7qc tools bb
TRANSCRIPT
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But …..Oh, my God! How do I do it fast and easily ???
I’m growing fat. I need to monitor my body weight for the next 6 months.
I want to include exercise in my daily activities and follow it up
I want to know the fat content of each
food item
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Don’t worry Tom., I am here to help
you.
I will you teach you some of the QC
tools…
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QC tools…What is that ? That is Quality
control tool. ( In your case it can be Quantity Control
tools)
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Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
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Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Check Sheet
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Module Objectives
This module will help you to understand
• Concept of Check Sheet
• Reason for using Check Sheet
• Types of Check Sheet
• Steps for creating a Check Sheet
- Check Sheet
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Reasons for using Check sheets
Check Sheet
Simplifies data collection
distinguishing
between
facts and opinions
To save time
To Have a clarity of
thoughts and data
To gain a better
understanding
Easy to
interpret
- Check Sheet
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Check sheet
The Check Sheet is a data-gathering and
interpretation tool
- Check Sheet
Month ,day
Component
1
2
3
4
5
6
7
8
9
10
4/1 2 3 4Month ,day
Component
1
2
3
4
5
6
7
8
9
10
4/1 2 3 4Month ,day
Component
1
2
3
4
5
6
7
8
9
10
4/1 2 3 4
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Measured Data
Measured Data
Check Sheet
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Types of Check Sheet
- Check Sheet
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Measured Data
Measured Data
Check Sheet
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Counted Data
Counted Data
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Types of Check Sheet
- Check Sheet
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Measured Data
Measured Data
Check Sheet
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Counted Data
Counted Data
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Primary Data
Primary Data
YES / NO or √√√√ / X - TypeYES / NO or √√√√ / X - Type
Types of Check Sheet
- Check Sheet
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Measured Data
Measured Data
Check Sheet
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Counted Data
Counted Data
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Primary Data
Primary Data
YES / NO or √√√√ / X - TypeYES / NO or √√√√ / X - Type
Ordered Data
Ordered Data
1st, 2nd Order …Very Good, Good, No Good … - Type
1st, 2nd Order …Very Good, Good, No Good … - Type
Types of Check Sheet
- Check Sheet
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Measured Data
Measured Data
Check Sheet
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Counted Data
Counted Data
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Primary Data
Primary Data
YES / NO or √√√√ / X - TypeYES / NO or √√√√ / X - Type
Ordered Data
Ordered Data
1st, 2nd Order …Very Good, Good, No Good … - Type
1st, 2nd Order …Very Good, Good, No Good … - Type
Point Scale Data
Point Scale Data
1 Point, 2 Point …etc.
1 Point, 2 Point …etc.
Types of Check Sheet
- Check Sheet
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Measured Data
Measured Data
Counted Data
Counted Data
Primary Data
Primary Data
Point Scale Data
Point Scale Data
Ordered Data
Ordered Data
Indiscrete value such as height, weight, length, time & temp., Etc.Indiscrete value such as height, weight, length, time & temp., Etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
Discrete value such as no. Of recording errors, no. of Item sold
& Rejections etc.
YES / NO or √√√√ / X - TypeYES / NO or √√√√ / X - Type
1st, 2nd Order …Very Good, Good, No Good … - Type
1st, 2nd Order …Very Good, Good, No Good … - Type
1 Point, 2 Point …etc.
1 Point, 2 Point …etc.
Types of Check Sheet
- Check Sheet
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Problem solving stages for using Check Sheet
1 Problem
2 Observation
3 Analysis
4 Action
5 Check
6 Standardisation
7 Conclusion
Step no QC story step Can use Cannot use
…an
d th
is is
a che
ck sh
eet !
!!!
Check sheets can be used in all stages of Problem solving
- Check Sheet
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Steps to create a check sheet
Clarify the measurement objective
Create a form for collecting data
Collect the data
Tally the data
- Check Sheet
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Price
Mileage
Power
Style
Suspension
I want to
buy a bike
Clarify the measurement objective
- Check Sheet
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Yamaha Crux R TVS Centra Bajaj Caliber HH Passion +
Price
Mileage
Power
Style
Suspension
Total
Measure
Model
Create a form for collecting data
- Check Sheet
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Power
Yamaha Crux R 7.6/7500
TVS Centra 7.5/7500
Bajaj Caliber 9.5/8000
HH Passion + 7.5/8000
ModelPower
(bhp/RPM)
Yamaha Crux R 39120
TVS Centra 40470
Bajaj Caliber 42567
HH Passion + 43876
Model Price (Rs.,)
Price
Yamaha Crux R 60
TVS Centra 100
Bajaj Caliber 90
HH Passion + 75
ModelMileage
(Kmpl)
Mileag
e
Style
Yamaha Crux R Yes
TVS Centra Yes
Bajaj Caliber No
HH Passion + Yes
Model
Availability of
adjustable
suspension
Suspension
Yamaha Crux R
TVS Centra
Bajaj Caliber
HH Passion +
Model Style
Collect data
- Check Sheet
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Power
Yamaha Crux R 7.6/7500
TVS Centra 7.5/7500
Bajaj Caliber 9.5/8000
HH Passion + 7.5/8000
ModelPower
(bhp/RPM)
Yamaha Crux R 39120
TVS Centra 40470
Bajaj Caliber 42567
HH Passion + 43876
Model Price (Rs.,)
Price
Yamaha Crux R 60
TVS Centra 100
Bajaj Caliber 90
HH Passion + 75
ModelMileage
(Kmpl)
Mileage
Style
Yamaha Crux R Yes
TVS Centra Yes
Bajaj Caliber No
Model
Availability of
adjustable
suspension
Suspension
Yamaha Crux R
TVS Centra
Bajaj Caliber
HH Passion +
Model Style
Poin
t sca
le
Prim
ary
data
Mea
sure
d da
ta
Mea
sure
d da
ta
Mea
sure
d da
taCollect data
- Check Sheet
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Best Criteria
Price lower
Mileage higher
Power higher
Style higher
Suspension more
Measure
Model
Measure
1-5 Scale ( 1-worst 5-best)
Collect data
- Check Sheet
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Yamaha Crux R TVS Centra Bajaj Caliber HH Passion +
Price
Mileage
Power
Style
Suspension
Total
Measure
Model
Tally the data
Yamaha Crux R TVS Centra Bajaj Caliber HH Passion +
Price
Mileage
Power
Style
Suspension
Total
Measure
Model
16 21 17 15
- Check Sheet
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7QC TOOLSE1 E2 E1 E2 E1 E2 E1 E2
D1
D2
D1
D2
A2
C1 C2 C1 C2
B1
B2
A1
Other Examples of a Check Sheet – Multivariable chart
- Check Sheet
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Other Examples of a Check Sheet – Multivariable chart
< 110 cc > 110 cc Scooty Pep < 110 cc > 110 cc Scooty Pep
Sales
Profit
Sales
Profit
Domestic
Export
March April
Motor cycle Scooterettes Motor cycle Scooterettes
- Check Sheet
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Exercise:
There are five machines in a manufacturing cell. Among that
two machines are JH Step 4 passed and another 2 are Step
2 passed and one machine is step 1 passed.
Construct a check sheet to identify the factors which is
influencing the high scrap rate.
The cell is getting operated by 3 workmen in all the three
shifts, among them 2 are undergone cell specific training
The scrap cost of the component is high when it has
happened in the last operation and vice versa
- Check Sheet
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1 2 3
Cost
rangeTotal
Cost
range
ShiftTotal
Scrap data
OperatorLevel of
machine
Shift Shift Overall
Total
Cost
rangeTotalMachine
Traini
ng
given
Your check sheet can be like this …
- Check Sheet
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1 2 3
A Y 2 1 0
B N 2 2 1
C Y 5 7 9
A Y 1 2 1
B N 11 5 10
C Y 3 4 5
A Y 1 1 0
B N 22 58 45
C Y 6 8 12
A Y 2 1 2
B N 7 9 11
C Y 7 9 10
A Y 2 2 3
B N 1 6 8
C Y 8 9 7
Total 245 394 395
Step 4
Step1
Traini
ng
given
459
M5
M1
M2
M3
M4 Step 2
Step 2
1
2
3
44
5
1
2
3
4
5
76
5
10
32
171
92
90
1
2
3
84
85
9
30
87
64
55
10
22
201
ShiftTotal
Scrap data
29
OperatorLevel of
machine
Shift
Step 4
232
230
MachineCost
rangeTotal
Cost
range
Shift Overall
Total
Cost
rangeTotal
Your check sheet can be like this …
Step 1 machine is making more scrap
Operator without training is making
more scrap
- Check Sheet
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• The Check Sheet is a data-gathering and interpretation tool
• There are five data type Check Sheets
Measured data check sheets
Counted data check sheets
Primary data check sheets
Ordered data check sheets
Point scale data check sheets
• There are four steps to construct a check sheet
• Use of Multivariable chart for extensive data collection
Summary
- Check Sheet
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Pareto diagram
Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
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- Pareto Diagram
ent rl
200
150
100
50
0
100
80
60
40
20
0
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Module objectives
At the end of this session, you will be able to …
� Explain Pareto diagram and its usage
� Explain steps & construct pareto diagram
� Interpret Pareto diagram
- Pareto Diagram
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7QC TOOLSVilfredo Pareto (1848-1923) , an Italian economist
observed that 20% of the Italian people owned 80%
of their country's accumulated wealth.
Who or What is Pareto?
- Pareto Diagram
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Pareto’s Rule
A few causes lead to many defects Vital Few
Pareto's rule states that vital few causes (20% of the
causes) are responsible for a large percentage of the
effect (80% of the effects).
A Pareto diagram is a tool used to identify the vital few
causes and trivial many
- Pareto Diagram
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Steps for creating Pareto Diagram
1. Collect data
2. Arrange data in the descending order
3. Calculate the relative % for individual data
4. Calculate the cumulative % for individual data
5. Draw a graph with scales on both axis
6. Draw bar chart based on data
7. Using cumulative % data, draw cumulative curve
8. Identify the VITAL FEW (thumb rule > 70%)
- Pareto Diagram
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Step 1 : Data collection from check sheet
4Others14
6Information & Systems13
4Research & Development12
15Finance11
66Materials10
8Personnel9
5Stores8
1Manufacturing Planning7
2Factory production6
20Plant Maintenance5
45Marketing4
12Service3
2Quality 2
10Production Engineering 1
No. of calls registered in the period week 45 to 50.
DepartmentSl.No
Example : Identification of depts. contributing majority of telephone calls
- Pareto Diagram
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Step 2 : Arrange data in the descending order
Manufacturing Planning14
Factory production13
Quality12
Others11
Research & Development10
Stores9
Information Systems8
Personnel7
Production Engineering 6
Service5
Finance4
Plant Maintenance3
Marketing2
Materials1
DepartmentSl.No
200
1
2
2
4
4
5
6
8
10
12
15
20
45
66
Nos.
- Pareto Diagram
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200
1Manufacturing Planning14
2Factory production13
2Quality12
4Others11
4Research & Development10
5Stores9
6Information Systems8
8Personnel7
10Production Engineering 6
12Service5
15Finance4
20Plant Maintenance3
45Marketing2
66Materials1
Nos.DepartmentSl.No
100
0.5
1.0
1.0
2.0
2.0
2.5
3.0
4.0
5.0
6.0
7.5
10.0
22.5
33.0
Relative %
Step 3 : Calculate the relative % for individual
- Pareto Diagram
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100200
0.5
1.0
1.0
2.0
2.0
2.5
3.0
4.0
5.0
6.0
7.5
10.0
22.5
33.0
Relative %
1Manufacturing Planning14
2Factory production13
2Quality12
4Others11
4Research & Development10
5Stores9
6Information Systems8
8Personnel7
10Production Engineering 6
12Service5
15Finance4
20Plant Maintenance3
45Marketing2
66Materials1
Nos.DepartmentSl.No
100.0
99.5
98.5
97.5
95.5
93.5
91.0
88.0
84.0
79.0
73.0
65.5
55.5
33.0
Cumulative %
Step 4 : Calculate the cumulative % for individual
- Pareto Diagram
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25
50
75
100
125
150
175
200
Materials
Marketing
Plant Maintenance
Finance
Service
Production Engineering
Personnel
Information Systems
Stores
Research & Development
Others
Quality
Factory production
Manufacturing Planning
Dept
In nos
0
25
50
75
100
Cumulative %
Step 5 : Draw a graph with scales on both axis
- Pareto Diagram
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45
20 15 12 10 8 6 5 4 4 2 2 10
25
50
75
100
125
150
175
200
Materials
Marketing
Plant Maintenance
Finance
Service
Production Engineering
Personnel
Information Systems
Stores
Research & Development
Others
Quality
Factory production
Manufacturing Planning
Dept
In nos
0
25
50
75
100
Cumulative %
Step 6 : Draw bar chart based on data
- Pareto Diagram
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2015 12 10 8 6 5 4 4 2 2 1
66
55.5
65.5
73
79
8488
9193.5
95.597.5 98.5 99.5 100
33
0
25
50
75
100
125
150
175
200
Materials
Marketing
Plant
Maintenance
Finance
Service
Production
Engineering
Personnel
Information
Systems
Stores
Research &
Development
Others
Quality
Factory
production
Manufacturing
Planning
Dept
In nos
0
25
50
75
100
Cumulative %
66
55.5
65.5
73
79
8488
9193.5
95.597.5 98.5 99.5 100
3375
100
125
150
175
200
In nos
50
75
100
Cumulative %
Step 7 : Using cumulative % data, draw cumulative curve
- Pareto Diagram
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Now let’s construct the Pareto using Minitab…
- Pareto Diagram
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Enter Departmentdetails in column C1
Enter phone call details in column C2
Data entry sheet - Minitab
- Pareto Diagram
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Navigation details in MINITAB
Select Stat > Quality
tools > Pareto chart
- Pareto Diagram
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Select Chart defects table
Place cursor in labels in and select C1
Place cursor in Frequencies in and
select C2
Data entry to tables in MINITAB
- Pareto Diagram
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- Pareto Diagram
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Count
Percent
Department
Count 5 4 9
Percent 33.0 22.5 10.0 7.5 6.0 5.0
66
4.0 3.0 2.5 2.0 4.5
Cum % 33.0 55.5 65.5 73.0
45
79.0 84.0 88.0 91.0 93.5 95.5 100.0
20 15 12 10 8 6
Other
Others
Stores
Information & Systems
Personnel
Production Engineering
Service
Finance
Plant Maintenance
Marketing
Materials
200
150
100
50
0
100
80
60
40
20
0
Pareto Chart of Department
Graphical display in MINITAB
- Pareto Diagram
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Count
Percent
Department
Count 5 4 9
Percent 33.0 22.5 10.0 7.5 6.0 5.0
66
4.0 3.0 2.5 2.0 4.5
Cum % 33.0 55.5 65.5 73.0
45
79.0 84.0 88.0 91.0 93.5 95.5 100.0
20 15 12 10 8 6
Other
Others
Stores
Information & Systems
Personnel
Production Engineering
Service
Finance
Plant Maintenance
Marketing
Materials
200
150
100
50
0
100
80
60
40
20
0
Pareto Chart of Department
How do we interpret a Pareto Chart?
Draw horizontal line at cumulative 70% for effect
70 %
Draw vertical line from the intersection for vital few causes
Vital Few
- Pareto Diagram
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Exercises…
1. Tool setting time in Crankshaft cell
3. Breakdown hours of furnaces
2. Internal customer complaints of Engine assly.
Operation Sec
Keyway milling 2.4
Profile Grinding 1.5
Crankpin Hole Drilling 0.6
Fine Boring 0.6
Boss Grinding 0.6
Thread Rolling 0.2
Induction Hardening 0
CGCF 40
SQF 5.5
PHF 2.5
TF 1.5
Crank case 277
Cylinder complete 61
Cylinder head 45
Cover clutch 40
Let’s use
- Pareto Diagram
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Results…
What is your result?
2. Internal customer complaints of Engine assly.1. Tool setting time in Crankshaft cell
3. Breakdown hours of furnaces
- Pareto Diagram
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Summary
A few causes lead to many defectsPareto's 20:80 rule:
Count
Percent
Department
Count 5 4 9
Percent 33.0 22.5 10.0 7.5 6.0 5.0
66
4.0 3.0 2.5 2.0 4.5
Cum % 33.0 55.5 65.5 73.0
45
79.0 84.0 88.0 91.0 93.5 95.5 100.0
20 15 12 10 8 6
Other
Others
Stores
Information & Systems
Personnel
Production Engineering
Service
Finance
Plant Maintenance
Marketing
Materials
200
150
100
50
0
100
80
60
40
20
0
Pareto Chart of Department
A Pareto diagram is a tool used to identify the vital few causes
Vital Few
- Pareto Diagram
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Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Cause & Effect Diagram
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At the end of this module, you will be able to :
� Explain the usage of Cause and Effect diagram
� Construct a Cause and Effect diagram
Module objectives
- Cause & Effect Diagram
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What is a Cause and Effect diagram?
Example – Analysis of Poor Vehicle Mileage
A graphical tool that helps to identify, sort and display possible
causes of a problem or quality characteristics.
It is also called as ‘Ishikawa diagram’ or ‘Fishbone diagram’.
- Cause & Effect Diagram
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Why should we use a Cause and Effect diagram?
� Structured approach to determine the root causes of a problem
or quality characteristic
� Indicates possible causes of variation in a process
� Encourages group participation and utilizes group knowledge
� Identifies areas where data should be collected for further study
- Cause & Effect Diagram
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Step- by - step procedure
to construct a Cause and Effect diagram
- Cause & Effect Diagram
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Step 1 - Identify and clearly define the outcome or EFFECT
to be analyzed
� Decide on the effect to be examined. Effects are stated as particular quality
characteristics, problems resulting from work, planning objectives such as
• Poor mileage
• Higher scrap
• Delay in product development
• Lower customer conversion rates
� Remember, an effect may be positive (an objective) or negative (a problem),
depending upon the issue that’s being discussed.
e.g. Positive effect – Zero defect, 100% Service level
Negative effect – High engine noise, Low productivity
- Cause & Effect Diagram
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Effect:
- Cause & Effect Diagram
Poor Vehicle Mileage
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Step 2 – Draw the SPINE and create EFFECT BOX
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Spine
Effect box
- Cause & Effect Diagram
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Step 3 – Identify the main CAUSES contributing to the
effect being studied
� Establish the main causes, or categories, under which other possible causes are
listed. Commonly used categories are
• 4Ms - Men, Method, Material, Machinery
• 4Ps – Policies, Procedures, People, Plant
• Environment – significantly important 5th category
� Write the main categories above and below the spine
� Draw a box around each category label and use a diagonal line to form a
branch connecting the box to the spine.
- Cause & Effect Diagram
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Step 3 – Identify the main Causes contributing to the effect
being studied continued…
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Method Machine
MaterialMen
- Cause & Effect Diagram
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Step 4 – For each major factors, identify other specific
factors which may be the Causes of the Effect
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Method Machine
MaterialMen
Under inflated
tyres
Carburettor
adjustments
Use wrong
gears
Drive too
fast
Poor
maintenance
Poor driving
habits
Improper
lubrication
Wrong
Octane fuel
- Cause & Effect Diagram
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Step 5 – Identify increasing more detailed levels of causes
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Method Machine
MaterialMen
Under inflated
tyres
Carburettor
adjustments
Use wrong
gears
Drive too
fast
Poor
maintenance
Poor driving
habits
Improper
lubrication
Wrong
Octane fuel
Focus area
- Cause & Effect Diagram
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No oil change
Wrong oil
Don’t know right oil
No Owner’s Manual
Resource problem
Don’t know recommended octane
No Owner’s Manual
Level 1
Level 2
Level 3
Level 4Material
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Improper
lubrication
Wrong
Octane fuel
Step 5 – Identify increasing more detailed levels of causes
continued…
- Cause & Effect Diagram
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Step 5 – Identify increasing more detailed levels of causes
continued…
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Method Machine
MaterialMen
Under-inflated tyres
Carburettor
adjustments
Use wrong
gears
Drive too
fast
Poor
maintenance
Poor driving
habits
Improper
lubrication
Wrong
Octane fuel
No record of tyre pressure
Difficult air-stems
Too rich
Fuel mixUnskilled mechanic Poor design
Can’t hear engine
Impatience Poorhearing
Always late
No awareness
Money.
Poor trg
“When in Rome…”
No oil change
Wrong oil
Money
Don’t know right oil
Don’t know recommended
octane
No Owner’s Manual
Level 1
Level 2
Level 3
Level 4All the causes are not captured here due to space constraint on the screen.
No Owner’s
Manual
Done for all CAUSES
- Cause & Effect Diagram
677QC Tools
7QC TOOLS
Step 6 – Analyse the diagram
� Look at the balance of the diagram
• Thick cluster in a area indicates need for further study
• A main category having only a few specific causes may indicate a need for
further identification of causes
� Look for the causes that appear repeatedly. These may represent root causes
� Look for what you can measure in each cause so you can quantify the effects
of any changes you make
� Most importantly, identify and circle the causes that you can take action on
- Cause & Effect Diagram
687QC Tools
7QC TOOLS
Men Material
Poor Vehicle
Mileage
Poor Vehicle
Mileage
Method Machine
Under-inflated tyres
Carburettor
adjustments
Use wrong
gears
Drive too
fast
Poor
maintenance
Poor driving
habits
Improper
lubrication
Wrong
Octane fuel
No record of tyre pressure
Difficult air-stems
Too rich
Fuel mixUnskilled mechanic Poor design
Can’t hear engine
Impatience Poorhearing
Always late
No awareness
Money.
Poor trg
“When in Rome…”
No oil change
Wrong oil
Money.
Don’t know right oil
Don’t know recommended
octane
No Owner’s Manual
Level 1
Level 2
Level 3
Level 4All the causes are not captured here due to space constraint on the screen.
Step 6 – Analyse the diagram continued…
No Owner’s
Manual
- Cause & Effect Diagram
697QC Tools
7QC TOOLS
We may like to do cause-verification.
Prioritisation of causes identified in Cause and Effect diagram
Case 1 – Known causes with spec. limits.
Step 6 – Analyse the diagram continued…
- Cause & Effect Diagram
4M Cause Specification Investigation Analysis
Man No focused training Functionwise
trainingGeneric
No method to measure
operator's skills
Skill matrix for
each workmenNo skill matrix
No OJTPractical training
at genbaNo OJT
Workmen not trained in
specific jobs
Need based
training
Common
module given
MaterialModule content is
academic oriented
Content should be
specific need
based
Theory based
Method
707QC Tools
7QC TOOLS
Effort
Impact
High
High
Low
Low
High impact
Low effort
Prioritisation of causes identified in Cause and Effect diagram
Case 2 – Subjective causes
We may use Four-blocker method
Step 6 – Analyse the diagram continued…
- Cause & Effect Diagram
1 2
34
717QC Tools
7QC TOOLS
Step 6 – Analyse the diagram continued…
Prioritisation of causes identified in Cause and Effect diagram
Case 2 – Unknown causes appearing for the 1st time
Such causes need to the explored further
- Cause & Effect Diagram
727QC Tools
7QC TOOLS
Summary – Cause and Effect diagram
� A graphical tool that helps to identify, sort and display possible
causes of a problem or quality characteristics
� Structured approach to determine the root causes of a problem
Can you recall?Can you recall?
- Cause & Effect Diagram
737QC Tools
7QC TOOLSLate arrival of train
at station
Late arrival
of train
at station
Method Machine
MaterialMen
Group 3
Group 1 Group 2
Group 4
- Cause & Effect Diagram
Lets do an exercise on Cause & Effect Diagram
747QC Tools
7QC TOOLS
Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Graph & Control Charts
757QC Tools
7QC TOOLSGraphs
- Graph & Control Charts
767QC Tools
7QC TOOLS
Module Objectives
This module will help you to understand
• Concept for Graph
• Reasons for using Graphs
• Types of Graphs
• Construction and interpretation of Graphs
- Graph & Control Charts
777QC Tools
7QC TOOLS
Graph
Graph is a visual representation tool used for showing the
relationship between two or more variables
- Graph & Control Charts
787QC Tools
7QC TOOLS
Facilitate in understanding
the data
Quick and direct Easy to remember
Highlight most
important facts
Graph
- Graph & Control Charts
797QC Tools
7QC TOOLS
Types of Graphs
• Line graph
•Bar graph
• Pie chart
- Graph & Control Charts
40
45
42 42 42
43
807QC Tools
7QC TOOLS
Line graph
A line graph is a way to summarize how two or more
pieces of variables are related and how they vary
depending on one another
- Graph & Control Charts
40
45
42 42 42
43
817QC Tools
7QC TOOLS
Construction of line graph
Step no:1 - gathering data
• Data must be chronological or sequential form. (At least 25 or more
samples must be taken in order to get an accurate run chart)
Month Weight in Kg
Mar 55
Apr 57
May 58
Jun 60
Jul 62
Aug 63
Sep 62
Oct 61
Nov 61
- Graph & Control Charts
827QC Tools
7QC TOOLS
Construction of line graph
Month Weight in Kg
Mar 55
Apr 57
May 58
Jun 60
Jul 62
Aug 63
Sep 62
Oct 61
Nov 61
Step no:2 – organising the data
• Divide the data into two sets of variable – X and Y ( Dependant
variable as Y and independent variable as X )
X Y
- Graph & Control Charts
837QC Tools
7QC TOOLS
Step no:3 – charting the data
• Plot the y values versus the x values using an appropriate scale
that will make the points on the graph visible
• Construct a best fit line that passes through the points
Trend of weight over 9 months
55
5758
60
6263
6261
50
52
54
56
58
60
62
64
66
68
Mar Apr May Jun Jul Aug Sep Oct
Weight (grams)
Construction of line graph
- Graph & Control Charts
847QC Tools
7QC TOOLSUse of MINITAB to
Construct graphs
- Graph & Control Charts
857QC Tools
7QC TOOLS
General layout of MINITAB 14
New worksheet
Worksheet – Data entry in this region
- Graph & Control Charts
867QC Tools
7QC TOOLS
Various types of graphs in MINITAB
- Graph & Control Charts
877QC Tools
7QC TOOLS
Minitab - graphs
Scatter plot
Data
- Graph & Control Charts
887QC Tools
7QC TOOLS
Minitab - graphs
Types of plot
- Graph & Control Charts
897QC Tools
7QC TOOLS
Minitab - graphs
Select X & Y variable
- Graph & Control Charts
907QC Tools
7QC TOOLS
Minitab - graphs
Line graph
Options to modify the graph to get data
label
- Graph & Control Charts
917QC Tools
7QC TOOLS
Minitab - graphs
Window to get the data label in graph
- Graph & Control Charts
927QC Tools
7QC TOOLS
Month
Weight in Kg
NovSepJulMayMar
63
62
61
60
59
58
57
56
55
54
6161
62
63
62
60
58
57
55
Scatterplot of Weight in Kg vs Month
The Final Graph
Line graph of Weight vs Month
- Graph & Control Charts
937QC Tools
7QC TOOLS
Bar graph
Bar graphs are the tools to represent the data in
the form of bars to easily identify the trends and
patterns
- Graph & Control Charts
947QC Tools
7QC TOOLS
Types of Bar graph
• Clustered Bar graph
• Stacked Bar graph
0
10
20
30
40
50
60
1993 1994 1995 1996 1997 1998 1999 2000
Year
Number of police officers
0
10
20
30
40
50
60
1993 1994 1995 1996 1997 1998 1999 2000
Year
Number of police officers
Vertical
Horizontal
Vertical
Horizontal
• Simple Bar graphVertical
Horizontal
0
10
20
30
40
50
60
1993 1994 1995 1996 1997 1998 1999 2000
Year
Number of police officers
Simple Bar graph Clustered Bar graph Stacked Bar graph
- Graph & Control Charts
957QC Tools
7QC TOOLS
Characteristics of bar graphs
• Figure numbered and titled
• Bars of equal width
• Different shading or texture to represent different data sets
• Non-numerical variable on horizontal x-axis
• Labels and units included on x and y axes
• Even scales on axes
- Graph & Control Charts
967QC Tools
7QC TOOLS
To create bar graph in MINITAB
Bar chart option
- Graph & Control Charts
977QC Tools
7QC TOOLS
To create bar graph in MINITAB
Bar chart types selection
- Graph & Control Charts
987QC Tools
7QC TOOLS
To create bar graph in MINITAB
Selection of X & Y axis variable
- Graph & Control Charts
997QC Tools
7QC TOOLS
To create bar graph in MINITAB
Options to modify the graph to get
data label
- Graph & Control Charts
1007QC Tools
7QC TOOLS
Year
No., of Police officers
20001999199819971996199519941993
60
50
40
30
20
10
0
56
5149
4745
48
52
55
Chart of No., of Police officers vs Year
The Final Bar-Chart…..
- Graph & Control Charts
1017QC Tools
7QC TOOLS
To create clustered-bar graph in Minitab
- Graph & Control Charts
1027QC Tools
7QC TOOLS
To create clustered-bar graph in Minitab
- Graph & Control Charts
1037QC Tools
7QC TOOLS
Data
C1
2000
1999
1998
1997
1996
1995
1994
1993
North
West
East
No rth
West
East
North
West
East
North
West
East
North
West
East
North
West
East
No rth
West
East
North
West
East
60
50
40
30
20
10
0
10
32
55
12
33
52
15
35
48
14
42
45
18
52
47
15
45
49
12
42
51
10
32
56
The Final Clustered Bar-Chart…..
- Graph & Control Charts
1047QC Tools
7QC TOOLS
To create stacked bar graph in Minitab
- Graph & Control Charts
1057QC Tools
7QC TOOLS
To create clustered-bar graph in Minitab
- Graph & Control Charts
1067QC Tools
7QC TOOLSData
20001999199819971996199519941993
60
50
40
30
20
10
0
33
55
35
52
32
48
30
45
16
30
21
35
40
53
45
56
The Final Stacked Bar-Chart…..
- Graph & Control Charts
1077QC Tools
7QC TOOLS
Pie Chart
A pie chart is a circle graph divided into pieces, each
displaying the size of some related piece of information.
- Graph & Control Charts
1087QC Tools
7QC TOOLS
Types of Pie Chart
Plant-1 (0)
0%Plant-2 (3)
37%
Plant-3 (2)
24%
R & D (1)
13%
Sp. Wh (1)
13%
Plant 4
13%
Other
25%
• Simple Pie chart
• Pie of Pie chart
• Exploded Pie chart
• Bar of Pie chart
- Graph & Control Charts
1097QC Tools
7QC TOOLS
To create pie-chart in Minitab
name
variable
- Graph & Control Charts
1107QC Tools
7QC TOOLS
To create Pie-chart in Minitab
- Graph & Control Charts
1117QC Tools
7QC TOOLS55, 62.5%
Kerala11, 12.5%Andhra
22, 25.0%Tamilnadu
Category
Tamilnadu
Andhra
Kerala
Pie Chart of Quantity vs State
- Graph & Control Charts
1127QC Tools
7QC TOOLS
• Clearly define the information(s) you want to infer from the data
• Experiment with different types of graphs and select the most appropriate
• Plot the graph
• Infer from the graph
Nature of information needed Type of chart
To analyse the distribution
To compare items
To establish time series and to
determine the time frequency
To analyse relationship
Pie chart
Bar graph, Line graph
Bar graph, Line graph
Line graph
Change, rise, growth, increase, decrease,
decline, fluctuation Range, concentration,
Increase with, decrease with, vary with,
despite, correspond to, relate to
Share of, percent of the, smallest, the
majority of
Example
Ranking, larger than, smaller than, equal to
Guidelines for constructing a graph
- Graph & Control Charts
1137QC Tools
7QC TOOLS
A good graph should
• Be simple and uncluttered
• Have a title and labels
•Show the data without altering the message of the data
• Show accurately the facts
• Clearly shows any trends or differences in the data
- Graph & Control Charts
1147QC Tools
7QC TOOLS
Exercise:
Open the file : Exercise graph.mtw
Let us do some exercise in Minitab.
There are 8 columns in the Minitab
Try the data to draw line graphs, Bar chart and Pie
chart
- Graph & Control Charts
1157QC Tools
7QC TOOLS
Your graph may be like this …
Month
Scrap cost / Engine
NovSepJulMayMarJan
2.8
2.7
2.6
2.5
2.4
2.3
2.2
2.1
Line graph of Scrap cost / Engine vs Month
Name of state
Literacy rate %
MadhyapradeshKarnatakaAndhrapradeshKeralaTamilnadu
90
80
70
60
50
40
30
20
10
0
6566
72
83
68
Bar chart of Literacy rate % vs Name of state
8, 8.0%Foreign
8, 8.0%Science fiction
11, 11.0%Horror
14, 14.0%Drama
14, 14.0%Romance
18, 18.0%Action
27, 27.0%Comedy
Category
Horror
Science fiction
Foreign
Comedy
Action
Romance
Drama
Pie Chart of Number of movie vs Type of movie
Data
Month 1 JulJunMayAprMarFebJan
60
50
40
30
20
10
0
Variable
Weight Y
Weight Z
Stacked bar chart of Weight Y, Weight Z vs Month 1
- Graph & Control Charts
1167QC Tools
7QC TOOLS
• Graph is a visual representation tool used for
showing the relationship between two or more
variables
• Line graph, Bar graph and Pie chart are most
commonly used graphs
Summary
- Graph & Control Charts
1177QC Tools
7QC TOOLS
Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Histogram
HistogramHistogram
1187QC Tools
7QC TOOLS
At the end of this module, you will be able to :
� Explain the construction of a histogram
� Interpret output data from a histogram
� Construct a histogram using Minitab software
Module objectives
- Histogram
1197QC Tools
7QC TOOLS
What do we need to infer from this data?
Battery failure data for 56 Pep vehiclesBattery failure data for 56 Pep vehicles
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
- Histogram
1207QC Tools
7QC TOOLS
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
How do you find that?
We can use Histogram.
How the data looks like
Range of battery life
Mean of battery life
- Histogram
1217QC Tools
7QC TOOLS
Histogram
45
16
18
6
1
0
2
4
6
8
10
12
14
16
18
20
36-45 46-55 56-65 66-75 76-85 96-95
Marks obtained
Frequency
What is a histogram?
Example – Marks obtained by 50 students in a class
Range of
marks
No. of
students
A histogram is a graphical representation of frequency distribution of
data
Majority have scored
in-between 56-75
- Histogram
1227QC Tools
7QC TOOLS
� To display large amounts of data values in a relatively simple chart form
� To tell relative frequency of occurrence
� To understand the central tendency & spread of the data
� To understand overall distribution of the data
Where to use a histogram?
- Histogram
1237QC Tools
7QC TOOLS
Step- by - step procedure
to construct a histogram
- Histogram
1247QC Tools
7QC TOOLS
Example
Battery failure data for 56 Pep vehicles
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
- Histogram
1257QC Tools
7QC TOOLS
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
Vehicle
No.
Battery
life, days
1 60 15 187 29 263 43 174
2 37 16 121 30 352 44 145
3 32 17 297 31 290 45 309
4 163 18 134 32 316 46 152
5 230 19 331 33 283 47 338
6 300 20 261 34 304 48 270
7 265 21 220 35 264 49 424
8 166 22 389 36 319 50 313
9 78 23 129 37 287 51 273
10 196 24 278 38 252 52 321
11 194 25 355 39 143 53 369
12 115 26 286 40 359 54 256
13 182 27 249 41 267 55 293
14 294 28 294 42 156 56 270
Step 1 - Determine the range (R) of the data
Obtain the largest & smallest values from the data
Calculate the R = Largest value – Smallest value
Range = 424 – 32
Range = 392
Smallest
observed value
Largest
observed value
- Histogram
1267QC Tools
7QC TOOLS
Step 2 - Determine the class interval & interval breadth
of the data
where n is the total no. of observations
Class interval = n
Here, n = 56, therefore,
Class interval =
Class interval = 7.49 = 7, after rounding it off to nearest integer
56
Now , to determine class breadth,
Class breadth = R /
Class breadth = 392 / 7
Class breadth = 56
n
- Histogram
1277QC Tools
7QC TOOLS
Step 3 – Create table of upper & lower limits of
class-intervals
The lower limit of the first class-interval is the lowest observed value in the data.
i.e. Lower limit of the 1st class = 32
Upper limit = Lower limit + Class breadth
= 32 + 56
= 88
To determine the next class-interval, start from the next number i.e. 89
So, Lower limit of 2nd class = 89
Upper limit = 89 + 56 = 145
Similarly, we can decide the class limits for all 7 class-intervals…
- Histogram
1287QC Tools
7QC TOOLS
Step 3 – Create table of upper & lower limits of
class-intervals continued…
4283727
3713156
3142605
2592034
2021463
145892
88321
Upper limitLower limitClass interval
- Histogram
1297QC Tools
7QC TOOLS
Step 4 – Prepare frequency distribution table
How many pieces of data fall into each of the class?
56Total
4
6
9
5
22
8
2
IIII
IIII I
IIII IIII
IIII
IIII IIII IIII IIII II
IIII III
II
32 – 88
89 – 145
146 – 202
203 – 259
260 – 316
317- 373
374 – 430
1
2
3
4
5
6
7
FrequencyFrequency marksClass#
- Histogram
1307QC Tools
7QC TOOLS
Step 5 – Prepare a histogram [a bar graph] of class vs
frequency
Histogram - Battery failures [Pep]
46
9
5
22
8
2
0
5
10
15
20
25
32-88 89-145 146-202 203-259 216-316 317-373 374-430
No. of days of usage
No. of failures
Class
Frequency
Now, what do you interpret from this histogram?
- Histogram
1317QC Tools
7QC TOOLS
Introduction to few terms
Central tendency
Spread
Central tendency - A measure of location of the middle or the centre of a distribution
The mean is the most commonly used measure of central tendency
Spread or Dispersion - Describes how much the observations vary around the
central tendency
A histogram
- Histogram
1327QC Tools
7QC TOOLS
What do you interpret from this histogram?
Histogram - Battery failures [Pep]
46
9
5
22
8
2
0
5
10
15
20
25
32-88 89-145 146-202 203-259 216-316 317-373 374-430
No. of days of usage
No. of failures
Class
Frequency
1. It appears to be a bell-shaped distribution
2. Most of the battery failures seem to occur for the the period of
216 – 316 days of usage.i.e. Central tendency is at 216-316 days
3. The spread appears to be higher
Period with maximum no. of
failures
Maximum failures
- Histogram
1337QC Tools
7QC TOOLS
Interpretations from histograms
Histogram may be interpreted by asking 3 questions:
1. Is the process performing within specification limits?
2. Does the process seem to exhibit wide variation?
3. If action needs to be taken on the process, what action is appropriate?
The answer to these 3 questions lies in analyzing 3 characteristics of
the histogram.
- Histogram
1347QC Tools
7QC TOOLS
Interpretations from histograms continued…
1. Is the process performing within specification limits?
Analyse: How well is the histogram centered?
The centering of the data provides information on the process aim
about some mean or nominal value.
Process Data
Frequency
13.012.512.011.511.010.5
LSL USL
1
3
1
4
14
3
10
8
5
1
Process Capability of DiameterLSL
Target
Process
mean
- Histogram
USL
1357QC Tools
7QC TOOLS
2. Does the process seem to exhibit wide variation?
Analyse: How wide is the histogram?
Looking at histogram width defines the variability of
the process about the aim.
Interpretations from histograms continued…
Process Data
Frequency
13.012.512.011.511.0
LSL USL
22
7
10
12
10
2
3
2
Process Capability of Shaft dia
- Histogram
1367QC Tools
7QC TOOLS
3. If action needs to be taken on the process, what action is
appropriate?
Analyse:What is the shape of the histogram?
Interpretations from histograms continued…
Distribution other than normal indicates presence of special cause in the process
C9
Frequency
14121086420
12
10
8
6
4
2
0
1
00
111
0
22
3
6
5
10
12
6
Histogram of C9
Process Data
Frequency
13.012.512.011.511.0
22
7
10
12
10
2
3
2
Process Capability of Shaft diaNormal Non-
normal
- Histogram
1377QC Tools
7QC TOOLS
Depending upon the shape of the histogram
[i.e. distributions ], there are following types of histograms
1. Bell-shaped [normal]
2. Bi-modal [double-peaked]
3. Skewed
Interpretations from histograms continued…
- Histogram
1387QC Tools
7QC TOOLS
1. Bell-shaped [normal]
� Depicted by a bell-shaped curve
• most frequent measurement appears as center of distribution
• less frequent measurements taper gradually at both ends of
distribution
� Indicates that a process is running normally (only common causes are
present)
Example:Histogram - Cyld block failures - Victor
1
913
20
29
4238
6357
69
51 5257 59
4541
3833 32
16 14 13 14
40 0 0 0 1
0
10
20
30
40
50
60
70
80
725 4666 8606 12547 16487 20428 24368 28309 32249 36190
Kilometer of usage
No. of failures
Interpretations from histograms continued…
- Histogram
1397QC Tools
7QC TOOLS
2. Bi-modal [double-peaked]
� Distribution appears to have two peaks
� May indicate that data from more than one process are mixed together
• Materials may come from two separate vendors
• Samples may have come from two separate machines
Example: Histogram - Fork Gear-shift - Bore finish
1
4
8
5
9
3
0
2
4
6
8
10
0.1 0.17 0.24 0.31 0.38 More
RaFrequency
Interpretations from histograms continued…
- Histogram
1407QC Tools
7QC TOOLS
3. Skewed
� Appears as an uneven curve; values seem to taper to one side.
Example:
� Here most of the values lies in the lower part of the values of histogram
3A. Positively Skewed
Histogram - No. of trucks halted
81
125 4
0
20
40
60
80
100
0-24 25-48 49-72 72-96
Hrs of waiting
No. of trucks
Interpretations from histograms continued…
- Histogram
1417QC Tools
7QC TOOLSHistogram - Wheel-rim - Runout
1
6
21 22
0
5
10
15
20
25
0.94 1.02 1.09 More
Runout, mm
Frequency
� Here most of the values lies in the upper part of the values of histogram
3B. Negatively Skewed
Example:
3. Skewed
� Appears as an uneven curve; values seem to taper to one side.
Interpretations from histograms continued…
- Histogram
1427QC Tools
7QC TOOLS
General Rule for Constructing a Histogram
Number of samples
For the histogram to be representative of the true process
behavior, as a general rule, 30 to 50 samples should be
measured.
- Histogram
1437QC Tools
7QC TOOLS
Construction of a histogram using MINITAB software
- Histogram
1447QC Tools
7QC TOOLS
Start MINITAB This is the first screen of MINITAB
Here is the place for your data
Sessionwindow
- Histogram
1457QC Tools
7QC TOOLSEnter the data in a column,
say, C2
Enter the data
- Histogram
1467QC Tools
7QC TOOLS
Go to Graph Histogram
Draw histogram
- Histogram
1477QC Tools
7QC TOOLS
Select the type “With Fit…”
Draw histogram continued...
- Histogram
1487QC Tools
7QC TOOLSClick Select to select the column C2
C2 appears here
Click OK
Draw histogram continued...
- Histogram
1497QC Tools
7QC TOOLS
Here is the histogram
Draw histogram continued...
- Histogram
1507QC Tools
7QC TOOLS
Histogram
� A histogram is a graphical representation of frequency distribution of
data
� Histogram is used to understand
• Central tendency
• Spread
• Overall distribution
� Different types of histogram are -
• Bell-shaped [normal]
• Bi-modal [double-peaked]
• Skewed
Can you recall?Can you recall?
Summary - Histogram
- Histogram
1517QC Tools
7QC TOOLS55 56 61 58 60
66 56 71 48 52
57 56 62 66 61
58 63 67 61 60
55 65 54 55 60
38 54 62 61 61
59 67 57 59 61
61 59 55 62 57
55 59 62 58 60
56 63 64 55 51
Marks
56 45 66
38 35 34
73 37 49
55 69 53
50 32 50
43 50 62
53 67 57
50 50 46
59 67 62
49 45 51
Test scores
47 19 6 40 11
85 17 60 129 69
23 11 41 53 45
47 10 13 86 11
49 44 87 59 28
21 18 88 74 60
44 113 13 44 27
38 45 7 41 152
9 22 37 101 47
252 14 45 90 90
Data
46 48 62 51 47
52 63 56 49 47
48 66 42 54 57
55 48 57 50 53
52 49 58 60 56
47 46 56 51 48
53 47 56 57 49
55 56 49 57 58
49 50 60 56 45
54 54 51 60 52
Data A
Example - 1 Example - 2 Example - 3 Example - 4
Draw Histogram for the following using Minitab application…
- Histogram
1527QC Tools
7QC TOOLSMarks
Frequency
7264564840
20
15
10
5
0
1
2
8
19
16
2
1
0
1
Histogram of Marks
Test scores
Frequency
7060504030
9
8
7
6
5
4
3
2
1
0
11
33
5
8
4
1
3
1
Histogram of Test scores
Data
Frequency
240180120600
20
15
10
5
0
1
00
1
2
7
10
19
10
Histogram of Data
Data A
Frequency
6560555045
10
8
6
4
2
0
1
2
3
7
9
6
10
8
3
1
Histogram of Data A
Solution - 1
Solution - 4
Solution - 2
Solution - 3
Answers
Appears normally distributed
Appears normally distributed with wide variation
Appears + vely skewed Appears to be a bi-
modal distribution
- Histogram
1537QC Tools
7QC TOOLS
Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Scatter Diagram
Temperature
35302520151050
110
100
90
80
70
60
50
40
30
20
Scatterplot of No of ice creams sold vs Temperature
1547QC Tools
7QC TOOLS
Module objectives
At the end of this session, you will be able to …
� Explain Scatter diagram and its usage
� Explain steps & construct Scatter diagram
� Interpret Scatter diagram
- Scatter Diagram
1557QC Tools
7QC TOOLS
To know kinds of relationships between variables, Scatter
diagram was developed
Sir Francis Galton (1822-1911), by using the theory of linear
regression developed Scatter diagram.
Why Scatter diagram was developed?
- Scatter Diagram
1567QC Tools
7QC TOOLS
It is a visual display of data which shows the association
between two variables acting continuously on the same item.
What is Scatter diagram?
It illustrates the strength of the correlation between the
variables through the slope of a line.
- Scatter Diagram
1577QC Tools
7QC TOOLS
Step 1. Collect at least 20-30 paired data points: "paired" data are
measures of both the cause being tested and its supposed effect at one
point in time
Step 2. Draw a graph, with the "cause" on the horizontal axis and the
"effect" on the vertical axis.
Step 3. Determine the lowest and highest value of each variable and mark
the axes accordingly.
Step 4. Plot the paired points on the diagram. If there are multiple pairs
with the same value, draw as many circles around the point as there are
additional pairs with those same values.
Step 5. Identify and classify the pattern of association using the graphs
below of possible shapes and interpretations.
Steps for creating a Scatter Diagram
- Scatter Diagram
1587QC Tools
7QC TOOLS
Example : No. of ice cream sold against atmospheric temp.
Sno Temperature
Number of Ice-
Creams sold Sno Temperature
Number of
Ice-Creams
sold
1 21 70 17 12 44
2 26 86 18 32 105
3 15 50 19 20 56
4 24 80 20 27 92
5 18 58 21 23 74
6 29 96 22 31 102
7 20 56 23 33 106
8 27 92 24 11 42
9 23 74 25 34 106
10 17 54 26 35 107
11 30 100 27 10 39
12 19 62 28 5 30
13 14 48 29 8 35
14 13 46 30 3 25
15 16 52 31 2 22
16 28 94 32 6 32
Collection of paired data
- Scatter Diagram
1597QC Tools
7QC TOOLS
Draw the graph
Outside temperature
No of ice creams sold
In this example,
Temperature (cause) will be indicated by X (horizontal axis) and
Number of Ice-cream sold (Effect) by Y (vertical axis).
- Scatter Diagram
1607QC Tools
7QC TOOLS
10 20 30 40 50
20
40
60
80
100
120
Outside temperature
No of ice creams sold
Mark the axes based on lowest and highest values
Highest value in temperature – 35
Highest value in Number of Ice-cream sold - 107
- Scatter Diagram
1617QC Tools
7QC TOOLS
10 20 30 40 50
20
40
60
80
100
120
Outside temperature
No of ice creams sold
Plot the dataSno Temperature
Number of Ice-
Creams sold Sno Temperature
Number of
Ice-Creams
sold
1 21 70 17 12 44
2 26 86 18 32 105
3 15 50 19 20 56
4 24 80 20 27 92
5 18 58 21 23 74
6 29 96 22 31 102
7 20 56 23 33 106
8 27 92 24 11 42
9 23 74 25 34 106
10 17 54 26 35 107
11 30 100 27 10 39
12 19 62 28 5 30
13 14 48 29 8 35
14 13 46 30 3 25
15 16 52 31 2 22
16 28 94 32 6 32
- Scatter Diagram
1627QC Tools
7QC TOOLS
10 20 30 40 50
20
40
60
80
100
120
Outside temperature
No of ice creams sold
Identify and classify the pattern
- Scatter Diagram
1637QC Tools
7QC TOOLS
Now let’s construct the Scatter using Minitab…
- Scatter Diagram
1647QC Tools
7QC TOOLS
Enter Temperature values in column C1
Enter No of ice creams sold in column C2
- Scatter Diagram
1657QC Tools
7QC TOOLS
Select Graph > Scatter
plot
- Scatter Diagram
1667QC Tools
7QC TOOLSClick OK
Select with Regression
- Scatter Diagram
1677QC Tools
7QC TOOLS
Select C1 - X variables
Select C2 - Y variables
- Scatter Diagram
1687QC Tools
7QC TOOLSClick OK
- Scatter Diagram
1697QC Tools
7QC TOOLSTemperature
No of ice creams sold
35302520151050
110
100
90
80
70
60
50
40
30
20
Scatterplot of No of ice creams sold vs Temperature
- Scatter Diagram
1707QC Tools
7QC TOOLSTemperature
No of ice creams sold
35302520151050
110
100
90
80
70
60
50
40
30
20
Scatterplot of No of ice creams sold vs Temperature
How do we interpret this Scatter diagram ?
• Strong relationship between the two variables : If most
of the points fall along an imaginary straight line with either
a positive or negative slope
• No relationship between the two variables : If points are
randomly scattered about the graph
- Scatter Diagram
1717QC Tools
7QC TOOLSTemperature
No of ice creams sold
35302520151050
110
100
90
80
70
60
50
40
30
20
Scatterplot of No of ice creams sold vs Temperature
Strong relation
Interpretation
Scatter diagrams show relationships, but do not
prove that one variable causes the other
- Scatter Diagram
1727QC Tools
7QC TOOLS0
5
10
15
20
25
30
35
0 5 10 15 20
0
50
100
150
200
250
300
350
0 100 200 300 400
Strong Positive correlation Strong Negative correlation
Types of Scatter Diagram
- Scatter Diagram
1737QC Tools
7QC TOOLSWeak Positive correlation Weak Negative correlation
0
10
20
30
40
0 5 10 15 20
0
100
200
300
400
500
0 100 200 300 400
Types of Scatter Diagram
- Scatter Diagram
1747QC Tools
7QC TOOLS0
100
200
300
400
500
600
700
0 100 200 300 400
No correlation
Types of Scatter Diagram
- Scatter Diagram
1757QC Tools
7QC TOOLSJ-shaped /Non linear association
Suggests complex relationships
Types of Scatter Diagram
- Scatter Diagram
1767QC Tools
7QC TOOLS
No of
Vehicles
Consumable
cost/vehicle
62598 23.9
50614 33.1
35148 45.0
44932 30.6
43669 14.0
26419 42.9
18712 36.8
24466 65.7
30520 55.0
30166 59.2
36100 47.8
39766 40.1
No. of
Engines/m
onth
Power
consumption
/Engine
75349 2.67
81281 2.75
82298 2.66
90763 2.25
93386 2.3
96376 1.7
90361 2
92467 1.8
1. Consumable
cost Vs No. of
Vehicles
2. Compressor
power consump.
Vs No. of Eng.
3. Pressing load Vs interference between hole &
shaft
0.11 2779
0.101 2229
0.106 2421
0.11 2446
0.11 2480
0.107 2563
0.101 2177
0.103 2325
0.099 2185
0.104 2305
PRESSING LOAD
(Kg)
INTERFEREN
CE
Let’s use
Exercises…
- Scatter Diagram
1777QC Tools
7QC TOOLS
Results…
1. Consumable cost Vs No.
of Vehicles
2. Compressor power
consumption Vs No. of Eng.
Weak negative
correlation
Weak negative
correlation
What is your result?
3. Pressing load Vs interference between hole &
shaft
Strong positive
correlation
- Scatter Diagram
1787QC Tools
7QC TOOLS
Summary
It is a visual display of two variables acting continuously on the same item.
Scatter diagram
0
20
40
60
80
100
120
0 10 20 30 40
Outside TemperatureNumber of ice-cream
sold
It illustrates the strength of the correlation between the variables
0
5
10
15
20
25
30
35
0 5 10 15 20
Strong positive
0
50
100
150
200
250
300
350
0 100 200 300 400
Strong Negative
0
10
20
30
40
0 5 10 15 20
Weak positive
0
100
200
300
400
500
0 100 200 300 400
Weak Negative
0
100
200
300
400
500
600
700
0 100 200 300 400
No relation
It show relationships, but do not prove that one variable causes the other
- Scatter Diagram
1797QC Tools
7QC TOOLS
Check Sheet
Pareto Diagram
Cause & Effect diagram
Stratification
Scatter Diagram
Graphs
Histogram
7 QC Tools
- Stratification
1807QC Tools
7QC TOOLS
Stratification is the act of fine tuning the data in order to
make sure of the significance of the assured factors, to the
grass root level.
Stratification
- Stratification
1817QC Tools
7QC TOOLSRep.acct. – Operator not reporting back to duty
for more than 48hrs
Non-reportable acct. – Operator disablement extending
beyond the day of shift but less than
48 hrs
Hosur Mysore
2000-04 2001-04
Reportable accident 47 17
Non reportable accident 179 92
Mandays lost 1476 510
Accident data
Description
- Stratification
1827QC Tools
7QC TOOLS
Plant No., of accidents Unit Category
Others
42
108
42
108
44
Plant 1
Plant 2
Plant 3
Plant 4
R&D - 16,Sp.WH - 8,Canteen -
10,Civil - 5,SC.Y - 1E.WH-
2,PED - 1,TQC - 1,
Reg - 16,Contractor -
12,Temp.workman - 14,
Supplier- 0, Visitor -0
Reg - 43,Contractor -
22,Temp.workman - 41,
Supplier- 1, Visitor -1
Reg - 16,Contractor -
12,Temp.workman - 14,
Supplier- 0, Visitor -0
Reg - 49,Contractor -
16,Temp.workman - 43,
Supplier- 0, Visitor -0
Reg - 20,Contractor - 11,
Temp.workman - 13,
Supplier- 0, Visitor -0
Fab-15,Engine - 9,Painting -
11,Vehicle - 3,Stores - 4
Fab-25,Engine - 24,Painting -
16,Vehicle - 9,Stores - 20
,Plating - 14
M/C shop - 9,G/Shop -
17,HT/Plating - 8, Stores - 8
Fab-15,Engine - 30,Painting -
19,Vehicle - 15,Stores - 18
,Plating - 11
Accident data sheet
- Stratification
1837QC Tools
7QC TOOLS
Plant No. of accidents
Plant 1 42
Plant 2 108
Plant 3 42
Plant 4 108
Spares
Warehouse8
R&D 16
Canteen 10
Civil 5
Export
Warehouse2
Others 3
Accident data sheet
- Stratification
1847QC Tools
7QC TOOLS
According to plant
Plant wise
No of accidents
Others
Export ware house
Canteen
Civi l
Spare ware house
R & D
Plant 4
Plant 3
Plant 2
Plant 1
120
100
80
60
40
20
032
105
8
16
108
42
108
42
No of accidents
Plant
- Stratification
1857QC Tools
7QC TOOLS
� Similarly stratification can be done
� Unit wise
� Workmen category wise
� Shift wise
� Phenomena wise
� Machine/equipment wise
� and so on…
1867QC Tools
7QC TOOLS
Other Stratification methodologies
- Stratification
1877QC Tools
7QC TOOLS
• Stratification is the act of fine tuning the data in order to
make sure of the significance of the assured factors, to
the grass root level
• Stratification helps to get more information from different
perspective from the same data
Summary
- Stratification
1887QC Tools
7QC TOOLS