Pareto Diagram -7 QC Tools - ADDVALUE - Nilesh Arora

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TQM / 7 QC Tools
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Introduction

• The 7 QC Tools are simple statistical tools used
  for problem solving
• Inspired after seven famous weapons of Benkei.
  Viz
• Masakari-Broad Axe
• Kumade- Rake
• Nagihama - Sickle weapon
• hizuchi- Wooden mallet
• Nokogiri- Saw
• Tetsubo- iron staff
• sasumata- Half moon spear
• It was possibly introduced by Kaoru Ishikawa who
  in turn was influenced by a series of lectures W.
  Edwards Deming had given to Japanese engineers
  and scientists in 1950

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Conti

• The term 7 tools for QC is named after the 7
  tools of the famous warrior,Benkei. Benkei owned
  7 weapons, which he used to win all his battles.
  Similarly, from my own experience, you will find
  that you will be able to solve 95 of the
  problems around you if you wisely use the 7 tools
  of QC.
• - ISHIKAWA KAORU, Professor Emeritus,
  University of Tokyo
• These tools have been the foundation of Japan's
  astonishing industrial resurgence after the
  second world war.

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Basic QC Tools

• The following are the 7 QC Tools
• 1.Pareto Diagram
• 2.Cause Effect Diagram
• 3.Histogram
• 4.Control Charts
• 5.Scatter Diagrams
• 6.Flowchart
• 7.Check Sheets

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Pareto Diagram 1/2

• Origin of the tool lies in the observation by an
  Italian economist Vilfredo Pareto that a large
  portion of wealth was in the hands of a few
  people.
• Dr.Juran suggested the use of this principle to
  quality control for separating the "vital few"
  problems from the "useful many".
• Also referred as 80/20 rule viz your 80 of
  problems are due to 20 of cause.
• It is used in the field of materials management
  for ABC analysis. 20 of the items purchased by a
  company account for 80 of the value. These
  constitute the A items on which maximum attention
  is paid
• It works on cumulative frequency and shows how
  few items exert maximum influence

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Pareto Diagram 2/2

• For E.g
• 80 of sales revenue is earned by 20 of firms
  products
• 20 of the items in a factory Store may account
  for 80 of the volume of items issued
• 80 of defects are caused by 20 of the possible
  defects type
• Also used in conjunction with Brainstorming,
  Cause and Effect Analysis and Cumulative Line
  Chart. The Diagram displays, in decreasing order,
  the relative contribution of each cause or
  problem to the total
• The relative contribution can be based on the
  number of occurrences, the quality damage or the
  cost associated with each cause or problem

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How to create a Pareto Diagram 1/2
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Types of Defects No.of Defects Cumulative Total
D-Pause Fail 104 104
B-W/High 42 146
F-Auto Stop Fail 20 166
G-Others 14 180
A-Lever Tight 10 190
C-Less Torque 6 196
E-Abnormal noise 4 200
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Types of Defects Number of Defects
D-Pause Fail 104
B-W/High 42
F-Auto Stop Fail 20
G-Others 14
A-Lever Tight 10
C-Less Torque 6
E-Abnormal noise 4
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Types of Defects Number of Defects
A-Lever Tight 10
B-W/High 42
C-Less Torque 6
D-Pause Fail 104
E-Abnormal noise 4
F-Auto Stop Fail 20
G-Others 14
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Types of Defects Number of Defects Cumulative Total Cumulative
D-Pause Fail 104 104 52
B-W/High 42 146 73
F-Auto Stop Fail 20 166 83
G-Others 14 180 90
A-Lever Tight 10 190 95
C-Less Torque 6 196 98
E-Abnormal noise 4 200 100
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How to create a Pareto Diagram 2/2
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Pareto Diagram
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Cause Effect Diagram 1/2

• It is called Fish-Bone Diagram due to the shape
  of the completed structure.
• This was proposed by Kaoru Ishikawa in the
  1960s,hence also referred as Ishikawa Diagram
• The Ishikawa diagram shows the causes of a
  certain event. A common use of the Ishikawa
  diagram is in product design, to identify
  potential factors causing an overall effect
• It shows the relation between a quality
  characteristics and factors
• Causes in the diagram are often based on a
  certain set of causes, such as the 5M1E,8 P's or
  4 S's
• Cause-and-effect diagrams can reveal key
  relationships among various variables, and the
  possible causes provide additional insight into
  process behaviour.

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Cause Effect Diagram 2/2

• Causes in a typical diagram are normally grouped
  into categories, the main ones of which are
• The 5M1E- recommended for the manufacturing
  industry
• Machine, Method, Materials, Measurement, Men and
  Environment
• The 8 P's - recommended for the administration
  and service industries
• Price, Promotion, People, Processes, Place /
  Plant, Policies, Procedures, and Product (or
  Service)
• The 4 S's - recommended for the service industry
• Surroundings, Suppliers, Systems, Skills
• Causes should be specific, measurable, and
  controllable derived from brainstorming sessions.
  Then causes should be sorted through
  affinity-grouping to collect similar ideas
  together. These groups should then be labeled as
  categories of the fishbone.

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Structure of Cause-and-effect Diagram
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Procedure for making CE diagram

• STEP 1
• Determine the Pain point/ characteristic
• STEP 2
• Draw in the backbone from left to right, and
  enclose the characteristic in a square
• Next, write the primary causes which affect the
  characteristics as big bones also enclosed by
  squares
• STEP 3
• Write the causes (Secondary Causes) which affect
  the big bones (Primary Causes) as medium sized
  bones
• Write the causes (Territory Causes) which affect
  the medium sized bones as small bones.

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Conti

• STEP 4
• Assign an importance to each factor, and mark
  the particularly important factors that seem to
  have a significant effect on the quality
  characteristics.
• STEP 5
• Record any necessary information

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Example of CE Analysis
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Histogram 1/2

• Histogram is a graphical technique to represent
  dispersion of data
• Ideally it will have symmetrical shape tapering
  away on both sides from target value
• For E.g
• Production from same production line usually
  differs slightly in dimensions, hardness, or
  others qualities
• when we commute to work every day, the time
  required varies from one day to other
• Thus , Histogram can be used to
• To find out if the lot has acceptance dispersion
• To compare with target value and specification
  limits to identify special causes of variation

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Histogram 2/2

• Histogram is a graph that represents the class
  frequencies by vertical adjacent rectangles in a
  frequency distribution.
• In a histogram, the magnitude of the class
  interval is plotted along the horizontal axis and
  the frequency on the vertical axis
• Since each class has lower and upper values,
  hence two equal vertical lines represent the
  frequency.
• Upper ends of the two lines representing the
  class interval are joined together. The height of
  rectangle thus obtained are proportional to their
  frequencies.

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Methodology for drawing Histogram
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• How to calculate frequency in Excel
• Select the cell
• Go to Formulas/More Functions/ Statistical/Freque
  ncy
• Select the Data Bin limits
• You will have the frequency
• 5. Select the cell range of FREQ equal
  to BIN LIMITS
• 6. Go to Formula Bar in Excel and press
  ctrlshiftenter
• 7. You will have FREQ for defined range

STUDENT BIN LIMITS FREQUENCY
A 47 0 0
B 45 5 0
C 78 10 0
D 82 15 0
E 89 20 0
F 45 25 0
G 55 30 0
H 65 35 1
I 58 40 0
J 68 45 2
K 52 50 2
L 57 55 3
M 89 60 4
N 35 65 4
O 65 70 2
P 58 75 1
Q 50 80 2
R 52 85 3
S 73 90 2
T 62 95 0
U 59 100 0
V 65
W 68
X 84
Y 82
Z 80
STUDENT
A 47
B 45
C 78
D 82
E 89
F 45
G 55
H 65
I 58
J 68
K 52
L 57
M 89
N 35
O 65
P 58
Q 50
R 52
S 73
T 62
U 59
V 65
W 68
X 84
Y 82
Z 80
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HISTOGRAM
3. Draw the Bar graph and set the limits. You
will have a histogram
Almost a TWIN PEAK Case
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Types of histograms
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Control Charts 1/2

• Variability is inherent in all manufacturing
  processes. These variations may be due to two
  causes
• i. Random / Chance causes (un-preventable)
• ii. Assignable causes (preventable)
• Control charts was developed by Dr. Walter A.
  Shewhart during 1920's while he was with Bell
  Telephone Laboratories.
• These charts separate out assignable causes.
• Control chart makes possible the diagnosis and
  correction of many production troubles and brings
  substantial improvements in the quality of the
  products and reduction of spoilage and rework.
• It tells us when to leave a process alone as well
  as when to take action to correct trouble

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Control Charts 2/2

• Control chart is a chart to examine whether a
  process is in a stable condition.
• The control limits are drawn for the process
  characteristics to be controlled.
• Data is of two types
• Variable - measured and expressed quantitatively
• Attribute - qualitative
• The elements of a control chart
• ?? - Mean is the average of a sub-group
• R - Range is the difference between the minimum
  and maximum in a sub-group
• 1. CL - Center line This is the expected mean
  of the process
• 2. UCL - Upper Control Limit and
• 3. LCL - Lower Control Limit
• These are limit to maximum expected variation of
  the process.

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Control Chart
Upper control line
Upper warning line
Target
Lower warning line
Lower control line
Lower control line
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Interpreting Control Chart
One point outside control limit
UCL
UWL
Statistics
LWL
LCL
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3
4
5
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7
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Sample Number
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Interpreting Control Chart
Two points out of three consecutive points
between warning limit and corresponding control
limit
UCL
UWL
Statistics
LWL
LCL
Sample Number
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Interpreting Control Chart
Two consecutive points between warning limit and
corresponding control limit
UCL
UWL
Statistics
LWL
LCL
Sample Number
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Interpreting Control Chart
Seven consecutive points on one side of the
centre line
UCL
UWL
Statistics
LWL
LCL
Sample Number
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Interpreting Control Chart
Seven consecutive points having upward trend
UCL
UWL
Statistics
LWL
LCL
Sample Number
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Interpreting Control Chart
Seven consecutive points having downward trend
UCL
UWL
Statistics
LWL
LCL
Sample Number
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Scatter Diagram 1/2

• A relationship may or may not exist between two
  variables
• If a relationship exists, it may be positive or
  negative, it may be strong or weak and may be
  simple or complex
• A tool to study the relationship between two
  variables is known as Scatter Diagram
• Examples
• The relationship between moisture content in
  threads and elongation.
• The relationship between an Ingredient and
  Product Hardness.
• The relationship between cutting speed and
  variations in the length of parts.

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Scatter Diagram 2/2

• The method consists of plotting the two series
  on a graph and fitting a Line of Best Fit free
  hand
• The direction of line shows the extent of
  correlation. If the line goes upward from left to
  right, it means the correlation is positive.
• If the line goes downward from left to right, it
  means the correlation is negative.
• If the points on the plot are scattered largely,
  it shows little or no correlation.
• Although Scatter Diagrams are very convenient
  tools for asserting two-way relationships, they
  dont provide formal measures of these
  relationships.
• Scatter Diagrams also dont provide any means of
  establishing whether any apparent associations
  are actually due to chance or not.

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How to draw scatter diagram
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1. Select the Sales Profit column and insert a
   Scatter chart
2. Add the axis label Trend line

Year Average Sales (Lac) Profits (Lac)
1987 168 66
1988 182 70
1989 192 76
1990 235 92
1991 304 117
1992 304 132
1993 333 147
1993 343 151
1994 423 159
1995 484 170
1996 553 188
1997 548 186
1998 589 204
1999 639 223
2000 661 234
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Strong Positive correlation
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Various plot patterns of scatter diagrams
Y
Y
Y
X
X
X
Positive correlation may be present
No correlation
Positive correlation
Y
Y
Y
X
X
X
Negative correlation may be present
Negative correlation present
Strong Curvilinear Association
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Flow chart 1/2

• Purpose
• Visual illustration of the sequence of operations
  required to complete a task
• To develop understanding of how a process is done
• To study a process for improvement
• To communicate to others how a process is done
• When better communication is needed between
  people involved with the same process
• To document a process
• When planning a project
• Benefits
• Identify process improvements
• Understand the process
• Shows duplicated effort and other non-value-added
  steps
• Clarify working relationships between people and
  organizations
• Target specific steps in the process for
  improvement.

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Flow chart 1/2

• Benefits
• Show what actually happens at each step in the
  process
• Show what happens when non-standard events occur
• Graphically display processes to identify
  redundancies and other wasted effort
• How is it done?
• Write the process step inside each symbol
• Connect the Symbols with arrows showing the
  direction of flow

Toolbox
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Check sheet

• WHAT IS A CHECK SHEET ?
• A Check Sheet is a method for collecting the
  right data in a simple manner.
• Classification of check sheets according to
  functions
• Recording check sheet
• (A) Defective Item Check Sheet
• (B) Defective Cause Check Sheet
• (C) Production process distribution Check Sheet
• 2. Inspection Check sheet
• (A) Check up Confirmation Check Sheet
• (B) Evaluation item inspection Check Sheet

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How to make check sheet

• Clearly indicate the purpose of the data
  collection
• Decide on how to collect data
• Estimate the total quantum of data
• Decide on the Check Sheet form
• Enter the data and draw up the Check Sheet.
• Check if it meet the objectives. Is it easy to
  record? If there are any improvement points,
  freely amend it.
• Reading and using the check sheet
• Read the whole picture
• To see the time series of time, day and month
• Tie-up the use of other tools

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Recording check sheet 1/2
1. Defective Item Check Sheet for a motor
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3. Production process distribution Check Sheet
Recording check sheet 2/2
2. Defective Cause Check Sheet
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Inspection Check sheet
1. Check up Confirmation Check Sheet
2. Evaluation item inspection Check Sheet
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To sum up 7 QC tools ,they are used to
Tools Result
Pareto Diagram To Identify the major cause/issue
Cause and Effect Diagram To identify the cause and effect relationship
Histogram To see the distribution of data
Control Charts To find out abnormalities and identify the current status
Scatter Diagrams To identify the relationship between two things
Flow chart illustration of the sequence of operations required to complete a task
Check Sheets To record data collection
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