1659 =,3542
_
Process Variability
Example Control Chart
0 A1 B1 C1 D1 A2 B2 C2 D2 A3 B3 C3 D3
.30
.20
.10
p
UCL
LCL
_
Morals of the Example
1,Variation is an inherent part of any
process.
2,The system is primarily
responsible for worker
performance.
3,Only management can change the system.
4,Some workers will always be above average,
and some will be below.
Variable Control Charts,
R Chart(极差图 )
?Monitors Variability in Process
?Characteristic of interest is measured on interval or
ratio scale.
?Shows Sample Range Over Time
?Difference between smallest & largest values in
inspection sample
?e.g.,Amount of time required for luggage to be
delivered to hotel room
UCL D R
LCL D R
R
R
k
R
R
i
i
k
? ?
? ?
? ?
?
4
3
1
R Chart
Control Limits
Sample
Range
at Time i
# Samples
From
Table
R Chart
Example
You are manager of a
500-room hotel,You
want to analyze the
time it takes to deliver
luggage to the room.
For 7 days,you collect
data on 5 deliveries per
day,Is the process in
control?
R Chart & Mean Chart
Hotel Data
Sample Sample
Day Average Range
1 5.32 3.85
2 6.59 4.27
3 4.88 3.28
4 5.70 2.99
5 4.07 3.61
6 7.34 5.04
7 6.79 4.22
R
R
k
UCL D R
LCL D R
i
i
k
R
R
? ? ? ? ? ?
? ? ? ?
? ? ? ?
?
?
1
4
3
3 85 4 27 4 22
7 3 894
2114 3 894 8 232
0 3 894 0
.,,,
.,,
.
?
R Chart
Control Limits Solution
From
Table E.9
(n = 5)
?
?
_
R Chart
Control Chart Solution
UCL
0
2
4
6
8
1 2 3 4 5 6 7
Minutes
Day
LCL
R
_
Mean Chart (The X Chart)
? Shows Sample Means Over Time
? Compute mean of inspection sample over time
? e.g.,Average luggage delivery time in hotel
? Monitors Process Average
UCL X A R
LCL X A R
X
X
k R
R
k
X
X
i
i
k
i
i
k
? ? ?
? ? ?
? ?? ?
? ?
2
2
1 1and
Mean Chart
Sample
Range
at Time i
# Samples
Sample
Mean at
Time i
Computed
From
Table
_
_
_ _
_
_
__
__ _
_
Mean Chart
Example
You are manager of a
500-room hotel,You
want to analyze the time
it takes to deliver
luggage to the room,For
7 days,you collect data
on 5 deliveries per day,
Is the process in control?
R Chart & Mean Chart
Hotel Data
Sample Sample
Day Average Range
1 5.32 3.85
2 6.59 4.27
3 4.88 3.28
4 5.70 2.99
5 4.07 3.61
6 7.34 5.04
7 6.79 4.22
X
X
R
X
R
R
X
k
R
k
UCL A
LCL A
i
i
k
i
i
k
X
X
? ? ? ? ? ?
? ? ? ? ? ?
? ? ? ? ? ?
? ? ? ? ? ?
?
?
?
?
1
1
2
2
5 32 6 59 6 79
7 5 813
3 85 4 27 4 22
7 3 894
5 813 0 577 3 894 8 060
5 813 0 577 3 894 3 566
.,,,
.,,,
.,,,
.,,,
?
?
Mean Chart
Control Limits Solution
From
Table E.9
(n = 5)
?
?
__
_
__ _
__ _
_
_
_
Mean Chart
Control Chart Solution
UCL
LCL
0
2
4
6
8
1 2 3 4 5 6 7
Minutes
Day
X
__
本章小结
? Described Total Quality Management (TQM)
? Addressed the Theory of Process Management
(Deming抯 Fourteen points)
? Discussed The Theory of Control Charts
Common Cause Variation Vs Special Cause Variation
? Computed Control Charts for the Proportion of
Nonconforming Items
? Described Process Variability
? Computed Control charts for the Mean and the Range
