qc tools for engineers

1 7QC Tools

7QC TOOLS

2 7QC Tools

3 7QC Tools

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

4 7QC Tools

Don’t worry Tom.,

I am here to help

you.

I will you teach you

some of the QC

tools…

5 7QC Tools

QC tools…What is

that ? That is Quality

control tool. ( In

your case it can be

Quantity Control

tools)

6 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

7 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Check Sheet

8 7QC Tools

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

9 7QC Tools

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

10 7QC Tools

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

11 7QC Tools

Measured Data

Check Sheet

Indiscrete value such as height, weight, length, time & temp., Etc.

Types of Check Sheet

- Check Sheet

12 7QC Tools

Measured Data

Check Sheet

Indiscrete value such as height, weight, length, time & temp., Etc.

Counted Data

Discrete value such as no. Of recording errors, no. of Item sold

& Rejections etc.

Types of Check Sheet

- Check Sheet

13 7QC Tools

Measured Data

Check Sheet

Indiscrete value such as height, weight, length, time & temp., Etc.

Counted Data

Discrete value such as no. Of recording errors, no. of Item sold

& Rejections etc.

Primary Data

YES / NO or / X - Type

Types of Check Sheet

- Check Sheet

14 7QC Tools

Measured Data

Check Sheet

Indiscrete value such as height, weight, length, time & temp., Etc.

Counted Data

Discrete value such as no. Of recording errors, no. of Item sold

& Rejections etc.

Primary Data

YES / NO or / X - Type

Ordered Data

1st, 2nd Order …Very Good, Good, No Good … - Type

Types of Check Sheet

- Check Sheet

15 7QC Tools

Measured Data

Check Sheet

Indiscrete value such as height, weight, length, time & temp., Etc.

Counted Data

Discrete value such as no. Of recording errors, no. of Item sold

& Rejections etc.

Primary Data

YES / NO or / X - Type

Ordered Data

1st, 2nd Order …Very Good, Good, No Good … - Type

Point Scale Data

1 Point, 2 Point … etc.

Types of Check Sheet

- Check Sheet

16 7QC Tools

Check Sheet

Measured Data

Counted Data

Primary Data

Point Scale Data

Ordered Data

Indiscrete value such as height, weight, length, time & temp., Etc.

Discrete value such as no. Of recording errors, no. of Item sold

& Rejections etc.

YES / NO or / X - Type

1st, 2nd Order …Very Good, Good, No Good … - Type

1 Point, 2 Point … etc.

Types of Check Sheet

- Check Sheet

17 7QC Tools

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

Check sheets can be used in all stages of Problem solving

- Check Sheet

18 7QC Tools

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

20 7QC Tools

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

21 7QC Tools

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

22 7QC Tools

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

Collect data

- Check Sheet

23 7QC Tools

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

24 7QC Tools

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

25 7QC Tools

E1 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

26 7QC Tools

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

27 7QC Tools

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

28 7QC Tools

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

29 7QC Tools

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

30 7QC Tools

• 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

31 7QC Tools

Pareto diagram

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Pareto Diagram

Co

un

t

Pe

rce

nt

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

Othe

r

Other

s

Stor

es

Inform

ation & Sys

tems

Person

nel

Prod

uctio

n En

gine

ering

Service

Fina

nce

Plan

t Mainten

ance

Marke

ting

Mater

ials

200

150

100

50

0

100

80

60

40

20

0

Pareto Chart of Department

32 7QC Tools

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

33 7QC Tools

Vilfredo 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

34 7QC Tools

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

35 7QC Tools

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

36 7QC Tools

Step 1 : Data collection from check sheet

Sl.No Department No. of calls registered in the period

week 45 to 50.

1 Production Engineering 10

2 Quality 2

3 Service 12

4 Marketing 45

5 Plant Maintenance 20

6 Factory production 2

7 Manufacturing Planning 1

8 Stores 5

9 Personnel 8

10 Materials 66

11 Finance 15

12 Research & Development 4

13 Information & Systems 6

14 Others 4

Example : Identification of depts. contributing majority of telephone calls

- Pareto Diagram

37 7QC Tools

Step 2 : Arrange data in the descending order

Sl.No Department

1 Materials

2 Marketing

3 Plant Maintenance

4 Finance

5 Service

6 Production Engineering

7 Personnel

8 Information Systems

9 Stores

10 Research & Development

11 Others

12 Quality

13 Factory production

14 Manufacturing Planning

Nos.

66

45

20

15

12

10

8

6

5

4

4

2

2

1

200

- Pareto Diagram

38 7QC Tools

Sl.No Department Nos.

1 Materials 66

2 Marketing 45

3 Plant Maintenance 20

4 Finance 15

5 Service 12

6 Production Engineering 10

7 Personnel 8

8 Information Systems 6

9 Stores 5

10 Research & Development 4

11 Others 4

12 Quality 2

13 Factory production 2

14 Manufacturing Planning 1

200

Relative %

33.0

22.5

10.0

7.5

6.0

5.0

4.0

3.0

2.5

2.0

2.0

1.0

1.0

0.5

100

Step 3 : Calculate the relative % for individual

- Pareto Diagram

39 7QC Tools

Sl.No Department Nos. Relative %

1 Materials 66 33.0

2 Marketing 45 22.5

3 Plant Maintenance 20 10.0

4 Finance 15 7.5

5 Service 12 6.0

6 Production Engineering 10 5.0

7 Personnel 8 4.0

8 Information Systems 6 3.0

9 Stores 5 2.5

10 Research & Development 4 2.0

11 Others 4 2.0

12 Quality 2 1.0

13 Factory production 2 1.0

14 Manufacturing Planning 1 0.5

200 100

Cumulative %

33.0

55.5

65.5

73.0

79.0

84.0

88.0

91.0

93.5

95.5

97.5

98.5

99.5

100.0

Step 4 : Calculate the cumulative % for individual

- Pareto Diagram

40 7QC Tools

0

25

50

75

100

125

150

175

200

Ma

teri

als

Ma

rke

tin

g

Pla

nt

Ma

inte

na

nce

Fin

an

ce

Se

rvic

e

Pro

du

cti

on

En

gin

ee

rin

g

Pe

rso

nn

el

Info

rma

tio

n

Syst

em

s

Sto

res

Re

sea

rch

& D

eve

lop

me

nt

Oth

ers

Qu

ali

ty

Fa

cto

ry p

rod

ucti

on

Ma

nu

factu

rin

g P

lan

nin

g

Dept

In n

os

0

25

50

75

100

Cu

mu

lati

ve

%

Step 5 : Draw a graph with scales on both axis

- Pareto Diagram

41 7QC Tools

66

45

20 15 12 10 8 6 5 4 4 2 2 10

25

50

75

100

125

150

175

200

Ma

teri

als

Ma

rke

tin

g

Pla

nt

Ma

inte

na

nce

Fin

an

ce

Se

rvic

e

Pro

du

cti

on

En

gin

ee

rin

g

Pe

rso

nn

el

Info

rma

tio

n

Syst

em

s

Sto

res

Re

sea

rch

& D

eve

lop

me

nt

Oth

ers

Qu

ali

ty

Fa

cto

ry p

rod

ucti

on

Ma

nu

factu

rin

g P

lan

nin

g

Dept

In n

os

0

25

50

75

100

Cu

mu

lati

ve

%

Step 6 : Draw bar chart based on data

- Pareto Diagram

42 7QC Tools

45

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

Mate

rials

Mark

eti

ng

Pla

nt

Main

ten

an

ce

Fin

an

ce

Serv

ice

Pro

du

cti

on

En

gin

eeri

ng

Pers

on

nel

Info

rmati

on

Syste

ms

Sto

res

Researc

h &

Develo

pm

en

t

Oth

ers

Qu

ali

ty

Facto

ry

pro

du

cti

on

Man

ufa

ctu

rin

g

Pla

nn

ing

Dept

In n

os

0

25

50

75

100

Cu

mu

lati

ve %

45

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

Mate

rials

Mark

eti

ng

Pla

nt

Main

ten

an

ce

Fin

an

ce

Serv

ice

Pro

du

cti

on

En

gin

eeri

ng

Pers

on

nel

Info

rmati

on

Syste

ms

Sto

res

Researc

h &

Develo

pm

en

t

Oth

ers

Qu

ali

ty

Facto

ry

pro

du

cti

on

Man

ufa

ctu

rin

g

Pla

nn

ing

Dept

In n

os

0

25

50

75

100

Cu

mu

lati

ve %

Step 7 : Using cumulative % data, draw cumulative curve

- Pareto Diagram

43 7QC Tools

Now let’s construct the Pareto using Minitab…

- Pareto Diagram

44 7QC Tools

Enter Department

details in column C1

Enter phone call details in

column C2

Data entry sheet - Minitab

- Pareto Diagram

45 7QC Tools

Navigation details in MINITAB

Select Stat > Quality tools

> Pareto chart

- Pareto Diagram

46 7QC Tools

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

47 7QC Tools

Click OK

- Pareto Diagram

48 7QC Tools

Co

un

t

Pe

rce

nt

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

Othe

r

Other

s

Stor

es

Inform

ation & Sys

tems

Person

nel

Prod

uctio

n En

gine

ering

Service

Fina

nce

Plan

t Mainten

ance

Marke

ting

Mater

ials

200

150

100

50

0

100

80

60

40

20

0

Pareto Chart of Department

Graphical display in MINITAB

- Pareto Diagram

49 7QC Tools

Co

un

t

Pe

rce

nt

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

Othe

r

Other

s

Stor

es

Inform

ation & Sys

tems

Person

nel

Prod

uctio

n En

gine

ering

Service

Fina

nce

Plan

t Mainten

ance

Marke

ting

Mater

ials

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

50 7QC Tools

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

51 7QC Tools

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

52 7QC Tools

Summary

A few causes lead to many defects Pareto's 20:80 rule:

Co

un

t

Pe

rce

nt

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

Othe

r

Other

s

Stor

es

Inform

ation & Sys

tems

Person

nel

Prod

uctio

n En

gine

ering

Service

Fina

nce

Plan

t Mainten

ance

Marke

ting

Mater

ials

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

53 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Cause & Effect Diagram

54 7QC Tools

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

55 7QC Tools

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

56 7QC Tools

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

57 7QC Tools

Step- by - step procedure

to construct a Cause and Effect diagram

- Cause & Effect Diagram

58 7QC Tools

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

59 7QC Tools

Example for construction

Effect:

- Cause & Effect Diagram

Poor Vehicle Mileage

60 7QC Tools

Step 2 – Draw the SPINE and create EFFECT BOX

Poor Vehicle

Mileage

Spine

Effect box

- Cause & Effect Diagram

61 7QC Tools

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

62 7QC Tools

Step 3 – Identify the main Causes contributing to the effect

being studied continued…

Poor Vehicle

Mileage

Method Machine

Material Men

- Cause & Effect Diagram

63 7QC Tools

Step 4 – For each major factors, identify other specific

factors which may be the Causes of the Effect

Poor Vehicle

Mileage

Method Machine

Material Men

Under inflated

tyres

Carburettor

adjustments

Use wrong

gears

Drive too

fast

Poor

maintenance

Poor driving

habits

Improper

lubrication

Wrong

Octane fuel

- Cause & Effect Diagram

64 7QC Tools

Step 5 – Identify increasing more detailed levels of causes

Poor Vehicle

Mileage

Method Machine

Material Men

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

65 7QC Tools

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 4 Material

Poor Vehicle

Mileage

Improper

lubrication

Wrong

Octane fuel

Step 5 – Identify increasing more detailed levels of causes

continued…

- Cause & Effect Diagram

66 7QC Tools

Step 5 – Identify increasing more detailed levels of causes

continued…

Poor Vehicle

Mileage

Method Machine

Material Men

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 mix Unskilled mechanic Poor design

Can‟t hear engine

Impatience Poor hearing

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 4 All the causes are not captured here due to space constraint on the screen.

No Owner‟s

Manual

Done for all

CAUSES

- Cause & Effect Diagram

67 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

68 7QC Tools

Men Material

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 mix Unskilled mechanic Poor design

Can‟t hear engine

Impatience Poor hearing

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 4 All 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

69 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

70 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

3 4

71 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

72 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?

- Cause & Effect Diagram

73 7QC Tools

Late arrival

of train

at station

Method Machine

Material Men

Group 3

Group 1 Group 2

Group 4

- Cause & Effect Diagram

Lets do an exercise on Cause & Effect Diagram

74 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Graph & Control Charts

75 7QC Tools

Graphs

- Graph & Control Charts

76 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

77 7QC Tools

Graph

Graph is a visual representation tool used for showing the

relationship between two or more variables

- Graph & Control Charts

78 7QC Tools

Facilitate in understanding

the data

Quick and direct Easy to remember

Highlight most

important facts

Graph

- Graph & Control Charts

79 7QC Tools

Types of Graphs

• Line graph

•Bar graph

• Pie chart

- Graph & Control Charts

M1

M2

M3

M4

M5

0

10

20

30

40

50

60

70

80

90

100

M1 M2 M3 M4 M5

Studid

Studname

40

45

42 42 42

43

37

38

39

40

41

42

43

44

45

46

Jan Feb Mar Apr May Jun

80 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

37

38

39

40

41

42

43

44

45

46

Jan Feb Mar Apr May Jun

81 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

82 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

83 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

Wei

ght

(gra

ms)

Construction of line graph

- Graph & Control Charts

84 7QC Tools

Use of MINITAB to

Construct graphs

- Graph & Control Charts

85 7QC Tools

General layout of MINITAB 14

New worksheet

Worksheet – Data

entry in this region

- Graph & Control Charts

86 7QC Tools

Various types of graphs in MINITAB

- Graph & Control Charts

87 7QC Tools

Minitab - graphs

Scatter plot

Data

- Graph & Control Charts

88 7QC Tools

Minitab - graphs

Types of plot

- Graph & Control Charts

89 7QC Tools

Minitab - graphs

Select X & Y

variable

- Graph & Control Charts

90 7QC Tools

Minitab - graphs

Line graph

Options to modify the

graph to get data label

- Graph & Control Charts

91 7QC Tools

Minitab - graphs

Window to get the

data label in graph

- Graph & Control Charts

92 7QC Tools

Month

We

igh

t 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

93 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

0

10

20

30

40

50

60

70

80

90

100

M1 M2 M3 M4 M5

Studid

Studname

94 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

Nu

mb

er o

f p

oli

ce o

ffic

ers

0

10

20

30

40

50

60

1993 1994 1995 1996 1997 1998 1999 2000

Year

Nu

mb

er o

f p

oli

ce o

ffic

ers

Vertical

Horizontal

Vertical

Horizontal

• Simple Bar graph Vertical

Horizontal

0

10

20

30

40

50

60

1993 1994 1995 1996 1997 1998 1999 2000

Year

Nu

mb

er o

f p

oli

ce o

ffic

ers

Simple Bar graph Clustered Bar graph Stacked Bar graph

- Graph & Control Charts

95 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

96 7QC Tools

To create bar graph in MINITAB

Bar chart

option

- Graph & Control Charts

97 7QC Tools

To create bar graph in MINITAB

Bar chart types

selection

- Graph & Control Charts

98 7QC Tools

To create bar graph in MINITAB

Selection of X & Y

axis variable

- Graph & Control Charts

99 7QC Tools

To create bar graph in MINITAB

Options to modify

the graph to get

data label

- Graph & Control Charts

100 7QC Tools

Year

No

., o

f P

olic

e o

ffic

ers

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

101 7QC Tools

To create clustered-bar graph in Minitab

- Graph & Control Charts

102 7QC Tools

To create clustered-bar graph in Minitab

- Graph & Control Charts

103 7QC Tools

Da

ta

C1

2000

1999

1998

1997

1996

1995

1994

1993

Nor

thW

est

East

No rt

hW

est

East

Nor

thW

est

East

Nor

thW

est

East

Nor

thW

est

East

Nor

thW

est

East

No rt

hW

est

East

Nor

thW

est

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

104 7QC Tools

To create stacked bar graph in Minitab

- Graph & Control Charts

105 7QC Tools

To create clustered-bar graph in Minitab

- Graph & Control Charts

106 7QC Tools

Da

ta

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

107 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

M1

M2

M3

M4

M5

108 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

109 7QC Tools

To create pie-chart in Minitab

name

variable

- Graph & Control Charts

110 7QC Tools

To create Pie-chart in Minitab

- Graph & Control Charts

111 7QC Tools

55, 62.5%Kerala

11, 12.5%Andhra

22, 25.0%Tamilnadu

Category

Tamilnadu

Andhra

Kerala

Pie Chart of Quantity vs State

- Graph & Control Charts

112 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

113 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

114 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

115 7QC Tools

Your graph may be like this …

Month

Scra

p c

ost

/ E

ng

ine

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

Lit

era

cy

ra

te

%

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

Da

ta

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

116 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

117 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Histogram

Histogram

118 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

119 7QC Tools

What do we need to infer from this data?

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

120 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

How do you find that?

We can use Histogram.

How the data

looks like

Range of

battery life

Mean of

battery life

- Histogram

121 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

Fre

qu

en

cy

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

122 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

123 7QC Tools

Step- by - step procedure

to construct a histogram

- Histogram

124 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

125 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

126 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

127 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

128 7QC Tools

Step 3 – Create table of upper & lower limits of

class-intervals continued…

Class interval Lower limit Upper limit

1 32 88

2 89 145

3 146 202

4 203 259

5 260 314

6 315 371

7 372 428

- Histogram

129 7QC Tools

Step 4 – Prepare frequency distribution table

How many pieces of data fall into each of the class?

# Class Frequency marks Frequency

1

2

3

4

5

6

7

32 – 88

89 – 145

146 – 202

203 – 259

260 – 316

317- 373

374 – 430

IIII

IIII I

IIII IIII

IIII

IIII IIII IIII IIII II

IIII III

II

4

6

9

5

22

8

2

Total 56

- Histogram

130 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

. o

f fa

ilu

res

Class

Frequency

Now, what do you interpret from this histogram?

- Histogram

131 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

132 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

. o

f fa

ilu

res

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

133 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

134 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

Fre

qu

en

cy

13.012.512.011.511.010.5

LSL USL

1

3

1

4

14

3

10

8

5

1

Process Capability of Diameter

LSL

Target

Process

mean

- Histogram

Process Data

Freq

uen

cy

13.012.512.011.511.010.5

LSL USL

1

3

1

4

14

3

10

8

5

1

Process Capability of Diameter

USL

135 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

Fre

qu

en

cy

13.012.512.011.511.0

LSL USL

22

7

10

12

10

2

3

2

Process Capability of Shaft dia

- Histogram

Process Data

Freq

uen

cy

13.012.512.011.511.010.5

LSL USL

1

3

1

4

14

3

10

8

5

1

Process Capability of Diameter

136 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

Fre

qu

en

cy

14121086420

12

10

8

6

4

2

0

1

00

111

0

22

3

6

5

10

12

6

Histogram of C9

Process Data

Fre

qu

en

cy

13.012.512.011.511.0

22

7

10

12

10

2

3

2

Process Capability of Shaft diaNormal Non-

normal

- Histogram

Process Data

Freq

uen

cy

13.012.512.011.511.010.5

LSL USL

1

3

1

4

14

3

10

8

5

1

Process Capability of Diameter

137 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

138 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

. o

f fa

ilu

res

Interpretations from histograms continued…

- Histogram

139 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

RaF

req

ue

nc

y

Interpretations from histograms continued…

- Histogram

140 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

. o

f tr

ucks

Interpretations from histograms continued…

- Histogram

141 7QC Tools

Histogram - Wheel-rim - Runout

1

6

21 22

0

5

10

15

20

25

0.94 1.02 1.09 More

Runout, mm

Fre

qu

en

cy

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

142 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

143 7QC Tools

Construction of a histogram using MINITAB software

- Histogram

144 7QC Tools

Start MINITAB This is the first

screen of MINITAB

Here is the place

for your data

Session

window

- Histogram

145 7QC Tools

Enter the data

in a column,

say, C2

Enter the data

- Histogram

146 7QC Tools

Go to Graph

Histogram

Draw histogram

- Histogram

147 7QC Tools

Select the type

“With Fit…”

Draw histogram continued...

- Histogram

148 7QC Tools

Click Select to

select the

column C2

C2 appears

here

Click OK

Draw histogram continued...

- Histogram

149 7QC Tools

Here is the

histogram

Draw histogram continued...

- Histogram

150 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?

Summary - Histogram

- Histogram

151 7QC Tools

55 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

152 7QC Tools

Marks

Fre

qu

en

cy

7264564840

20

15

10

5

0

1

2

8

19

16

2

1

0

1

Histogram of Marks

Test scores

Fre

qu

en

cy

7060504030

9

8

7

6

5

4

3

2

1

0

11

33

5

8

4

1

3

1

Histogram of Test scores

Data

Fre

qu

en

cy

240180120600

20

15

10

5

0

1

00

1

2

7

10

19

10

Histogram of Data

Data A

Fre

qu

en

cy

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

153 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Scatter Diagram

Temperature

No

of

ice

cre

am

s s

old

35302520151050

110

100

90

80

70

60

50

40

30

20

Scatterplot of No of ice creams sold vs Temperature

154 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

155 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

156 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

157 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

158 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

159 7QC Tools

Draw the graph

Outside temperature

No o

f ic

e c

ream

s so

ld

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

160 7QC Tools

10 20 30 40 50

20

40

60

80

100

120

Outside temperature

No o

f ic

e c

ream

s so

ld

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

161 7QC Tools

10 20 30 40 50

20

40

60

80

100

120

Outside temperature

No o

f ic

e c

ream

s so

ld

Plot the data 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

- Scatter Diagram

162 7QC Tools

10 20 30 40 50

20

40

60

80

100

120

Outside temperature

No o

f ic

e c

ream

s so

ld

Identify and classify the pattern

- Scatter Diagram

163 7QC Tools

Now let’s construct the Scatter using Minitab…

- Scatter Diagram

164 7QC Tools

Enter Temperature

values in column C1

Enter No of ice creams

sold in column C2

- Scatter Diagram

165 7QC Tools

Select Graph > Scatter plot

- Scatter Diagram

166 7QC Tools

Click OK

Select with

Regression

- Scatter Diagram

167 7QC Tools

Select C1 - X

variables

Select C2 - Y

variables

- Scatter Diagram

168 7QC Tools

Click OK

- Scatter Diagram

169 7QC Tools

Temperature

No

of

ice

cre

am

s s

old

35302520151050

110

100

90

80

70

60

50

40

30

20

Scatterplot of No of ice creams sold vs Temperature

- Scatter Diagram

170 7QC Tools

Temperature

No

of

ice

cre

am

s s

old

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

171 7QC Tools

Temperature

No

of

ice

cre

am

s s

old

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

172 7QC Tools

0

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

173 7QC Tools

Weak 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

174 7QC Tools

0

100

200

300

400

500

600

700

0 100 200 300 400

No correlation

Types of Scatter Diagram

- Scatter Diagram

175 7QC Tools

J-shaped /Non linear association

Suggests complex relationships

Types of Scatter Diagram

- Scatter Diagram

176 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

177 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

178 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 TemperatureN

um

be

r o

f ic

e-c

rea

m

so

ld

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

179 7QC Tools

Check Sheet

Pareto Diagram

Cause & Effect diagram

Stratification

Scatter Diagram

Graphs

Histogram

7 QC Tools

- Stratification

180 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

181 7QC Tools

Rep.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

182 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

183 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

184 7QC Tools

According to plant

Plant wise

No

of

accid

en

ts

Othe

rs

Expo

rt war

e ho

use

Cantee

nCivi l

Spar

e war

e ho

use

R &

D

Plan

t 4

Plan

t 3

Plan

t 2

Plan

t 1

120

100

80

60

40

20

032

105

8

16

108

42

108

42

Chart of No of accidents vs Plant wiseN

o o

f accid

en

ts

Plant

- Stratification

185 7QC Tools

Similarly stratification can be done

Unit wise

Workmen category wise

Shift wise

Phenomena wise

Machine/equipment wise

and so on…

186 7QC Tools

Other Stratification methodologies

- Stratification

187 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

188 7QC Tools