This document introduces various graphical methods in Minitab that can be used at different stages of the DMAIC cycle for process improvement projects. It discusses histograms, run charts, control charts, box plots, dot plots, scatter plots, marginal plots, matrix plots, and Pareto diagrams. For each type of graph, it provides an example using sample data and step-by-step instructions for creating the graph in Minitab. The document emphasizes that graphics are useful for visualizing relationships in data and communicating findings to others.

1. Introduction in Minitab:
- Graphical Methods
14
12
10
Mean 6,054
StDev 0,2541
N 72
Histogram of Water Content
Normal
Boxplot of Water Content
Frequency
6,66,46,26,05,85,6
8
6
4
2
0
WaterContent 6,50
6,25
6,00
Time Series Plot of Water Content
Water Content
5,75
5,50
WaterContent
6,50
6,25
6,00
5,75
ngCheck
210
200
190
Scatterplot of Recieving Check vs Final check
Index
70635649423528211471
5,75
5,50
Final check
Recievin
240230220210200190180170160
180
170
160
Week 1
Knorr-Bremse Group
Graphical Methods & the DMAIC Cycle
Control
Maintain
DefineMaintain
Improvements
SPC
Control Plans
Project charter
(SMART)
Business Score Card
QFD VOC
D
Documentation QFD + VOC
Strategic Goals
Project strategy
C M
Measure
B li A l iImprove
AI
Baseline Analysis
Process Map
C + E Matrix
M t S t
Analyze
Improve
Adjustment to the
Optimum
FMEA Measurement System
Process Capability
Definition of critical
Inputs
FMEA
S
FMEA
Statistical Tests
Simulation
Tolerancing Statistical Tests
Multi-Vari Studies
Regression
Tolerancing
Always and
Everywhere!
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 2/34
Everywhere!

2. The Use of Graphs
In every phase of the DMAIC cycle during your project work
you will need to answer questions In general we can findyou will need to answer questions. In general we can find
answers for these questions with three methods in the
following order: 1. what kind of practical relations exist, 2. howg p ,
can I present that graphically and 3. which analytical methods
can I use to get the proof.
Graphics are useful in every project in two ways. They are
helpful to visualize the relations and to communicate them.
1. Practical1. Practical
2. GraphicalG ap ca
3. Analytical
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 3/34
y
About this Module
In this module you will be introduced to the
use of the software „Minitab“. After a shortuse of the software „Minitab . After a short
time you will be able to create several different
graphs and understand where to use these .
• Histogram
• Run Chart (Control Chart)( )
• Box Plot
• Dot Plot
• X-Y Scatter Plot
• Marginal Plot
• Matrix Plot
• Pareto Diagram
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 4/34
• Cause and Effect Diagram

3. Histogram
• For this example we need the file: WATER CONTENT.MTW
• The Variable (Y) is the water content of a mixing process.
The process runs 24hrs. at 6 days a week in 3 shifts. The
water contents should be held in the range of 5,5 – 7 %.
This is checked every 2 hrs
Graph
This is checked every 2 hrs.
>Histogram…
Day Time Shift Water Contenty
1 6 1 5,67
1 8 1 6
1 10 1 6,27
1 12 1 6,33
Select a
,
1 14 2 6,53
1 16 2 5,93
1 18 2 6
1 20 2 6,27
type of
graph!
1 20 2 6,27
1 22 3 6,07
1 0 3 6,33
1 2 3 6,13
1 4 3 6 071 4 3 6,07
2 6 1 6,33
2 8 1 6,47
2 10 1 6
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 5/34
Histogram
Graph
>Histogram…
>Simple
Select a
graph>Simple graph
variable
14
12
Histogram of Water Content
ncy
12
10
8
You can adjust the
graph by double
clicking the item you
Freque
6
4
clicking the item you
would like to change.
On the next page we
6,46,26,05,85,6
2
0
On the next page we
will change the
number of intervals
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 6/34
Water Content
6,46,26,05,85,6

4. Histogram
Graph
>Histogram…
>Simple
2. Select
Binning
3 Change>Simple
>Edit X Scale…
3. Change
number of
intervals
14
12
Histogram of Water Content
1. Select the X
axis with a ncy
12
10
8
double click
Freque
6
4
6,556,406,256,105,955,805,655,50
2
0
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 7/34
Water Content
6,556,406,256,105,955,805,655,50
Histogram
Graph
>Histogram…
>With Fit and Groups>With Fit and Groups
>Multiple Graphs
>By Variables
Histogram of Water Content
6,66,46,26,05,85,65,4
3
1 2 3
Mean 6,133
StDev 0 2292
1
g
Normal
2
1
sity
StDev 0,2292
N 12
Mean 6,183
StDev 0,2241
N 12
2
0
3
2
Dens
4 5 6
Mean 6,161
StDev 0,2386
N 12
3
4
6,66,46,26,05,85,65,4
1
0
6,66,46,26,05,85,65,4
Water Content
Mean 5,85
StDev 0,2560
N 12
Mean 5,911
StDev 0 1871
5
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 8/34
StDev 0,1871
N 12
6
Panel variable: Day

5. Histogram
Graph
>Histogram…
>With Fit and Groups
Histogram of Water Content
Normal
2,5
2,0
Day
1
2
3
4
quency
2,0
1,5 Mean StDev N
6,133 0,2292 12
6,183 0,2241 12
5
6
Freq
1,0
0 5
6,161 0,2386 12
5,85 0,2560 12
5,911 0,1871 12
6,083 0,2241 12
6, 83 0,
6,66,46,26,05,85,65,4
0,5
0,0
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 9/34
Water Content
Run Chart – Time Series Plot
Run charts use the same set of data as histograms, but
shows graphically the behavior over a certain time range.
Create a run chart with the same set of data
Stat
Create a run chart with the same set of data.
>Time Series
>Time Series Plot…
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6. Run Chart – Time Series Plot
Stat
>Time Series
>Ti S i Pl t>Time Series Plot…
>Simple
6,50
Time Series Plot of Water Content
ontent
6,25
WaterCo
6,00
5,75
70635649423528211471
5,75
5,50
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 11/34
Index
70635649423528211471
Run Chart – Time Series Plot
Stat
>Time Series
>Ti S i Pl t>Time Series Plot…
>With Groups
Select a
group
variable
6,50
Shift
3
1
2
Time Series Plot of Water Content
ontent
6,25
3
WaterCo
6,00
5,75
70635649423528211471
5,75
5,50
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 12/34
Index
70635649423528211471

7. From a Run Chart to a Control Chart
Stat
>Control Charts
>V i bl Ch t f I di id l
The individual chart is the most simple graph
within the statistical process control (SPC).
>Variable Charts for Individuals
>Individuals…
As the output you get the mean value and the
control limits based on the mean +- 3 StDev.
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 13/34
From a Run Chart to a Control Chart
Stat
>Control Charts
>Variable Charts for Indi id als>Variable Charts for Individuals
>Individuals…
6,75
UCL=6,638
I Chart of Water Content
lValue
6,50
6,25
Individual
6,00
5,75
_
X=6,054
70635649423528211471
,
5,50 LCL=5,469
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 14/34
Observation
70635649423528211471

8. Box Plot
Graph
>Boxplot…
>One Y>One Y
Simple
6,50
Boxplot of Water Content
95%
It represents 90% of the
data and there
ent
6,25 75%
95%data and there
distribution.
Very powerful if data
WaterConte
6,00
25%
50%
y p
are split into
subgroups, see next
page
5,75
25%
5 %
page
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 15/34
5,50
Box Plot
Graph
>Boxplot…
>One Y>One Y
With Groups
6,50
Boxplot of Water Content vs Day
ontent
6,25
WaterCo
6,00
5,75
654321
5,75
5,50
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 16/34
Day
654321

9. Dot Plot
Graph
>Dotplot…
>One Y Simple>One Y Simple
This diagram is very similarThis diagram is very similar
to a histogram.
Always all the data will be
shown
Dotplot of Water Content
shown.
Water Content
6,446,306,166,025,885,745,60
We also have the possibility to split the data in
subgroups (By variable).
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 17/34
Try some possibilities.
Dot Plot
Graph
>Dotplot…
>One Y>One Y
With Groups
Dotplot of Water Content vs Shift
Shift
1
2
Water Content
6,446,306,166,025,885,745,60
3
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10. X-Y Scatter Plot
Graph
>Scatterplot…
>Simple
With scatter plots we can compare two rows of
continuous data and visualize their relation.
>Simple
An example: The results shows the softening temperatures measured during
the final check at the supplier and at the incoming inspection of the customer.
File: SoftenTemp mtw
pp g p
The results of two different plastic types are listed in two columns.
File: SoftenTemp.mtw
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X-Y Scatter Plot
Graph
>Scatterplot…
>Simple
In the menu scatter plots Minitab offers the
option to add a regression line. This subject will
be discussed in week 2>Simple
Graph
be discussed in week 2.
210
200
Scatterplot of Recieving Check vs Final check
>Scatterplot…
>With Regression
ievingCheck
190
180
210
Scatterplot of Recieving Check vs Final check
Reci
180
170
Check
200
190
Final check
240230220210200190180170160
160
RecievingC
180
170
Final check
240230220210200190180170160
170
160
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Final check

11. X-Y Scatter Plot
With Minitab you have the
possibility to adjust the
h f d
Graph
>Scatterplot…
>With Connect and Groups
graphs for your needs.
We need some entries in
h d di l
>With Connect and Groups
the data display.
210 Material
1
2
Scatterplot of Recieving Check vs Final check
Check
200
190
2
RecievingC
180
240230220210200190180170160
170
160
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Final check
Marginal Plot
Graph
>Marginal Plot…
>With Histogram
A further possibility for visualization is a combination
of plots. Using the same data as before.
>With Histogram
We combine a scatter plot with either
histogram, box plot or dot plot.
Marginal Plot of Recieving Check vs Final check
eck
210
200
RecievingChe
190
180
170
Final check
R
240220200180160
170
160
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12. Matrix Plot
Graph
>Matrix Plot…
>Matrix of plots Simple
This is helpful if the problem is more complex.
You visualize the relations. It may serve as a
start point for further investigation>Matrix of plots Simple start point for further investigation.
Day Shift Sample time Temp Pressure Contamination %
File: Contamination.mtw
Day Shift Sample time Temp Pressure Contamination %
1 1 1 91 48 2
1 1 2 97 52 2
1 1 3 88 44 2
1 1 4 87 43 1
1 2 1 109 50 6
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 23/34
Matrix Plot
Graph
>Matrix Plot…
>Matrix of plots Simple
Matrix Plot of Contamination %; Temp; Pressure
>Matrix of plots Simple
Contamination %
5,0
2,5
11010090
2,5
0,0
110
100
Temp
100
90
55
5 02 50 0
50
45
Pressure
555045
? ?
5,02,50,0 555045
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 24/34
What can we learn here? What are the next possible steps?

13. Pareto Diagram
Pareto diagrams sort events vs. their frequencies, e.g. defects as ag q g
function of their occurrence. A rule of thumb says that 20% of the
causes are liable for 80% of the effects.
Example: during an inspection process 4 different types of defects
were monitored over 4 weeks. File: PARETO.CONTROL.MTW
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Pareto Diagram
Stat
>Quality Tools
>P t Ch t>Pareto Chart
Pareto Chart of Defects
1000
800
100
80
Count
Percent
600
00
60
P
400
200
40
20
Defects
Count
12,3
431 293 132 120
Percent 44,2 30,0 13,5
DeformationColorFlawsWeight
0 0
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 26/34
Cum % 44,2 74,2 87,7 100,0

14. Pareto Diagrams
The same data as before.
The diagrams on a weekly
lscale.
Required set up of the data
has shown.
Pareto Chart of reason by W 1 to 4
DefColorFlawsWeight
300
W 1 to 4 = 1 W 1 to 4 = 2 reason
Weight
Flaws
Pareto Chart of reason by W 1 to 4
nt
200
100
Color
Def
Coun
0
300
200
W 1 to 4 = 3 W 1 to 4 = 4 Defects W1 Defects W2 Defects W3 Defects W4 Reason W 1 to 4
Weight Flaws Weight Weight Weight 1
Flaws Flaws Weight Weight Flaws 1
Weight Flaws Flaws Color Weight 1
Def Flaws Def Weight Def 1
Weight Weight Color Flaws Weight 1
DefColorFlawsWeight
100
0
Flaws Weight Flaws Flaws Flaws 1
Weight Flaws Flaws Weight Weight 1
Flaws Weight Weight Def Flaws 1
Weight Flaws Flaws Flaws Weight 1
Flaws Def Weight Weight Flaws 1
Weight Weight Def Flaws Weight 1
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 27/34
reason
g
Cause and Effect Diagram
石川 馨 Kaoru Ishikawa, * 1915, Tokio; † 16. April 1989
He developed the „Ishikawa Diagram“ (1943), also
ll d C A d Eff t Di “called „Cause And Effect Diagram“
A graphic tool that helps identify, sort, and display possible
causes of a problem or quality characteristic.
1. Identify and define the effect (objective or problem)
2 Identify the main categories like 6 M´s:2. Identify the main categories, like 6 M s:
Material, Man, Machine, Measure, Method, Mother nature
3. Identify causes influencing the effect
4. Add detailed levels
5. Analyze the diagram… e.g. by help of Pareto
Circle what you can measure or take action on
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 28/34
y

15. Cause and Effect Diagram
The Cause and Effect diagram is an excellent tool to present e.g.
brainstorming results. It groups collected inputs with respect tog g p p p
the output. This is also named Ishikawa or Fishbone diagram.
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 29/34
Cause and Effect Diagram: Example
Or see Black Belt for further information or examples.
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16. Cause and Effect Diagram
Stat
>Quality Tools
>Ca se and Effect>Cause and Effect
File: Fischbone.mtw
Cause-and-Effect Diagram
Measurements Material Personnel
Dust
Cutting quality
Granulate size
g
to less checks
Externl
Homogeneity
Glass distribution
Granulation temp
Surface condition
Electrical charge
Granulate size
Dust
Weight
Diameter
Length
It is also possible to
Quality
Problems
Nozzle plate
Cutting condition
Cutting technique
Externl
Hot material in cold pipe
Dryer temp
Electrical charge
Silo de-loading
generate sub branches
for each main branch, e.g.
if material split in internal
Environment Methods Machines
Conveyor design
Dust collector
Transport system
Silo de loading
Silo loading
Transport Extern
Transport Intern
if material split in internal
or external causes.
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 31/34
Cause and Effect Diagram
Measurements Material Personnel
Cause-and-Effect Diagram
Measurements Material Personnel
Electrical charge
Granulate size
Dust
Cutting quality
Length
Granulate size
Quality
Problems
to less checks
Externl
Homogeneity
Glass distribution
Granulation temp
Surface condition
Dust
Weight
Diameter
Nozzle plate
Cutting condition
Cutting technique
Conveyor design
D t olle to
Hot material in cold pipe
Dryer temp
Electrical charge
Silo de-loading
Silo loading
Environment Methods Machines
Dust collector
Transport system
Transport Extern
Transport Intern
FishboneFlat cat
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 32/34

17. Cause and Effect Diagram
MaterialMaschine
Mensch
Event ungleich
Spezifikation
Zielsystem fällt aus
Verantw. n. geregelt
Event fehlerhaft
Event leer
EDM Prg.fehler
Mapping n. aktuell
EDM Prg.änderung
EAI
System
fällt aus
Virus
Policy geändert
DB voll
Bedienungs-
fehler
Service n.
gestartetReceive funct. n. gestartet
Event versehentl. gelöscht
Auf Fehler wird n. reagiert
Fehler wird n. bemerkt
Kontrollplan n. vorh./vollst.
Prg. n. getestet
Keiner/falscher Testplan
Fehlerursachen
Stromausfall
OS-Fehler
Uhr verstellt
Verschiedene Zonen
Event fehlerhaft
Neue SW
installiert HW ProblemStammdaten nicht oder falsch def. Falsche Prg.version installiert
ASNA lä ft i ht
wurde
ungeplant
gestoppt
Fehlerhafte
Eingangsdaten
Eingabedaten
zu langFehler in
Messsystem
OS Fehler
Netzwerk
Switch
Überlastung
Provider-
Fehler
SZ / WZ
ASNA läuft nicht
falsch
konf.
nicht
gestartet
Prog.fehler
in KBMW00
Prog fehler in
RPG-Prog.
DB-Locks
Schlüsselwerte
nicht definiert
User sperrt
Datensatz
Fehler in MW
Mitwelt
Methoden
Prog.fehler in
XPPSDispatcherSchedule
Mapping
Konfiguration
Komponent.
Available Fishbone tools are, e.g.
Mi it b MS Vi iMS Vi i MS P i t
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 33/34
Minitab, MS VisioMS Visio, MS Powerpoint
Summary
The following graphical tools have been created
with Minitab:with Minitab:
•Histogram
•Run Chart (Control Chart)Run Chart (Control Chart)
•Box Plot
•Dot Plot•Dot Plot
•X-Y Scatter Plot
•Marginal Plot•Marginal Plot
•Matrix Plot
P t Di•Pareto Diagram
•Cause and Effect Diagram
Knorr-Bremse Group 07 BB W1 Graphics 07, D. Szemkus/H. Winkler Page 34/34