The Basic Seven (B7)
Tools of Quality
"As much as 95% of quality related problems in the factory can be solved
with seven fundamental quantitative tools." - Kaoru Ishikawa
By
Zaipul Anwar
Business & Advanced Technology Centre,
Universiti Teknologi Malaysia
What are the Basic Seven Tools
of Quality?







Fishbone Diagrams
Histograms
Pareto Analysis
Flowcharts
Scatter Plots
Run Charts
Control Charts
Where did the Basic Seven come
from?
Kaoru Ishikawa

Known for “Democratizing Statistics”

The Basic Seven Tools made statistical analysis less complicated
for the average person

Good Visual Aids make statistical and quality control more
comprehendible.
The Basic Seven (B7)
Tools of Quality
Fishbone Diagrams

No statistics involved

Maps out a process/problem

Makes improvement easier

Looks like a “Fish Skeleton”
Fishbone Diagram Overview (1 of 2)

Definition



Use within organizations


Uses
Ishikawa
benefits
Creation of the Diagram

Steps 1-9
Fishbone Diagram Overview (2 of 2)

Example


Service example
Exercise

Ham Industries
Fishbone (Cause and Effect or Ishikawa)
Diagrams (1 of 4)

Named after Kaoru Ishikawa





Japanese Quality pioneer
Resembles skeleton of a fish
Focus on causes rather than symptoms of a problem
Emphasizes group communication and brainstorming
Stimulates discussion
Fishbone (Cause and Effect or Ishikawa)
Diagrams (2 of 4)



One of Seven basic tools of Japanese Quality
Leads to increased understanding of complex
problems
Visual and presentational tool
Fishbone (Cause and Effect or Ishikawa)
Diagrams (3 of 4)


Typically done on paper or chalkboard
Recently some computer programs have been
created to make Fishbone Diagrams

Ishikawa Environment
Use in Organizations (1 of 2)

Can be used to improve any product, process, or
service
Any area of the company that is experiencing a
problem
 Isolates all relevant causes

Use in Organizations (2 of 2)

Helps bring a problem into light
Group discussion and brainstorming
 Finds reasons for quality variations, and the
relationships between them

Creating Fishbone Diagrams
(1 of 4)
•
As a group:
1. Establish problem (effect)
-state in clear terms
-agreed upon by entire
group
2. Problem becomes the
“head” of the fish
-draw line to head (“backbone”)
Creating a Fishbone Diagram
(2 of 4)
3.
Decide major causes of the problem
- by brainstorming
- if the effect or problem is part of a process the major
steps in the process can be used
4. Connect major causes to backbone of the
fish with slanting arrows
Creating a Fishbone Diagram
(3 of 4)
5. Brainstorm secondary causes for each of the
major causes
6. Connect these secondary causes to their
respective major causes
7. Repeat steps 5 & 6 for sub-causes dividing
with increased specificity
- usually four or five levels
Creating a Fishbone Diagram
(4 of 4)
8. Analyze and evaluate causes and sub-causes
-may require the use of statistical, analytical, and graphical tools
9. Decide and take action
Example (1 of 4)

Step 1 & 2:
(“backbone”)
Poor Service
(“head”)
Example (2 of 4)

Step 3 & 4:
Appearance
Responsiveness
Poor Service
Attention
Reliability
Example (3 of 4)

Step 5, 6, & 7:
Responsiveness
Appearance
time
equipment
personnel
courtesy
Attention
facility
Poor Service
accuracy
One on one
service
dependability
Reliability
Example (4 of 4)

Step 8 & 9:

Use tools to analyze and evaluate causes



Pareto diagrams, charts, and graphs
Statistical analysis for causes in processes
Decide and take action


Use fishbone diagram, analysis and evaluations to find causes that can
be fixed
Take action to eliminate and fix problem causes
Summary (1 of 3)
•
Fishbone Diagrams
- visual diagram
- resembles fish skeleton
- identifies the causes of a problem (effect), and their
relationships
- created by Kaoru Ishikawa for Quality Management
Summary (2 of 3)

Organizational Uses
Increases communication about problems
 Used to improve any product, process, or service
 Important part of quality management

Summary (3 of 3)

Creation of Fishbone diagrams
Problem or effect is head of fish
 Identify major, secondary and tertiary causes, and
attach to backbone identifying relationships
 Analyze and Evaluate results
 Act to fix the problem(s)

Exercise

Create a Fishbone (cause and effect, Ishikawa)
Diagram for the following:
Management at Ham Industries has noticed that the productivity of its
workers is well below the standard. After interviewing its employees, it was
noticed that a vast majority felt dissatisfied and unhappy with their work.
Your boss has asked you and a group of your peers to find the causes of
worker dissatisfaction . Include all possible causes to at least the secondary
level.
Bibliography
//home.t-online.de/home/kfmaas/q_ishika.html
www.zi.unizh.ch/software/unix/statmath/sas/sasdoc/qc
/chap17/sect1.htm
www.dti.gov.uk/mbp/bpgt/m9ja00001/m9ja0000110.htm
l
Foster, S. Thomas. Managing Quality: An Integrative
Approach. 2001, Prentice-Hall
The Basic Seven (B7)
Tools of Quality
Histograms

Bar chart

Used to graphically represent groups of data
Overview
1)
2)
3)
4)
5)
6)
What is a Histogram?
What are some possible uses for a Histogram?
Where did the Histogram come from?
How do Histograms work?
A real world example.
An exercise.
What is a Histogram?

A Histogram is a variation of a bar chart in
which data values are grouped together and put
into different classes.

This grouping allows you see how frequently
data in each class occur in the data set.
What is a Histogram (cont.)



Higher bars represent more data values in a
class.
Lower bars represent fewer data values in a class.
On the next slide is an example of what a
Histogram looks like.
Example of a Histogram
Uses for a Histogram
A Histogram can be used:
 to display large amounts of data values in a relatively
simple chart form.
 to tell relative frequency of occurrence.
 to easily see the distribution of the data.
 to see if there is variation in the data.
 to make future predictions based on the data.
Where did the Histogram
Come From?

The Histogram was first implemented by Kaoru
Isikawa, one of Japans’ most renowned experts
on quality improvement.

Isikawa spent his life trying to improve quality in
Japan.
Where did the Histogram
Come From? (cont.)

His major contributions to quality improvement
are known as the basic seven tools of quality.

Included in his basic seven tools of quality is the
Histogram.
How do Histograms Work?



First, you need need to pick a process to analyze.
Next, you need a large amount of data, at least 100 data
values so that patterns can become visible.
Then, you need to assemble a table of the data values
that you collected with regards to frequency of data
values.
How do Histograms Work?
(cont)

Next, you need to calculate some statistics for the
Histogram, including: mean, minimum, maximum,
standard deviation, class width, number of classes,
skewness, and kurtosis.

Then, you actually create the Histogram using these
statistics.
How do Histograms Work?
(cont)

After you have created a Histogram, it will
take one of five shapes:

Normal Distribution:
How do Histograms Work?
(cont)

Positively Skewed:

Negatively Skewed:
How do Histograms Work?
(cont)

Bi-Modal Distribution:

Multi-Modal Distribution:
How do Histograms Work?
(cont)

Once your Histogram is complete, you can
analyze its shape, as well as the statistics that you
came up with.

This analysis will help you to make better
decisions toward quality improvements.
Constructing a Histogram
From a set of data compute
 sum
 mean (x)
 Max
 Min
 Range (max-min)
Constructing a Histogram


Use range to estimate beginning and end
Calculate the width of each column by dividing
the range by the number of columns
Range
# of Columns
= Width
Acme Pizza Example

Let’s say the owner wants a distribution of
Acme’s Thursday Night Sales
Data Set from last Thursday(slices)
02122413121224341432232122122142212122121212121
21222121211222314223222123224224412223221224212
421721223121121222122121222424
Acme Pizza Example
Mean = 2.032258
Max = 7
Min = 0
Range = 7
Question
For 7 columns what would the width be?
Range/Columns=7/7=1 slice
Acme Pizza Example
Histogram
65
70
60
50
40
33
30
20
8
10
12
0
0
1
5
6
7
0
1
2
3
4
Slices of Pizza
Constructing a Histogram
How is this helpful to Acme?
 2 slices of pizza most common order placed
 Distribution of sales useful for forecasting next
Thursday’s late night demand
If you were an Acme manager how could you apply
this information?
The Basic Seven (B7)
Tools of Quality
Pareto Analysis

Very similar to Histograms

Use of the 80/20 rule

Use of percentages to show importance
Pareto Analysis, how to use it

1. Gather facts about the problem, using Check Sheets or
Brainstorming, depending on the availability of information.

2. Rank the contributions to the problem in order of frequency.

3. Draw the value (errors, facts, etc) as a bar chart.

4. It can also be helpful to add a line showing the cumulative
percentage of errors as each category is added. This helps to
identify the categories contributing to 80% of the problem.

5. Review the chart – if an 80/20 combination is not obvious,
you may need to redefine your classifications and go back to
Stage 1 or 2.
Acme Pizza (Example 1)
Slices
0
1
2
3
4
5
6
7
Frequency
1
33
65
8
12
0
0
1
%
.3
13.09
25.79
3.17
4.76
0
0
.3
Acme Pizza (Example 1)

The completed Pareto Analysis results in the following graph:
70
60
50
40
30
20
10
0
21
1
2
43
34
75
56
Slices of Pizza
67
Acme Pizza (part 2)

Critical Thinking
How does the Pareto Analysis differ from the
Histogram?

How can this be a useful tool to the Acme boss?
A series of Pareto charts drill down
to more detail (Example 2) :
Fault by Main Cause
1st level
Analysis
gives “Design”
as main cause
of failure
100
70
80
60
Percent
40
30
60
40
20
20
10
0
Count
Percent
Cum %
n
s ig
De
Design Faults
0
ild
Bu
er
Oth
4
5.3
97.4
2
2.6
100.0
100
57
75.0
75.0
13
17.1
92.1
50
80
40
Percent
Defect
t
en
on
mp
Co
Count
Count
50
2nd level
Analysis gives
breakdown of
“Design”
30
20
0
Count
Percent
Cum %
40
20
10
Defect
60
t
ec
nn
Co
le
du
Mo
21
36.8
36.8
s
tor
Mo
ue
q
r
To
10
17.5
54.4
t
uc
tar
sd
ld S Tran
Co
8
14.0
68.4
le
du
Mo
er
IC
AS
8
14.0
82.5
0
n
atio
libr
Ca
IOP
5
8.8
91.2
3
5.3
96.5
n
Imo
2
3.5
100.0
The Basic Seven (B7)
Tools of Quality
Flowcharts

A graphical picture of a PROCESS
Process
Decision
The process flow
Flowcharts
Don’t Forget to:

Define symbols before beginning

Stay consistent

Check that process is accurate
Acme Pizza Example
(Flowchart)
Window
(start)
Take Customer
Order
Money?
yes
Get Pizza
no
Lockup
Put More in
Oven
2 Pies
noAvailable?
yes
Time
to close?
no
Take to Customer
yes
How can we use the flowchart to analyze
improvement ideas from the Histogram?
Window
(start)
Take Customer
Order
Money?
yes
Get Pizza
no
Lockup
Put More in
Oven
2 Pies
noAvailable?
yes
Time
to close?
no
Take to Customer
yes
Want some practice?
Make a flowchart for:





Taking a shower
Cooking dinner
Driving a car
Having a party
Creating a Flowchart
Any other processes you can think of ?
The Basic Seven (B7)
Tools of Quality
Scatter Plots
 2 Dimensional X/Y plots
 Used to show relationship between
independent(x) and dependent(y) variables
Acme Pizza
(Scatter Diagram)
Minutes Cooking
10
45
30
75
60
20
25
Defective Pies
1
8
5
20
14
4
6
In this simple example, you can find the existing relationship without much
difficulty but…
Scatter Diagrams
•Easier to see direct
relationship
25
20
15
10
5
0
0
20
40
60
Time Cooking (minutes)
80
Scatter Diagrams


As a quality tool
What does this tell Acme management about
their processes?
Improvements?
25
20
15
10
5
0
0
20
40
60
Time Cooking (minutes)
80
The Basic Seven (B7)
Tools of Quality
Run charts

Time-based (x-axis)

Cyclical

Look for patterns
Run Charts
Slices/hour
8 9 10 11 12 1 2 3 4
8 9 10 11 12 1 2 3 4 8 9 10 11 12 1 2 3 4
PM- AM
PM- AM
PM- AM
Thursday
Thursday
Thursday
Week 1
Week 2
Week 3
Time
The Basic Seven (B7)
Tools of Quality
Control Charts

Deviation from Mean

Upper and Lower Spec’s

Range
Control Charts
Upper Limit
X
Lower Limit
Unacceptable
deviation
Control Charts
Acme Pizza Management wants to get
in on the control chart action
•Average Diameter = 16 inches
•Upper Limit = 17 inches
•Lower Limit = 15 inches
Acme example
Control Charts
Upper Limit
17 inches
16 inches=X
Lower Limit
15 Inches
Small Pie
Acme example #50
Control Charts
•Pies within specifications were
acceptable
•One abnormally small pie is
“uncommon”
•Should be examined for quality control
Logical Order for B7 Tools
Big
Picture
Flow
Chart
Data
Collection
Check
Sheet
Data
Analysis
Problem
Identification
Prioritization
Histograms
Cause
&
Effect
Pareto
Analysis
Scatter
Diagrams
Control
Charts
Summary

Basic Seven Tools of Quality

Measuring data

Quality Analysis

“Democratized statistics”
Bibliography

Foster, Thomas. Managing Quality. An IntegrativeApproach. Upper Saddle River :
Prentice Hall, 2001.

Stevenson, William. “Supercharging Your Pareto Analysis.” Quality Progress
October 2000:
51-55.

“Dr Kaoru Ishikawa.” Internet
“http://www.dti.gov.uk/mbp/bpgt/m9ja00001/m9ja0000110.html.” 16
February 2001.

“Chemical and Process Engineering.” Internet.
“http://lorien.ncl.ac.uk/ming/spc/spc8.htm.” 17 February 2001.