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7QC Tools Q7T/PPT- 1 7 QC TOOLS 7 QC TOOLS

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Page 1: 7qc Tools Test

7QC Tools

Q7T/PPT- 1

7 QC TOOLS7 QC TOOLS

Page 2: 7qc Tools Test

7QC Tools

Q7T/PPT- 2

Types of 7QC toolsCheck SheetCheck Sheet

Pareto DiagramPareto Diagram

Cause & Effect diagramCause & Effect diagram

StratificationStratification

Scatter DiagramScatter Diagram

Graph &Control chartsGraph &Control charts

HistogramHistogram

7 QC Tools7 QC Tools

Types

Page 3: 7qc Tools Test

7QC Tools

Q7T/PPT- 3

Check sheetCheck sheetCheck sheet

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Q7T/PPT- 4

What is a check sheet?

Why is a check sheet necessary?

Check sheet

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Q7T/PPT- 5

Check sheets are forms used for

• standardizing

• checking results of work

• verifying and collecting data

Check sheet

Check sheet

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Q7T/PPT- 6

Check Sheet

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 - Type

YES / 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 SheetCheck sheet

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Q7T/PPT- 7

Defect check sheet

Check sheet

Example of check sheet

Month ,dayComponent

12345678

9

10

4/1 2 3 4

No. of No. of defectsdefects

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Q7T/PPT- 8

• Clarifying the objective• Determining the type of check sheet to

use• Deciding which items to check• Creating the check sheet• Recording the data• Tallying the data• Examining the check sheet

How to prepare check sheets?

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Q7T/PPT- 9

Below items can be added , as necessary

1. The purpose of the checks

2. The items being checked

3. The methods of the checks

4. The dates and times of the checks

5. The person to perform the checks

6. The results

Check points for check sheets preparationCheck sheet

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Q7T/PPT- 10

Pareto diagramPareto diagram

Pareto

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Q7T/PPT- 11

Do you remember this? (14th March 2001 - Eden gardens )

Pareto

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Q7T/PPT- 12

Do you remember this? (14th March 2001 - Eden gardens )

Pareto

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Q7T/PPT- 13

Now let’s look at the second innings score board:IndiaSS Das hit wicket b Gillespie 39S Ramesh c ME Waugh b Warne 30VVS Laxman c Ponting b McGrath 281SR Tendulkar c Gilchrist b Gillespie 10SC Ganguly c Gilchrist b McGrath 48R Dravid run out 180N R Mongia b McGrath 4Zaheer Khan not out 23Harbhajan Singh not out 8

Total 657

Pareto

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Q7T/PPT- 14

When we observe which batsmen got the maximum runs we can see that Laxman & Dravid got 461 out of the 657 runs. That is about 70% of the runs.

22% of the 9 batsmen who batted got 70% of the runs!

Let’s now observe the Australian 2nd innings score card

Pareto

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Q7T/PPT- 15

AustraliaM Hayden lbw b Tendulkar 67M Slater c Ganguly b Harbhajan 43J Langer c Ramesh b Harbhajan 28M Waugh lbw b Raju 0S Waugh c Sub B Harbhajan 24R Ponting c Das b Harbhajan 0A Gilchrist lbw b Tendulkar 0J Gillespie c Das b Harbhajan 6S Warne lbw b Tendulkar 0M Kasprowicz not out 13G McGrath lbw b Harbhajan 12

Total 212

Pareto

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Q7T/PPT- 16

Who got the wickets?

O M R W

Zaheer Khan 8 4 30 0

V Prasad 3 1 7 0

Harbhajan Singh 30.3 8 73 6

V Raju 15 3 58 1

S Tendulkar 11 3 31 3

S Ganguly 1 0 2 0

Pareto

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Q7T/PPT- 17

When we observe which bowlers got the maximum wickets we can see that Harbhajan & Tendulkar got 9 out of the 11 wickets. That is about 80% of the wickets.

30% of the 6 bowlers who bowled got 80% of the wickets!

This illustrates the Pareto principle

Pareto

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Q7T/PPT- 18

• Vilfredo Pareto was an Italian engineer in the 19th Century who studied the number of people in various income classes & declared

‘’20% of the people own 80% of the country’s wealth;

80% of the people own 20% of the country’s wealth”

Pareto

Pareto

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Q7T/PPT- 19

Pareto Principle

Pareto principle holds good to the present day in various applications

‘ A few causes lead to many defects;

many causes lead to few defects.’

The few causes that lead to many defects are the vital few.

The many causes that lead to few defects are the trivial many.

Pareto

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Q7T/PPT- 20

“Get to the biggest problems first”

‘Solve the vital few’

Pareto

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Q7T/PPT- 21

REMEMBER …The most frequent or most costly events are not always the most important.

e.g.Two fatal accidents deserve more attention than 100 cut fingers.

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Q7T/PPT- 22

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%)

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Pareto

Creating a Pareto Diagram

Steps

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Q7T/PPT- 23

Data collection through check sheetPeriod : Week No. 45 To 50No. Of External Phone Calls

4Others146Information & Systems134Research & Development1215Finance1166Materials108Personnel95Stores81Manufacturing Planning72Factory production620Plant Maintenance545Marketing412Service32Quality 210Production Engineering 1

No. Of cells regd.DepartmentSl.No

STEP 1 66

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Q7T/PPT- 24

200

1Manufacturing Planning142Factory production132Quality124Others114Research & Development105Stores96Information Systems88Personnel710Production Engineering 612Service515Finance420Plant Maintenance345Marketing266Materials1

No. Of cells reqd.DepartmentSl.No

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Pareto

STEP 2 Arrange data in the descending orderNo. Of External Phone Calls

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Q7T/PPT- 25

2000.51.01.02.02.02.53.04.05.06.07.510.022.533.0

Relative %

1Manufacturing Planning142Factory production132Quality124Others114Research & Development105Stores96Information Systems88Personnel710Production Engineering 612Service515Finance420Plant Maintenance345Marketing266Materials1

Nos.DepartmentSl.No

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Pareto

STEP 3 Calculate the relative % for individualNo. Of External Phone Calls

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Q7T/PPT- 26

100200100.099.598.597.595.593.591.088.084.079.073.065.555.533.0

Cumulative %

0.51.01.02.02.02.53.04.05.06.07.510.022.533.0

Relative %

1Manufacturing Planning142Factory production132Quality124Others114Research & Development105Stores96Information Systems88Personnel710Production Engineering 612Service515Finance420Plant Maintenance345Marketing266Materials1

Nos.DepartmentSl.No

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STEP 4 Calculate the cumulative % for individualData No. Of External Phone Calls

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Q7T/PPT- 27

100200100.099.598.597.595.593.591.088.084.079.073.065.555.533.0

Cumulative %

0.51.01.02.02.02.53.04.05.06.07.510.022.533.0

Relative %

1Manufacturing Planning142Factory production132Quality124Others114Research & Development105Stores96Information Systems88Personnel710Production Engineering 612Service515Finance420Plant Maintenance345Marketing266Materials1

Nos.DepartmentSl.No

TRIVIAL MANY

VITAL FEW

Pareto

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Q7T/PPT- 28

10020010073.065.555.533.0

Cumulative %

277.510.022.533.0

Relative %

60Others515Finance420Plant Maintenance345Marketing266Materials1

Nos.DepartmentSl.No

Pareto

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Q7T/PPT- 29

Pareto

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66

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Pareto

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70 %

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Q7T/PPT- 32

• To Clearly prioritise the magnitude of the problem.

• To identify the vital few and trivial many problems.

• To find 80/20 rule which states that 80% of the

problems are created by 20% of the causes.

Pareto

Why pareto ?

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Q7T/PPT- 33

Add examples from APC………..

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Q7T/PPT- 34

SL# D esc ription O ct '02 Nov '02 D ec '02 Jan '03 Total % D PU C um %1 Sec o n d Pass 520 710 73 759 2062 6 .38 75.972 D efec tive 68 227 22 14 331 1 .02 88. 1 63 B roken C om p 6 48 6 5 65 0 .20 90.564 M is inserted 1 22 1 7 31 0 . 1 0 91 . 705 Skewed C om p 6 14 1 3 24 0 .07 92.586 C om p M issing 15 0 0 4 1 9 0 .06 93.287 O ut of to le ranc e 8 7 0 4 1 9 0 .06 93.988 N o / Low so lder 8 9 0 1 1 8 0 .06 94.649 L ifted 7 2 0 4 1 3 0 .04 95. 1 2

10 Shorts 9 0 0 0 9 0 .03 95 .5Tested 8612 14314 1185 12859 36970P assed 7838 13219 1058 11978 34093 8 .4 8 .02

Q 4' 02 F inal failu re D etails

Q 4 F in a l F a i lu re D eta i ls

2062

331

65 31 24 19 19 18 13 9

75.97

88.16 90.56 91.70 92.58 93.28 93.98 94.64 95.12 95.5

0

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Q4 ‘02 Final Failure Details

Data Collection

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Q7T/PPT- 35

You have to cut down your house expenditure by 20% / month

How will you do it ?

Pareto

Same problem, but different approach…

ParetoPareto

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Q7T/PPT- 36

Make a check list of all the expenses in your home & the amount you

spend on these expenses

Pareto

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Q7T/PPT- 37

1300Petrol16

500Insurance Premium13

200Clothes15

300Others17

0Loan repayment14

200Hospital121500Educational11200Travel101500Entertainment & Lifestyle92000Groceries8150Maid servant7300Milkman6120News paper bill5210Cable TV Bill4280Water Bill3500Electricity Bill23000House Rent 1

AmountExpenseSl.No

Pareto

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Q7T/PPT- 38

Arrange these expenses & amounts in an order, with the highest

expense being the first & lowest expense being the last

Pareto

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Q7T/PPT- 39

150Maid servant15

120News paper16

300Others9

12260

0Loan repayment17

200Hospital14200Clothes13200Travel12210Cable TV11280Water bill10

300Milkman8500Insurance premium7500Electricity bill6

1300Petrol51500Educational41500Entertainment32000Groceries23000House rent1

AmountExpenseSl.No

Pareto

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Q7T/PPT- 40

Calculate the percentage contribution of each of these expenses.

Percentage can be calculated by the formula

Individual expense

Total expenseX 100

Pareto

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Q7T/PPT- 41

1.63200Hospital14

1.22150Maid servant15

0.98120Newspaper16

100122600

1.631.631.722.282.452.454.084.0810.6

12.2312.2316.3224.47

Relative %

0Loan repayment17

200Clothes13

200Travel12

210Cable TV11

280Water bill10

300Others9

300Milkman8

500Insurance premium7

500Electricity bill6

1300Petrol5

1500Educational4

1500Entertainment3

2000Groceries2

3000House rent1

Nos.DepartmentSl.No

Pareto

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Q7T/PPT- 42

1000.98120Newspaper16

99.021.22150Maid servant15

97.81.63200Hospital14

10010012260100.0

96.1794.5492.9191.1988.9186.4684.0179.9375.8565.2553.0240.7924.47

Cumulative %

0

1.631.631.722.282.452.454.084.0810.6

12.2312.2316.3224.47

Relative %

0Loan repayment17

200Clothes13

200Travel12

210Cable TV11

280Water bill10

300Others9

300Milkman8

500Insurance premium7

500Electricity bill6

1300Petrol5

1500Educational4

1500Entertainment3

2000Groceries2

3000House rent1

Nos.DepartmentSl.No

Pareto

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Q7T/PPT- 43

1000.98120Newspaper16

99.021.22150Maid servant15

97.81.63200Hospital14

10010012260100.0

96.1794.5492.9191.1988.9186.4684.0179.9375.8565.2553.0240.7924.47

Cumulative %

0

1.631.631.722.282.452.454.084.0810.6

12.2312.2316.3224.47

Relative %

0Loan repayment17

200Clothes13

200Travel12

210Cable TV11

280Water bill10

300Others9

300Milkman8

500Insurance premium7

500Electricity bill6

1300Petrol5

1500Educational4

1500Entertainment3

2000Groceries2

3000House rent1

Nos.DepartmentSl.No

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Q7T/PPT- 44

0

2000

4000

6000

8000

10000

12000

House R

ent

Grocerie

sEnte

rtainm

ent

Educa

tiona

l

Petrol

Others

Expenses

Amou

nt

0102030405060708090100

Cum

ulat

ive

%

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Q7T/PPT- 45

Cause & Effect Cause & Effect diagramdiagram

Cause & effect diagram

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Q7T/PPT- 46

• To identify and systematically list the different causes

that can be attributed to a problem (or an effect)

• To identify the reasons why a process goes out of

control

• To decide which causes to investigate for process

improvement.

Why Cause & Effect ?Cause & effect diagram

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Q7T/PPT- 47

What is Effect ?

EFFECT = A Result or an outcome

EFFECT is What happens

Cause & effect diagram

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Q7T/PPT- 48

What is cause ?

CAUSE = Reason or Factor contributing to the EFFECT

CAUSE is WHY it happens

Cause & effect diagram

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Q7T/PPT- 49

The analysis of “why?” for “what?”

is cause and effect diagram

Cause & effect diagram

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In 1953, Kaoru Ishikawa, Professor of the University of Tokyo, used the Cause & effect diagram for the first time.A cause & effect diagram is also called a fish bone diagram since it looks like the skeleton of a fish.

Cause & effect diagram

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Pareto chart

Cause-and-effect diagram

Cause & Effect diagram derived from pareto

Cause & effect diagram

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Steps of making cause & effect diagram

Cause & effect diagram

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Q7T/PPT- 53

Steps of making cause & effect diagramCause & effect diagram

Step 0 • Gather members for discussion • Clarify the problem to all members Step 1 • Conduct Brain storming session• List all possible causes Step 2

• Classify the causes into 4M • Draw Ist level Cause & Effect diagramStep 3 • Delete irrelavant causes Step 4• Assign importance factor to the remaining causesStep 5 • Conduct why why analysis if required to find root causes

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Q7T/PPT- 54

Cause & effect diagram

Step 1

List all the causes that have been suggested by team members as a part of brain storming.

What is brain storming ?

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Q7T/PPT- 55

Brainstorming is another tool which we use as a part of all the 7 QC tools

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Q7T/PPT- 56

BRAIN STORMING !

Brain storming

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Q7T/PPT- 57

BRAIN STORMING

Brain storming is a technique to obtain creative ideas from a group of persons in a shortest possible time

Brain storming plays an important role to build a cause and effect diagram

WHY To identify the problem - to identify the causes

To find solution - to prevent problem

Brain storming

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Q7T/PPT- 58

BRAIN STORMING

Brain storming can be conducted in two ways

1. Structured

• Every person in a group must give an idea as their turn arises.

• Forces even shy people to participate.

• Creates a certain amount of pressure to contribute.

Brain storming

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Q7T/PPT- 59

2. Unstructured

• Group members simply give ideas as they come to mind.

• Creates more relaxed atmosphere

• Risks domination.

Thumb rule : 5 – 15 minutes works well

Brain storming

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BRAIN STORMING SESSION• Let all the members speak freely and give ideas

• Encourage wild ideas

• “Quantity” rather than “Quality” ideas

• Suspend judgment on “Good” or “Bad”

• Ride on another’s ideas

• Never criticize other persons’ opinions

• Never prohibit a person from speaking

• See the problem from different angles/facets

• Write down all the viewpoints

• List the cause/ideas

• Think of the countermeasures to eliminate the causes

• Leader/facilitator need to guide the members in generating ideas

• Whenever necessary non – members can also be involved

Brain storming

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Q7T/PPT- 61

WHY BRAIN STORMING?

TO IDENTIFY THE PROBLEM

TO IDENTIFY CRITICAL CAUSES

TO FIND THE SOLUTION

TO PREVENT THE PROBLEM

Brain storming

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Q7T/PPT- 62

BENEFITS OF BRAIN STORMING?

Brain storming

• Individual is limited in generating ideas and that

group produces more ideas

• Ideas are improved upon by members

• Presence of others increases creativity

• Pooling of ideas and resources is made possible by

coming together as a group

• Individual is limited in generating ideas and that

group produces more ideas

• Ideas are improved upon by members

• Presence of others increases creativity

• Pooling of ideas and resources is made possible by

coming together as a group

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Q7T/PPT- 63

Cause & effect diagram

Step 2

Draw Cause & Effect diagram – Level 1

Classify the causes into 4M

Sort out the relations among the causes & connect the sub causes to the main causes. The main causes should then be connected to the effect.

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MATERIALMETHOD

MAN MACHINE

Sub cause

Sub-sub cause

CAUSES EFFECT

PROBLEM

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Cause & effect diagram

MACHINEMAN

MATERIAL METHOD

Fatigue

Dimensional Variation

Location

JIGS & FIXTURES

STABILITY

INSPECTION

Method

Attentiveness

SPIRIT

Experience

HEALTH

SKILL

Storage

QUALITY

Inspection

ShapeFORM

Dimension

Feed

WORKING

Spindle speed

Illness Training

ConcentrationInstrument

Clamping

Imbalance

Vibration

SETTING

Degree of tightening

Placement on locator

2

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Cause & effect diagram

Step 3

Delete irrelavant causes

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Cause & effect diagram

MACHINEMAN

MATERIAL METHOD

Fatigue

Dimensional Variation

Location

JIGS & FIXTURES

STABILITY

INSPECTION

Method

Attentiveness

SPIRIT

Experience

HEALTH

SKILL

Storage

QUALITY

Inspection

ShapeFORM

Dimension

Feed

WORKING

Spindle speed

Illness Training

ConcentrationInstrument

Clamping

Imbalance

Vibration

SETTING

Degree of tightening

Placement on locator

2

The EFFECT or PROBLEM is stated on the right side of the diagramand the major INFLUENCES or CAUSES are listed to the left.

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Cause & effect diagram

Step 4

Evaluate the siginificance of each cause to the problem and assign importance factor

Assign an importance to each factor, & mark the particularly important factors which seem to have a significant effect.

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Cause Verification

4M Cause Specification Investigation Analysis

Man No focused training Functionwise training

Generic

No method to measure operator's skills

Skill matrix for each workmen

No skill matrix

No OJTPractical training at genba

No 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

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Cause & effect diagram

Step 5

Do why why analysis for the significant causes

Atleast ask why 3 times

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Why defects?

D

People

1st Why

Plant

PoliciesProcedure

5th Why

C

3rd Why

4th Why

Thorough investigation of causes

2nd Why

Cause & effect diagram

ASK WHY? 5 TIMES

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Examples :- Cylinder does not operate smoothly

Why Answer ActionWhy is opertion not smooth? Strainer clogged. Clean strainer.Why has strainer clogged? Oil was dirty. Drain oil and clean.Why did oil get dirty? Dirt enters tank. Prevent scattering of chips and cutting fluidWhy does dirt get in? Upper plate of tank has hole and gap. Plug hole and gap.Why was hole made? Repair error during maintenance work. Standardize repairs.

Phenomenon(Result)

Cause

Phenomenon(Result)

Cause

Cause

Phenomenon(Result)

Phenomenon(Result)

Primary Secondary

Tertier

‘WHY WHY’ Analysis

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Why Answer ActionDisassemble leaking part.

Why did it leak? Cut in O-ring. Replace O-ring.Why was it cut? Rod has scratch. Remove scratch.

Why was it scratched? Chip was scattered and attached on rod.

Take measure to prevent chips from scattering

Why did chips get attached? Cylinder is located within scattering range of chips. Change cylinder position

Rod cover is not placed. Install cover.Why is rod praced in that Why no cover?

Defective design and installation

Standardize design and installation.

- Oil leaks from cylinder rod each time it operates.

‘WHY WHY’ Analysis

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• Special effort should be made to identify as many

causes as possible

• The ideal method to identify as many causes as

possible would be by brainstorming with the team

members.

• All the ideas/causes suggested by members during

the brainstorming session should be noted however

insignificant they may initially appear. Brainstorming

is a session specially meant for free flow of ideas.

Cause & effect diagram

Guidelines

Remember

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MATERIALMETHOD

MAN MACHINE

Sub cause

Sub-sub cause

CAUSES EFFECT

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COPYING PAPERHANDLING

MACHINE PROCESS CONSUMABLES

Party removed

Dust accumulation

POOR QUALITY

OF XEROX COPIES

Paper shortage

Over consumption

Not using specified quality of paper

Non-standard

Non-standard

Supply from various sources

Wrong paper usage

Paper with stablesLack of knowledge

Not understanding the defect codes/ communicating defects

Nominated persons not handling

Paper jam not cleared properly

Untrained personnel handling the machine

Limited machines

Heavy usage

No cleaning

Location

Frequentchanges Serviced by

unauthorized personsImproper service

No periodical service

No stabilizer

Power

High fluctuation

No communication

Specified toner not filled

Lack of knowledge

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Effect

Causes

1

Cause & effect diagram

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A combination of Pareto diagram & cause and effect diagram is an ideal way to arrive at the main problem & its causes.

Take the biggest problem from the pareto diagram & put it on the right side in the cause & effect diagram.

Derive the causes for the same.

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Examples from APC………..

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Data Mixed process& Original

MANMAN

METHODMETHOD MATERIALMATERIAL

MACHINEMACHINE

PROCESS PROCESS

SCRAPSCRAP

Scrap Disposal Training/Procedure is inadequate

Machine rejectionsare high.

No process flow

Improper Handling

Handling Pro not defined.

Incoming material.

Improper Storage

Improper /Movement

High Rej in M/C.

Improper StorageIn racks .

No Awareness

Inadequate Training

Improper tools

Program /Nozzleerror

No plan forFeeder maintenance

Identification and SegregationNot done.

No Alarms for M/C Board Jam.

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Data Mixed process& Original

MANMAN

METHODMETHOD MATERIALMATERIAL

MACHINEMACHINE

PROCESS PROCESS

SCRAPSCRAP

Scrap Disposal Training/Procedure is inadequate

Machine rejectionsare high.

No process flow

Improper Handling

Handling Pro not defined.

Incoming material.

Improper Storage

Improper /Movement

High Rej in M/C.

Improper StorageIn racks .

No Awareness

Inadequate Training

Improper tools

Program /Nozzleerror

No plan forFeeder maintenance

Identification and SegregationNot done.

No Alarms for M/C Board Jam.

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LowProductivity

MAN

MATERIAL

METHOD

MACHINE

High Rejection on plastic parts

Scratches

Flow & Black Mark

Printing Defect

Tab & radial BHS problem

GSM error Spindle up

Battery Charging

Operator Skill (Prep of Heat

sink)

Operator absenteeism

Imbalance flow of production

ICT Downtimes and Second pass

High DPU

M/c Cycle time improvement

High Touch up defects before ICT

IC-9 Screening

Serial Number Screening

Board Flow from Wave to ICT

Ishikawa Diagram

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StratificationStratification

Stratification

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Stratification

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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

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Why Stratification?

Stratification

To ascertain the difference between different

categories and to analyse the reasons behind

abnormal distribution.

To obtain clues for identifying the causes

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Case studyProblem : Increased Inventory

sheetsBarsTubesImportsProprietarypressingsFastenersRubberRubberBearings

Shop wiseAssy wiseSub-Assy wiseStage wiseMachine wiseRtRejections

Castings

Raw Material

Components

Work in process

Tubes

Proprietary

Fasteners

Bearings

Shop wise

Sub-Assy wise

TotalInventory

Stratification

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Case study 2

Problem : More No. of Accidents

Stratification

Let us stratify the the data regarding the accidents

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STATISTICSSTATISTICS

REPORTABLE ACCIDENTS REPORTABLE ACCIDENTS :: 08 08

NONNON--REPORTABLE ACCIDENTSREPORTABLE ACCIDENTS :: 3333

NEAR MISS INCIDENTSNEAR MISS INCIDENTS :: 2121

LOST TIME INJURIESLOST TIME INJURIES :: 4141

MANDAYS LOSTMANDAYS LOST : : 187187

Rep.acct.Rep.acct. –– Operator not reporting back to duty Operator not reporting back to duty for for more than 48hrsmore than 48hrs

NonNon--reportable acct.reportable acct. –– Operator disablement extending Operator disablement extending beyond beyond the day of shift but the day of shift but less than 48 hrsless than 48 hrs

Lost time injuryLost time injury –– Reportable + NonReportable + Non--reportablereportable

Stratification

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ANALYSIS ANALYSIS ––REPORTABLE ACCIDENTREPORTABLE ACCIDENT

Total no of reportable accident :Total no of reportable accident : 88

Stratification

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ACCORDING TO CATEGORYACCORDING TO CATEGORY

Temp.workman(3)

38%

Regular Employee (4)

49%

Contract Labour (1)

13%

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

Stratification

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ACCORDING TO PROBLEMACCORDING TO PROBLEM

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

0

0

0

0

0

0

0

2

6

0 1 2 3 4 5 6 7

wrong assembly

Contact with chemical

Fall from Two wheeler

Fall from Height

others

Hit by objects/Fallen objects

Hit against object

Wrong handling of material handlingequipment

Adjusting/Cleaning/Loading/Unloadingwhile M/C running

No of Accidents

Stratification

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Total no.of Reportable accidents : Total no.of Reportable accidents : 88

ACCORDING TO BODY PARTS INJUREDACCORDING TO BODY PARTS INJURED

Finger (5)62%

Hand (1)13%

Leg (2)25%

Stratification

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Plant-1 (0)0%

Plant-2 (3)37%

Plant-3 (2)24%

R & D (1)13%

Sp. Wh (1)13%

Others (1)13%

ACCORDING TO PLANTACCORDING TO PLANT

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

Stratification

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Total no.of Reportable accidents : Total no.of Reportable accidents : 88

ACCORDING TO UNITACCORDING TO UNIT

1 1 1

0 0 00

1

2

FAB ENG UNIT PAINT VECH UNIT STORES PLATING

No.o

f acc

iden

ts

PLANTPLANT-- 22

Stratification

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ACCORDING TO SHIFTACCORDING TO SHIFT

4

2 2

0 00

1

2

3

4

5

I II III GEN OT

No.o

f acc

iden

ts

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

Stratification

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ACCORDING TO MONTHACCORDING TO MONTH

0

3

0 0 0 0

2

0

1 1

0

1

0

1

2

3

4

APRIL

MAY

JUNE

JULY

AUGUST

SEPTEM

BER

OCTOBER

NOVEMBER

DECEM

BER

JANUARY

FEBRAUARY

MARCH

No.o

f acc

iden

ts

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

Stratification

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ACCORDING TO FAULTACCORDING TO FAULT

3

2

3

0

1

2

3

4

OPERATORS FAULT SUPERVISORY FAULT SYSTEM ANDENVIRONMENT FAULT

No.o

f acc

iden

ts

Total no.of Reportable accidents : Total no.of Reportable accidents : 88

Stratification

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The data has been stratified

1. According to employee category

2. According to phenomenon

3. According to body parts injured

4. According to plant

a. According to unit

5. According to shift

6. According to month

7. According to fault

Stratification

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Graph & Control charts

Graph&control charts

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Graph&control charts

GraphWhat is Graph?When there are more than 2 interrelated data sets,you writethe datasets on a graph so as to clearly define therelationships.

Why Graph? The details of the data should be• Correctly understood• In their entirety• With just a one look – Pictorial representation

A picture is worth of thousand words

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Graph&control charts

Types of Graphs & Its applicationBar graphs,line graphs, pie charts, and band graphs.There are also other specialty graphs such as radarcharts, Z charts and area graphs

Applications

To understand relative sizes of numbers

To understand trends over time

To understand percent-ages of totals

Graph

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Graph&control charts

Pie chart - Composition of sales turnover 2001-02

Vehicle sales92%

Export Sales1%

Spare parts sales

6%

Other income

1%

Pie charts are used to show percentages or proportions of different components of a specific item.

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Graph&control charts

Bar chart - Sales performance

1417 19 27

4162

83

104133

162184 194

262

0

50

100

150

200

250

300

90-91 91-92 92-93 93-94 94-95 95-96 96-97 97-98 98-99 99-00 00-01 '01-02 '02-03

Rs Million x 100Plan for 2002-03

Bar charts are used for comparing quantities between persons, regions, time intervals etc.

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Graph&control charts

Line chart - Hourly output of Workmen

40

45

42 42 42

43

37

38

39

40

41

42

43

44

45

46

Jan Feb Mar Apr May Jun

No.

of w

o rkm

en

Line graphs are used to depict change or variation over time.

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Graph&control charts

How to draw graphs?

• Select the type of chart or graph most suitable for the type of data.

• Decide the units and scale of items to be shown on X-axis and Y-axis

• Fill the information on the graph

• Join the required points to complete lines or bars.

• Colour or shade the lines or bars to distinguish between different groups or classes.

• Provide appropriate title.

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To add examples from APC

Histogram

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Productivity improvement

208

277246

278

370397

522

0

100

200

300

400

500

600

OCT NOV DEC JAN FEB MARCH APRILMonth

Uni

ts p

rodu

ced

/ Shi

ft

BeforeAfter

Results

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Results

DPU Trend for Cerror Torre

13.912.1 11.9

8.27.3 7.4

6.5

9.98.3

12

7.4

4.4 4.2 3.8

23.8

20.4

23.9

15.6

11.7 11.610.3

0

5

10

15

20

25

30

% D

PUICTFINALDPU

ICT 13.9 12.1 11.9 8.2 7.3 7.4 6.5FINAL 9.9 8.3 12 7.4 4.4 4.2 3.8DPU 23.8 20.4 23.9 15.6 11.7 11.6 10.3

OCT NOV DEC JAN FEB MAR APRIL

Before

After

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Southern chips Problem trend

April

25%

11%26%

16%

22%ScratchesPrinting missingCkt Brkr BrokenSleeve not putWire interchangeWire not connected

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Histogram

Histogram

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It shows the distribution of data

Histogram is an important diagnostic tool which gives a ‘Birds –eye-view’ of the variation in a data set. It is nothing but a frequency distribution chart.

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• In quality control, we try to discover facts by collecting data & then take necessary action based on those facts.

• The data is not collected as an end in itself, but as a means of finding out the facts behind the data.

Histogram

Data

FACTS

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• For example, consider a sampling inspection. We take a sample from a lot, carry out measurements on it, and then decide whether we should accept the whole lot or not. Here our concern is not the sample itself, but the quality of the whole lot.

The totality of items under consideration is called the population.

Histogram

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• The data obtained from a sample serves as a basis for a decision on the population.

• The larger the sample size is, the more information we get about the population.

• But an increase of sample size also means an increase in the amount of data

Histogram

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• It becomes difficult to understand the population from these data even when they are arranged into tables.

• In such a case we need a method which will enable us to understand the population at a glance.

A histogram answers our needs.

Histogram

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Histogram shows a bar chart of accumulated data and provides the easiest way to evaluate the distribution of data .The horizontal axis shows the values of the characteristics, with the region between the largest value and smallest value being broken into several smaller spaces. The sizes of the vertical bars reflects the number of data that fall into these spaces.

Histogram

What is histogram ?

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How to make a histogram?Let us make a histogram using an example.

Histogram

Example:

To investigate the distribution of the diameters of steel shafts produced in the grinding process, the diameters of 90 shafts are measured as shown in the table.

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SampleNumber1 - 10 2.51 2.517 2.522 2.522 2.51 2.511 2.519 2.532 2.543 2.52511 - 20 2.527 2.536 2.506 2.541 2.512 2.515 2.521 2.536 2.529 2.52421 - 30 2.529 2.523 2.523 2.523 2.519 2.528 2.543 2.538 2.518 2.53431 - 40 2.52 2.514 2.512 2.534 2.526 2.53 2.532 2.526 2.523 2.5241 - 50 2.535 2.523 2.526 2.525 2.532 2.522 2.502 2.53 2.522 2.51451 - 60 2.533 2.51 2.542 2.524 2.53 2.521 2.522 2.535 2.54 2.52861 - 70 2.525 2.515 2.52 2.519 2.526 2.527 2.522 2.542 2.54 2.52871 - 80 2.531 2.545 2.524 2.522 2.52 2.519 2.519 2.529 2.522 2.51381 - 90 2.518 2.527 2.511 2.519 2.531 2.527 2.529 2.528 2.519 2.521

Results of Measurement

Diameter after grinding

Histogram

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CONSTRUCTING A HISTOGRAM

STEPS

1. Collect data

2. Determine the largest value & smallest value

3. Obtain the range R (The range is the smallest value in the set of data subtracted from the largest value

4. Divide the range value in to certain number of classes referred to as K

5. Determine the class width, H = R / K

6. Divide the value of class boundary

7. Construct a frequency table, based on the values compiled

8. Construct Histogram based on the frequency table

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STEP 1 Collect data

CASE STUDYPeriod : wk no. 15 to 20Material : ms flange collarUOM : mmThickness : 9 mm + 1.5 mm

9.9 9.3 10.2 9.4 10.1 9.6 10.1 9.9 9.89.8 9.8 10.1 9.9 9.7 9.8 10.0 9.9 9.69.7 9.4 9.6 10.0 9.8 9.9 10.4 10.1 10.010.2 10.1 9.8 10.1 10.3 10.0 9.8 10.2 10.79.9 10.7 9.3 10.3 9.9 9.8 9.5 9.8 9.49.3 10.2 9.2 9.9 9.7 9.9 9.5 9.8 9.49.0 9.5 9.7 9.7 9.8 9.8 9.6 9.3 9.710.0 9.7 9.4 9.8 9.4 9.6 10.3 10.0 9.89.5 9.7 10.6 9.5 10.1 10.0 10.1 9.8 9.39.6 9.4 10.1 9.5 10.1 10.2 9.5 9.8 9.310.3 9.6 9.7 9.7 10.1 9.8 10.0 9.7 10.09.5 9.5 9.8 9.9 9.2 10.0 9.7 10.0 9.79.9 10.4 9.3 9.6 10.2 9.7 9.7 9.7 10.79.9 10.2 9.8 9.3 9.6 9.5 10.7 9.6

N = 125

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CASE STUDY

STEP 2 DETERMINE THRE LARGEST AND SMALLEST VALUEMinimum Maximum

9.9 9.3 10.2 9.4 10.1 9.6 10.1 9.9 9.8 9.3 10.29.8 9.8 10.1 9.9 9.7 9.8 10.0 9.9 9.6 9.6 10.19.7 9.4 9.6 10.0 9.8 9.9 10.4 10.1 10.0 9.4 10.410.2 10.1 9.8 10.1 10.3 10.0 9.8 10.2 10.7 9.8 10.79.9 10.7 9.3 10.3 9.9 9.8 9.5 9.8 9.4 9.3 10.79.3 10.2 9.2 9.9 9.7 9.9 9.5 9.8 9.4 9.2 10.29.0 9.5 9.7 9.7 9.8 9.8 9.6 9.3 9.7 9.0 9.810.0 9.7 9.4 9.8 9.4 9.6 10.3 10.0 9.8 9.4 10.39.5 9.7 10.6 9.5 10.1 10.0 10.1 9.8 9.3 9.5 10.69.6 9.4 10.1 9.5 10.1 10.2 9.5 9.8 9.3 9.3 10.210.3 9.6 9.7 9.7 10.1 9.8 10.0 9.7 10.0 9.6 10.39.5 9.5 9.8 9.9 9.2 10.0 9.7 10.0 9.7 9.2 10.09.9 10.4 9.3 9.6 10.2 9.7 9.7 9.7 10.7 9.3 10.79.9 10.2 9.8 9.3 9.6 9.5 10.7 9.6 9.3 10.7

9.0 10.7

N = 125

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CASE STUDY

STEP 4 Divide the ‘R’ in to No. Of Classes, referred to as ‘K’ 125 data points would be broken down in to 7 – 12 classes.

Method - 1

No.of data points No. of classes

Under 50 5 – 7

50 – 100 6 – 10

100 – 250 7 – 12

Over 250 10 - 20

Method – 2No. Of Classes – K =√N where,

N = No. Of sample

For example, if N = 125K =√125 = 11

Let us use K = 10 classes

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CASE STUDY

STEP 3 Obtain the range of R

Maximum value – Minimum Value = R

10.7 – 9.0 = 1.7

R = 1.7

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CASE STUDY

STEP 5 Determine the class width ‘H’

R (Range)= H

K (# of classes)1.7

= 0.1710

Can be rounded off to 0.20

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CASE STUDY

STEP 6 Divide the value of class boundaryFor simple determination of class boundaries, take the smallest individual measurement in the data set. Use this number or round to the next appropriate lowest number. This will be lower end point for our first class boundary.

In our example this would be 9.0. Now take this number and add the class width to it, 9.00 + 0.20.

But it is essential to fix class boundaries in such way that every observed reading will fit in to ‘one’ and ‘only’ class. Therefore, we may choose the class boundaries with one decimal place more than the observed readings.

For example, if the observations are in one decimal, the class boundaries will be in two decimals and so on.

For our case study, it will be 8.95 + 0.20 = 9.15

Finally, consecutively add the class width, to the lowest class boundary until the correct number of classes, approximately 10 and containing the range of all our numbers is obtained.

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CASE STUDY

STEP 7 Construct a frequency table

Class #

Class Boundaries Midpoint Frequency Total

1 8.95-9.15 9.05 1

2 9.15-9.35 9.25 9

3 9.35-9.55 9.45 16

4 9.55-9.75 9.65 27

5 9.75-9.95 9.85 29

6 9.95-10.5 10.05 26

7 10.5-10.35 10.25 11

8 10.35-10.55 10.45 1

9 10.55-10.75 10.65 5

10 10.75-10.95 10.85 0

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CASE STUDY

STEP 8 Construct Histogram

05

101520253035

8.95 9.15 9.35 9.55 9.75 9.95 10.15 10.35 10.55 10.75Thickness in mm

Freq

uenc

y USL

The specification for the thickness characteristic is 7.5 to 10.5, with a target of 9. The above Histogram indicates the process is targeted high and that 3% may be above the upper specification limit.

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HISTOGRAM

Having two peaks

Having a cut end

Having extraordinarily high value in

the end internal

Having an isolated peak

Right & Left symmetrical

Slopping the right

Slopping to the left

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Average response time to patient rings (1st shift)

050

100150200

1 2 3 4 5 6 7 8 9 1Minutes

# O

f Res

pons

es

Histogram - Daily Example Height of 100 men

010203040

63 65 67 69 71Height (inches)

# O

f Men

Histogram-ManufacturingPrint Density

02468

0.6 0.8 0.1 1.2 1.4Block density of print

Freq

uenc

y

Histogram – Administration/Service Example

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To analyze processes and discover items to be improved

To research process capability

To control the process (in a time series)

To verify effects of an improvement

Histogram

Application

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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.

Histogram

Uses of Histogram

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Scatter diagramScatter diagram

Scatter diagram

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In actual practice, it is often essential to study the relation of two corresponding data types

For example, to what extent will the dimension of a machined part be varied by the change in the speed of a lathe?

Scatter diagram Scatter diagram

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To study the relation of two variables such as the speed of the lathe & the dimension of the part we can use what is called a Scatter diagram.

Scatter diagram

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The two variables we will deal with are:

a) A quality – characteristic & a factor affecting it,

b) Two related quality characteristics, or

c) Two factors relating to a single quality characteristic.

Let’s consider the steps in making a scatter diagram

Scatter diagram

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Examples of such relationships

Speed Vs Mileage

Cutting speed Vs Tool life

Etc……

Scatter diagram

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Step 1

Collect paired data (x,y) between which you want to study the relations & arrange the data in a table. It is desirable to have at least 30 pairs of data.

Scatter diagram

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Step 2

Find the maximum & minimum values for both x & y. Decide the scales of horizontal & vertical axes so that both the lengths become approximately equal, then the diagram will be easier to read. Keep the number of unit graduations between 3 to 10 for each axis & use round numbers to make it easier to read.

=

Scatter diagram

Choosing units that express the range of the x and y values, draw an x scale along the horizontal axis and a y scale along the vertical axis.

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Step 3Plot the data on the section paper. Step 4Enter all necessary items. Make sure that the following

items are included so that anyone besides the maker of the diagram can understand at a glance:

a) Title of the diagramb) Time intervalc) Number of pairs of datad) Title & units of each axise) Name (etc) of the person who made the diagram

Scatter diagram

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Example

A manufacturer of plastic tanks who made them using the blow moulding process encountered problems with defective tanks that had thin tank walls. It was suspected that the variation in air pressure, which varied from day to day, was the cause of the defective thin walls. The table shows data on blowing pressure & percent defective. Let us draw a scatter diagram using this data according to the steps given previously.

Scatter diagram

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Date Air pressure Percent(kgf/cm2) Defective

Oct-01 8.6 0.8892 8.9 0.8843 8.8 0.8744 8.8 0.8915 8.4 0.8746 8.7 0.8867 9.2 0.9118 8.6 0.9129 9.2 0.89510 8.7 0.89611 8.4 0.89412 8.2 0.86413 9.2 0.92214 8.7 0.90915 9.4 0.90516 8.7 0.89217 8.5 0.87718 9.2 0.88519 8.5 0.86620 8.3 0.89621 8.7 0.89622 9.3 0.92823 8.9 0.88624 8.9 0.90825 8.3 0.88126 8.7 0.88227 8.9 0.90428 8.7 0.91229 9.1 0.92530 8.7 0.872

Data of blowing air pressure & percent defective of plastic tank

Scatter diagram

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Step 1

As seen in the table, we have 30 pairs of data.

Step 2

In this example, let blowing air pressure be indicated by X(horizontal axis), & percent defective by Y (vertical axis).

Then,

The maximum value of X: Xmax = 9.4 (kgf/cm2)

The minimum value of X : Xmin = 8.2 (kgf/cm2)

The maximum value of Y: Ymax = 0.928 (%)

The minimum value of Y : Ymin = 0.864 (%)

Scatter diagram

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We mark off

the horizontal axis in 0.5(kgf/cm2) intervals, from 8.0 to 9.5 (kgf/cm2) and

the vertical axis in0.01(%) intervals, from 0.85 to 0.93(%)

Step 3

Plot the data.

Scatter diagram

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0.85

0.86

0.87

0.88

0.89

0.9

0.91

0.92

0.93

8 8.5 9 9.5

Scatter diagram

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Step 4

Enter the time interval of the sample obtained (oct.1 – oct 30) number of samples (n = 30), horizontal axis (blowing air pressure [kgf/cm2]), vertical axis (percent defective [%]), and title of diagram (scatter diagram of blowing air pressure & percent defective).

0.85

0.86

0.87

0.88

0.89

0.9

0.91

0.92

0.93

8 8.5 9 9.5

(Oct 1 – Oct 30)

n=30

P er c

e nta

ge d

e fe c

ti ve

Blowing air pressure

Scatter diagram

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How to read scatter diagrams ?You can grasp the correlation between pairs of data just by looking at the shape of a scatter diagram. 5 examples are given below

Scatter diagram

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05

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0 5 10 15 20

Series1

Positive correlation

Scatter diagram

If y increases with x or the vice versa,then x and y are positively correlated.

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050

100150200250300350

0 100 200 300 400

Series1

Negative correlation

Scatter diagram

If y decreases as x increases, then the two

types of data are negatively correlated.

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0100200300400500600700

0 100 200 300 400

Series1

No correlation

Scatter diagram

If no significant relationship is apparent between x and y, then the two data types are not correlated.

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0

10

20

30

40

0 5 10 15 20

Series1

0

100

200

300

400

500

0 100 200 300 400

Series1

Positive correlation may be present Negative correlation may be present

Scatter diagram

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Let us do an exercise !

Let us say you are simply not satisfied with the marks that your younger brother/sister is scoring. So you want him/her to study more. But does studying more really help? How to find out?

Scatter diagram

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Try a scatter diagram !

No. of hours of study/day0.5 1.0 1.5 2.0 2.5

Perc

enta

ge o

f mar

ks50

60

70

80

90

Scatter diagram

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