Post on 13-Jul-2020
An Introduction to Statistical Process Control
Charts (SPC)
Steve Harrison
Topics
• Variation – A Quick Recap
• An introduction to SPC Charts
• Interpretation
• Quiz
• Application in Improvement work
Variation
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
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
0
20
40
60
80
100
120
Consecutive trips
Min.
Special Cause - My trip to work
Mean
Upper process limit
Lower process limit
Two Types of Variation
Special Cause:
• assignable cause
• signal
Common Cause:
• chance cause
• noise
Statistically significant (not good or bad)
8
SPC Charts
9
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…
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
Measures of Central Tendency
• Mean = Average – SPC Chart
• Median = Central or Middle Value – Run Chart
• Mode = Most frequently occurring value
12
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.
Standard Deviation and a normal distribution
PRACTICAL INTERPRETATION OF THE STANDARD DEVIATION
Mean Mean + 3s Mean - 3s
99.7% will be within 3 s
3s AND THE CONTROL CHART
6s
3s
3s
UCL
LCL
Mean
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
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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
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
Point above Upper Control Limit (UCL)
SPECIAL CAUSES - RULE 1
MEAN
LCL
UCL
Or point below Lower Control Limit (LCL)
SPECIAL CAUSES - RULE 1
MEAN
LCL
UCL
MEAN
Eight points above centre line
SPECIAL CAUSES - RULE 2
LCL
UCL
MEAN
SPECIAL CAUSES - RULE 2
LCL
UCL Or eight points below centre line
MEAN
Six points in a downward direction
SPECIAL CAUSES - RULE 3
LCL
UCL
MEAN
SPECIAL CAUSES - RULE 3
LCL
Or six points in an upward direction
UCL
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%
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%
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%
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%
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
Example
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
Annotated SPC Charts
Application – Responding to Variation
33
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
34
PRACTICAL
Length Of Stay for Bowel Surgery Patients
Quality Composite Ratio
Outpatient attendances (Part 1)
Outpatient attendances (Part 2)
% discharged by noon
THANKS!