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Title: The Basic Seven (B7) Tools of Quality


1
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 AnwarBusiness Advanced Technology
Centre,Universiti Teknologi Malaysia
2
What are the Basic Seven Tools of Quality?
  • Fishbone Diagrams
  • Histograms
  • Pareto Analysis
  • Flowcharts
  • Scatter Plots
  • Run Charts
  • Control Charts

3
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.

4
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

5
Fishbone Diagram Overview (1 of 2)
  • Definition
  • Uses
  • Ishikawa
  • Use within organizations
  • benefits
  • Creation of the Diagram
  • Steps 1-9

6
Fishbone Diagram Overview (2 of 2)
  • Example
  • Service example
  • Exercise
  • Ham Industries

7
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

8
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

9
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

10
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

11
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

12
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)

13
Creating a Fishbone Diagram (2 of 4)
  • 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

14
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

15
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

16
Example (1 of 4)
  • Step 1 2

Poor Service
(backbone)
(head)
17
Example (2 of 4)
  • Step 3 4

Responsiveness
Appearance
Poor Service
Reliability
Attention
18
Example (3 of 4)
  • Step 5, 6, 7

Responsiveness
Appearance
time
equipment
personnel
facility
Poor Service
accuracy
One on one service
courtesy
dependability
Reliability
Attention
19
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

20
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

21
Summary (2 of 3)
  • Organizational Uses
  • Increases communication about problems
  • Used to improve any product, process, or service
  • Important part of quality management

22
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)

23
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.

24
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.html
  • Foster, S. Thomas. Managing Quality An
    Integrative Approach. 2001, Prentice-Hall

25
The Basic Seven (B7) Tools of Quality
  • Histograms
  • Bar chart
  • Used to graphically represent groups of data

26
Overview
  • 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.

27
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.

28
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.

29
Example of a Histogram

30
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.

31
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.

32
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.

33
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.

34
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.

35
How do Histograms Work? (cont)
  • After you have created a Histogram, it will take
    one of five shapes
  • Normal Distribution

36
How do Histograms Work? (cont)
  • Positively Skewed
  • Negatively Skewed

37
How do Histograms Work? (cont)
  • Bi-Modal Distribution
  • Multi-Modal Distribution

38
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.

39
Constructing a Histogram
  • From a set of data compute
  • sum
  • mean (x)
  • Max
  • Min
  • Range (max-min)

40
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
Width
of Columns
41
Acme Pizza Example
  • Lets say the owner wants a distribution of
    Acmes Thursday Night Sales
  • Data Set from last Thursday(slices)
  • 0 2 1 2 2 4 1 3 1 2 1 2 2 4 3 4 1 4 3 2 2 3 2
    1 2 2 1 2 2 1 4 2 2 1 2 1 2 2 1 2 1 2 1 2 1 2 1 2
    1 2 2 2 1 2 1 2 1 1 2 2 2 3 1 4 2 2 3 2 2 2 1 2 3
    2 2 4 2 2 4 4 1 2 2 2 3 2 2 1 2 2 4 2 1 2 4 2 1 7
    2 1 2 2 3 1 2 1 1 2 1 2 2 2 1 2 2 1 2 1 2 2 2 4 2
    4

42
Acme Pizza Example
  • Mean 2.032258
  • Max 7
  • Min 0
  • Range 7
  • Question
  • For 7 columns what would the width be?

Range/Columns7/71 slice
43
Acme Pizza Example
Histogram
times ordered
Slices of Pizza
44
Constructing a Histogram
  • How is this helpful to Acme?
  • 2 slices of pizza most common order placed
  • Distribution of sales useful for forecasting next
    Thursdays late night demand
  • If you were an Acme manager how could you apply
    this information?

45
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

46
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.

47
Acme Pizza (Example 1)
  • Slices Frequency
  • 0 1 .3
  • 1 33 13.09
  • 2 65 25.79
  • 3 8 3.17
  • 4 12 4.76
  • 5 0 0
  • 6 0 0
  • 7 1 .3

48
Acme Pizza (Example 1)
  • The completed Pareto Analysis results in the
    following graph

times ordered
2
1
4
3
7
5
6
Slices of Pizza
49
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?

50
A series of Pareto charts drill down to more
detail (Example 2)
1st level Analysis gives Design as main cause
of failure
2nd level Analysis gives breakdown of Design
51
The Basic Seven (B7) Tools of Quality
  • Flowcharts
  • A graphical picture of a PROCESS

Process
Decision
The process flow
52
Flowcharts
  • Dont Forget to
  • Define symbols before beginning
  • Stay consistent
  • Check that process is accurate

53
Acme Pizza Example (Flowchart)
  • Window Take Customer Money?
  • (start) Order
  • Get Pizza
  • Lockup
  • Put More in
  • Oven 2 Pies
  • Available?
  • Time
  • to close?
  • Take to Customer

yes
no
no
yes
no
yes
54
How can we use the flowchart to analyze
improvement ideas from the Histogram?
  • Window Take Customer Money?
  • (start) Order
  • Get Pizza
  • Lockup
  • Put More in
  • Oven 2 Pies
  • Available?
  • Time
  • to close?
  • Take to Customer

yes
no
no
yes
no
yes
55
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?

56
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

57
Acme Pizza (Scatter Diagram)
  • Minutes Cooking Defective Pies
  • 10 1
  • 45 8
  • 30 5
  • 75 20
  • 60 14
  • 20 4
  • 25 6
  • In this simple example, you can find the
    existing relationship without much difficulty but

58
Scatter Diagrams
  • Easier to see direct relationship

Defective Pizzas
Time Cooking (minutes)
59
Scatter Diagrams
  • As a quality tool
  • What does this tell Acme management about their
    processes?
  • Improvements?

Defective Pizzas
Time Cooking (minutes)
60
The Basic Seven (B7) Tools of Quality
  • Run charts
  • Time-based (x-axis)
  • Cyclical
  • Look for patterns

61
Run Charts
Slices/hour
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85
90 95 100
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
Time
PM- AM
PM- AM
PM- AM
Thursday Week 1
Thursday Week 2
Thursday Week 3
62
The Basic Seven (B7) Tools of Quality
  • Control Charts
  • Deviation from Mean
  • Upper and Lower Specs
  • Range

63
Control Charts
  • Upper Limit
  • Lower Limit

X
Unacceptable deviation
64
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

65
Acme example Control Charts
  • Upper Limit
  • 17 inches
  • Lower Limit
  • 15 Inches

X
16 inches
Small Pie
66
Acme example 50Control Charts
  • Pies within specifications were acceptable
  • One abnormally small pie is uncommon
  • Should be examined for quality control

67
Logical Order for B7 Tools
Big Picture
Data Collection
Data Analysis
ProblemIdentification
Prioritization
FlowChart
CheckSheet
Histograms
CauseEffect
ParetoAnalysis
ScatterDiagrams
ControlCharts
68
Summary
  • Basic Seven Tools of Quality
  • Measuring data
  • Quality Analysis
  • Democratized statistics

69
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.go
    v.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.
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