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An Introduction to Statistical Process Control
Charts (SPC)
Steve Harrison
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Topics
• Variation – A Quick Recap
• An introduction to SPC Charts
• Interpretation
• Quiz
• Application in Improvement work
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Variation
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Common Cause Variation
• Typically due to a large number of small sources
of variation
• Example: Variation in work commute due to
traffic lights, pedestrian traffic, parking issues
• Usually requires a deep understanding of the
process to minimise the variation
• Multiple factors
5
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Special Cause Variation
• Are not part of the normal process. Arises from
special circumstances
• Example: Variation in work commute impacted
by flat tyre, road closure, ice and snow.
• Usually best uncovered when monitoring data in
real time (or close to that)
• Assignable cause
6
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0
20
40
60
80
100
120
Consecutive trips
Min.
Special Cause - My trip to work
Mean
Upper process limit
Lower process limit
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Two Types of Variation
Special Cause:
• assignable cause
• signal
Common Cause:
• chance cause
• noise
Statistically significant (not good or bad)
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SPC Charts
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SPC, Statistical Process Control
or The Control Chart
Elements
1. Chart/graph showing data, running record, time
order sequence
2. A line showing the mean
3. 2 lines showing the upper and lower process
‘control’ limits
Its best if you have 25 data points to set up a control chart, but
50 are better if available. Be careful of too many points…
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The Anatomy of an SPC or Control Chart
0
10
20
30
40
50
60
70
80
F M A M J J A S O N D J F M A M J J A S O N D
Upper
process
control limit
Mean
Lower
process
control limit
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Measures of Central Tendency
• Mean = Average – SPC Chart
• Median = Central or Middle Value – Run Chart
• Mode = Most frequently occurring value
12
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Standard Deviation or σ
In statistics, standard deviation shows how much
variation exists from the mean.
A low standard deviation indicates that the data
points tend to be very close to the mean; high
standard deviation indicates that the data points
are spread out over a large range of values.
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Standard Deviation and a normal distribution
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PRACTICAL INTERPRETATION OF THE STANDARD DEVIATION
Mean Mean + 3s Mean - 3s
99.7% will be within 3 s
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3s AND THE CONTROL CHART
6s
3s
3s
UCL
LCL
Mean
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Run Charts vs. SPC Charts
Run Chart
• Simple
• Easy to create in Excel or
on paper
• Less Sensitive
• Only need 12-15 data
points
SPC
• More Powerful
• Control lines show the
degree of variation
• Need software
• Better with 25+ data
points
17
0
10
20
30
40
50
60
70
80
4-A
pr
6-A
pr
8-A
pr
12
-Ap
r
14
-Ap
r
18
-Ap
r
20
-Ap
r
22
-Ap
r
3-M
ay
5-M
ay
9-M
ay
11
-May
13
-May
15
-May
% D
aily
TT
Os C
om
ple
ted
by N
oo
n
Ward x – % of total TTOs completed by 12 noon April 4 - May 15, 2012
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Special cause variation
0
10
20
30
40
50
60
70
80
90
F M A M J J A S O N D J F M A M J J A S O N D
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Point above Upper Control Limit (UCL)
SPECIAL CAUSES - RULE 1
MEAN
LCL
UCL
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Or point below Lower Control Limit (LCL)
SPECIAL CAUSES - RULE 1
MEAN
LCL
UCL
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MEAN
Eight points above centre line
SPECIAL CAUSES - RULE 2
LCL
UCL
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MEAN
SPECIAL CAUSES - RULE 2
LCL
UCL Or eight points below centre line
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MEAN
Six points in a downward direction
SPECIAL CAUSES - RULE 3
LCL
UCL
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MEAN
SPECIAL CAUSES - RULE 3
LCL
Or six points in an upward direction
UCL
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Quiz – Does the chart show
A. Special Cause
Variation?
B. Common Cause
Variation?
C. Both of the above
D. No Variation
Special C
ause V
ariatio
n?
Comm
on Cause
Varia
tion?
Both o
f the above
No Varia
tion
0% 0%
33%
67%
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How many special cause signals are present
on this chart?
A. 0
B. 1
C. 2
D. 3
E. 16
0 1 2 3 16
33%
67%
0%0%0%
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How many special cause signals are present
on this chart?
A. 0
B. 1
C. 2
D. 3
E. 16
0 1 2 3 16
0% 0% 0%0%
100%
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How many special cause signals are present
on this chart?
A. 0
B. 1
C. 2
D. 3
E. 16
0 1 2 3 16
0% 0% 0%
100%
0%
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What use is this?
• Evaluate and improve underlying process
• Is the process stable?
• Use data to make predictions and help planning
• Recognise variation
• Prove/disprove assumptions and (mis)conceptions
• Help drive improvement – identify statistically
significant change
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Example
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Annotated SPC Charts
• One of the most powerful tools for improvement
• Describe a process captured over time (as
opposed to being a single sample)
• Reveal any trends a process might be
experiencing
• When combined with careful annotation they track
the impact of change
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Annotated SPC Charts
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Application – Responding to Variation
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Process with
common cause
variation
Reduce variation:
make the process even more reliable
Not satisfied with result:
redesign process to get a better
result
Process with
special cause
variation
Identify the cause:
if positive then can it be replicated or
standardized. If negative then cause
needs to be eliminated
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PRACTICAL
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Length Of Stay for Bowel Surgery Patients
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Quality Composite Ratio
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Outpatient attendances (Part 1)
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Outpatient attendances (Part 2)
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% discharged by noon
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THANKS!
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