7 qc tools-trg module- act--advance cluster

1Slide No.Property of ACT ( ACMA Centre for Technology ) 2007

77QC toolsQC tools

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Pareto Diagram

Check Sheet

Cause and Effect Diagram

Graph and Control Chart

Scatter Diagram

Stratification

Histogram

Seven QC ToolsSeven QC Tools





Sl.No Tools

Scatter Diagram To see relation between two sets of data

Function

1

2

3

5

6

7

Histogram To see the distribution pattern compared against the standard values.

Stratification To segregate data according to contributing sources.(Suppliers,machines,operators etc)

Presentation of data in a pictorial form for better understanding and see if the process is under stable conditions.

Graph and Control Chart

Cause and Effect Diagram

To reorganise the factors (causes) which are influencing the problem

4

Check Sheet / Data Sheet

To Collect the data in a simple manner and to prevent omitting the checks

To pick up the important few problems from the trivial many. Pareto Daigram





Take reading of temperature nearest to degree.Time Temp (0C) Time Temp (0C)0800 60 1300 610900 62 1400 581000 59 1500 631100 58 1600 631200 59 1700 59

Note : Power failure from 12.00 to 12.15 Hours

Solder Bath TemperatureChecked by : Raised by :

Check SheetCheck Sheet





What is Check Sheet ?What is Check Sheet ?A Check sheet is a paper form on which item to be

checked have been printed already so that data can be collected easily and concisely. Its main purposes are two-fold :1) To make data-gathering easy ;2) To arrange data automatically so that they can be used easily later on

Two Types of Data :Two Types of Data :1. Measurement data or Variable data.2. Attribute data.





Check sheets are of following types :Check sheets are of following types :

a) Check sheet for production process distribution.

b) Defective item check sheet.

c) Defect location check sheet.

d) Defect cause check sheet.





-10-9

Specification -8-7-6-5 1-4 2-3 4-2 6-1 9

8.300 0 111 82 73 34 25 16 17

Specification 8910

55

Frequency5 10 15 20

Total

ChecksDeviation

Check Sheet for Production Process Distribution::





Type SubtotalSurface scars I I I I I I I I I I I I I I 17

Cracks I I I I I I I I I 11

Incomplete I I I I I I I I I I I I I I I I I I I I I 26

Mishappen I I I 3

Others I I I I 5

62

Total rejects 42

Total :

Checks

Product :

Manufacturing stage: Final inspection

Type of defect: Scar,incomplete

crack,misshapen.

Total no.inspected : 1525

Remarks : All items inspected.

Date :

Section :

Inspector’s name :

Lot no :

Order no :

Defective Item Check Sheet:Defective Item Check Sheet:





A B C D

1

2

3

4

Defect Location Check SheetDefect Location Check Sheet

Defect Location Matrix For Blowholes (50 Defective Components)Defect Location Matrix For Blowholes (50 Defective Components)

1 2 3 4

A 1

B 12 15

C 10 11

D 1

From the location matrix it is

clear that most of the blow holes

are occupied in the segment B2,B3,C2 & C3.





o Damage x Blowhole Poor finish Crack Others

Defect Cause Check Sheet.Defect Cause Check Sheet.

AM PM AM PM AM PM AM PM AM PM AM PM

Fri SatEquipment Operator

Mon Tue Wed Thu

1

2

A

B

1

2

oxx ooooo xx

oooxxx

xx ooxx

oo xxxx oo

oo

oo

xx

xxx

oo xx





Points to remembered while making check sheetsPoints to remembered while making check sheets

v Easy to use and understand.

v Information should be true and accurate.

v Decide objective by involving all the members.

v Use 5W and 1H principle.

v Who will collect the data ?

v When will the data be collected ?

v Where will the data be collected ?

v How will data be collected ?

v Check sheets should be displayed on visible area.





Benefits of Check SheetsBenefits of Check SheetsData Collection have the following benefits :

• Right decision can be made.

• Errors due to subjective feeling or personal bias are avoided.

• Agreement on decisions necessary rather than different or

subjective opinion.

• Measurement understandable to all.

• Assessments of magnitude of improvements.

• Discovery of causes affecting quality and productivity.





Pareto DiagramPareto Diagram

156

105

20 16 9

85.2891.53 96.75 100

50.98

0

50

100

150

200

250

Coldshut

oil shot Damage Chip off Bad app0

20

40

60

80

100

No

of C

ompo

nent

s

% C

umul

ativ

e

Types of Defects





What is Pareto Diagram ?What is Pareto Diagram ?Pareto diagrams are presentation technique used to

show facts and they help us to separate the “vital few”.

Pareto diagram was first thought out by an Italian economist,

Pareto (1848 - 1923), when he used it as a method for national

income analysis to show that a large proportion of the wealth

was centered around a small minority of people.

After that, an American Quality Control Authority, Mr.Juran used

it in the field of Quality Control.





Steps to make the pareto diagrams :Steps to make the pareto diagrams :

1) Decide what problems are to be investigated and how to collect the

data.

2) Design a data tally sheet listing the items,with space to record their

totals.

3) Fill out the tally sheet and calculate the totals (Example-1)

4) Make the pareto diagram data sheet listing the items, their individual

totals,cumulative totals,percentages of overall total, and cumulative

percentages (Example-2)





Steps to make the pareto diagrams (contd.) :Steps to make the pareto diagrams (contd.) :

1) Draw two vertical axes and a horizontal axis.

2) Construct a bar diagram.

3) Draw the cumulative curve (Pareto curve).

4) Write any necessary items on the diagram.

a) Items concerning the diagram.

b) Items concerning the data.

5) Arrange the items in the order of quantity,and fill out the data sheet.





Type of Defect Total

Crack I I I I I I I I 10

Scratch I I I I I I I I I I I I I I I I …………. I I I I I I 42

Stain I I I I I 6

Strain I I I I I I I I I I I I I I I I I I I I I I I I 104

Gap I I I I 4

Pinhole I I I I I I I I I I I I I I I I 20

Others I I I I I I I I I I I I 14

Total 200

Tally

……………………….

Data Tally Sheet Data Tally Sheet -- Example Example --11





Strain 104 104 52 52

Scratch 42 146 21 73

Pinhole 20 166 10 83

Crack 10 176 5 88

Stain 6 182 3 91

Gap 4 186 2 93

Others 14 200 7 100

Total 200 - 100 -

Cumulative Percentage

Type of Defect

Number of Defect

Cumulative Total

Percentage of Overall Total

Data Sheet for Pareto Diagram Data Sheet for Pareto Diagram -- Example Example -- 22





4220

10 6 4 14

104

52

100939188

8373

0

20

40

60

80

100

120

140

160

180

200

D B F A C E Others0

10

20

30

40

50

60

70

80

90

100

Parteo Diagram by Defective Items:Parteo Diagram by Defective Items:

A :Crack, B: Scratch, C: Stain, D: Strain, E: Gap, F: Pinhole.

No

of D

efec

tive

Uni

tsN

o of

Def

ectiv

e U

nits

Cum

ulat

ive

Per

cent

age

Cum

ulat

ive

Per

cent

age

April 1 - June 30

(Number of Units Investigated : 5,000)(Number of Units Investigated : 5,000)





Cause and Effect DiagramCause and Effect Diagram

Material

Man Machine

Method

Characteristics





What is Cause and Effect Diagram ?What is Cause and Effect Diagram ?Any defect in a component, a product or service could be

due to one or more causes.To find out the relationship between

the causes and effect, a diagram is drawn systematically by

mapping out all the probable causes influencing the effect.

This is called a “Cause and Effect Diagram”

Cause and effect diagram was introduced by “Dr.K.Ishikawa”.

He used it in Kawasaki Iron Works in 1943.

Since final diagram looks like a fish bone it is also called as

Fish Bone Diagram.





Main Cause Main Cause A

Level 2Cause

Level 1Cause

Characteristics

Main Cause Main Cause

Level 3Cause

Format of a Cause and Effect DiagramFormat of a Cause and Effect Diagram

Above diagram depicts the basic format of Cause and Effect diagram. There is a hierarchical relationship of the effect to the main causes and their subsequent relationship to the sub-causes.





1) Determine the quality characteristics.

2) Choose one quality characteristics and write it on the right-

hand side of a sheet of paper, draw in the backbone form

left to right, and enclose the characteristic in a square. Next,

write the primary causes which affect the quality characteristics

as big bones also enclosed by squares.

Procedure for Making CauseProcedure for Making Cause--andand--effect Diagrams effect Diagrams for Identifying Causes:for Identifying Causes:





Procedure for Making CauseProcedure for Making Cause--andand--effect Diagrams effect Diagrams for Identifying Causes for Identifying Causes –– (contd):(contd):

3) Write the causes (Secondary causes) which affect the big

bones (primary causes) as medium-sized bones and write the

causes (tertiary causes) which affect the medium-sized bones

as small bones.

4) Assign an importance to each factor and mark the particularly

important factor that seem to have a significant effect on the

quality characteristics.

5) Record any necessary information.





Defeat in aDefeat in asports matchsports match

SpiritSpiritHealthHealth

Rest

Quantity

Nutrition Calories

Meal

Relaxation

Amusement

Time

Sleep

Depth

EncouragementPride

Fighting spirit

DevotionCalmness

Composure

Confidence

Patience

Carefulness

Concentration

TechniqueTechnique

InformationStudy ofopponent

Analysis

ObservationJudgement of situation

Experience of matches

Commonsense

Planning

Theory

Rules

StrategyStrategy

Power

MotionSpeed

CooperationTeamwork

Function

Schedule

ExerciseQuality

QuantityAdvice

Form

Model Repetition

Example of CauseExample of Cause--andand--Effect Diagram :Effect Diagram :





Valve Plate Projecting out of cyl.head in 94 dia cylinder head assembly WHY?

MAN

METHOD MATERIAL

Hole location not taken during assembly

Valve plate outerdimension oversize

Improper blanking

MACHINE

Wrong assembly

New operator

Gap less at suction side

Hole position shifted

In adequateFixture design

Milling Depth under size

High variation in the process

Example of CauseExample of Cause--andand--Effect Diagram :Effect Diagram :

M/c condition not ok

Importance not known to operator

No Poka yoke

In adequatedesign





Points to remembered.Points to remembered.

1) Once Cause and Effect diagram is made, check for its

completeness. If required get reviewed from the experts.

2) A good Cause and Effect diagram gives an excellent

understanding of a complex problem in a simple way.

3) Cause and Effect diagram is not an answer of the problem.

4) Main cause to be found out by collecting data or on collective

experience.

5) Less educated persons and with poor knowledge about process

can be benefited by this.





Graph and Control ChartGraph and Control ChartUCLC/LLCL





Graph is a pictorial representation of data which is easily

understandable at a glance. It is a visual representation of

data made up of points, lines, letters, words, numbers,

shades etc.

What is Graph :What is Graph :





Types of Graphs :Types of Graphs :

1) Line graph2) Bar chart / graph3) Pie chart or Circle graph4) Radar chart5) Compound graphs - bar and line6) Gantt chart





709

662

330273

376

275250

400

550

700

Jan'03 Feb Mar Apr May June

Month

Qty

Pro

duce

d

Production details

Line Graph :Line Graph :





3.4 34

6.3

4

7

0

1

2

3

4

5

6

7

8

9

10

Jan'01 Feb'01 Mar'01 Apr'01 May'01 Jun'01

Hrs

Bar Chart / Graph :Bar Chart / Graph :

HMC Machine BreakdownHMC Machine Breakdown





Damage & Broken - 340Tags removed - 334

Unwanted - 61Tags removed - 59 Leakage - 845

Tags removed - 825

Missing - 385Tags removed - 380

Loose - 393Tags removed - 390

Electrical - 332Tags removed - 325

Easy to CLI - 855Tags removed - 850

Pie chart or Circle graph :Pie chart or Circle graph :

Classification of abnormality tags.Classification of abnormality tags.





Radar chartRadar chart

0.85

60%

100%

80%

90%

0%

50%

100%unit1

unit2

unit3unit4

unit5

Plant performance : 2001-2002





3 34

7

4

7

3.5

4.75

8.759.25

54.75

0

1

2

3

4

5

6

7

8

9

10

Jan'01 Feb'01 Mar'01 Apr'01 May'01 Jun'01

Frequency

Hours

Compound graph Compound graph -- Bar and LineBar and Line

HMC Machine BreakdownHMC Machine Breakdown





Gantt chartGantt chart





What is Control Chart :What is Control Chart :

1) Control chart is a graphical device to aid in process control.

2) It consist of a graph with a central line denoting the target value

control limit” and “Limit control limit” and two limit lines on either side

of the central line called “Upper

3) Quality measured periodically is plotted on the chart and status of

control assessed.

4) The control chart was first proposed by Dr.Walter A Shewhart, an

engineer in the Bell Telephone Laboratories,USA with a view

to eliminate abnormal variation.





Two Types of Variations :Two Types of Variations :

1. Chance Causes.

2. Assignable Causes.

1. Chance Causes :

Which are uncontrollable and comprising very small

differences in raw materials in the same batch or machines,

actual conditions etc.

2. Assignable Causes :

Such as different settings of a machine, different raw

material batches, changes in operators, operator errors etc.





Characteristic Value Name

x - R Chart (average value and range)

x chart (measured value)

pn chart (number of defective units)

p chart (fraction defective)

c chart (number of defects)

u chart (number of defects per unit)

Discrete value

Continuous value

Types of Control ChartTypes of Control Chart





x - R Chart

Types of Control Chart :Types of Control Chart :

1) It is used for controlling and analyzing a process using

continuous values of product quality such as length, weight or

concentration and this provides the larger amount of information on the

process.

2) x represents an average value of a subgroup and R represents the

range of the subgroup.

3) An R chart is used usually in combination with an x chart to

control the variation within a subgroup.





Procedure to make control charts :Procedure to make control charts :

x = x1 + x2 +……+ xk

k

1) Collect the data.

2) Calculate x

n - Size of a sub groupx = x1 + x2 +……+ xn

n

k - Number of subgroups

3) Calculate x

x - R Chart





R = (Maximum value in a subgroup) -(Minimum Value in a subgroup)

x - R Chart

Procedure to make control charts (contd.) :Procedure to make control charts (contd.) :

4) Calculate R

R = Rx1 + Rx2 +……+ Rn

k

5) Calculate R





6) Calculate the control linesx - R Chart


x Chartx Chart

Central line :

CL = x

Upper control limit :

UCL = x + A2R.

Lower control limit :

UCL = x - A2R





7) Calculate the control linesx - R Chart


R ChartR Chart

Central line :

CL = R

Upper control limit :

UCL = D4R.

Lower control limit :

LCL = D3R





Size of Subgroup x Chartn A2 D3 D4 d2

2 1.88 --- 3.267 1.128

3 1.023 --- 2.575 1.693

4 0.729 --- 2.282 2.059

5 0.577 --- 2.115 2.326

6 0.483 --- 2.004 2.534

R Chart

Procedure to make control charts(contd.) :Procedure to make control charts(contd.) :8) List of Coefficients for x - R Chart.





x - R Chart

Procedure to make control charts(contd.) :Procedure to make control charts(contd.) :

9) Plot the points.

10) Draw the control lines.

11) Write the necessary items.





Examples of Control Chart :Examples of Control Chart :

UCL

C / L

LCL

UCL

C / L

LCL

Control Chart for Uncontrolled State

Control Chart for Controlled State





Average chart (X)

52.031

52.035

52.039

52.043

1 3 5 7 9 11 13 15 17 19 21 23 25

Samples

Rea

ding

s

READINGS

USL

LSL

Xdbar

UCL XBAR

LCL XBAR

Examples of Control Chart :Examples of Control Chart :





How to Read Control Charts :How to Read Control Charts :

1) Out of control limits.

2) Run. SevenSeven--point length ofpoint length ofrun is abnormal.run is abnormal.

Ten out of 11 consecutiveTen out of 11 consecutivepoints occurring on onepoints occurring on oneside is abnormal.side is abnormal.

RunRun





How to Read Control Charts (contd.) :How to Read Control Charts (contd.) :

3)3) TrendTrend

Seven upward pointsSeven upward points Drastic downward trendDrastic downward trend





22--sigma linesigma line33--sigma linesigma line

33--sigma linesigma line22--sigma linesigma line


4)4) Approach to the control limits (2 out of 3 points)Approach to the control limits (2 out of 3 points)





33--sigma linesigma line1.51.5--sigma linesigma line

How to Read Control Charts :How to Read Control Charts :

5)5) Approach to the central line.Approach to the central line.






6)6) PeriodicityPeriodicity





0

4 4

9

34

38

9.9

4.52.5 2.5

0

5

10

15

20

25

30

35

40

0 3.3 3.35 3.4 3.45 3.5 3.55 3.6 3.65 3.7

HistogramHistogram





Histogram is a graphical representation of a

frequency distribution which is a summary of variation

in a product or process.

What is Histogram :What is Histogram :





Steps to construct the Histogram :Steps to construct the Histogram :1) Collect 100 reading.

2) Find out lowest and highest value of reading row wise.

3) Find out lowest and highest from all the rows.

4) Compute the range . R = Max - Min.

5) Follow standard table for no of classes.

No of Observations No of Classes ( k )< 50 6

51 - 100 7101 - 200 8201 - 500 9

501 - 1000 10





20

18

16

14

12

10

8

6

4

2

01 2 3 4 5 678 10 20 50 200 500 1,000

nn

kk

n - Numbers of Measurements.

Graph to Determine KGraph to Determine K





Steps to construct the Histogram :Steps to construct the Histogram :1) Calculate the approximate width of class with the help of

formula ( R + W ) / K

Where “ R “ is the range. “ W “ is accuracy in the observation

and “ K “ is no.of classes.Make the frequency table and then

draw the histogram.

-- NoteNote

1) Classes should be continuous.i.e 1-5,5-10,10-15 etc.

2) All classes should have same width.





Histogram data sheetHistogram data sheet

1 104.1 11 104.5 21 104.4 31 104.4 41 104.6

2 104.4 12 104.3 22 104.5 32 104.3 42 104.4

3 104.3 13 104.4 23 104.4 33 104.4 43 104.6

4 104.5 14 104.5 24 104.3 34 104.7 44 104.7

5 104.4 15 104.4 25 104.2 35 104.2 45 104.3

6 104.3 16 104.5 26 104.4 36 104.4 46 104.5

7 104.2 17 104.2 27 104.6 37 104.3 47 104.2

8 104.5 18 104.4 28 104.4 38 104.5 48 104.5

9 104.3 19 104.3 29 104.3 39 104.4 49 104.4

10 104.5 20 104.4 30 104.1 40 104.3 50 104.3





Tally Data SheetTally Data Sheet104.1 - //

104.2 - ////

104.3 - //// //// //

104.4 - //// //// //// /

104.5 - //// ////

104.6 - ///

104.7 - //





2

5

12

16

10

3 2

0

5

10

15

20

104.1 104.2 104.3 104.4 104.5 104.6 104.7

in mm

Examples of Histogram :Examples of Histogram :





1

2

3

4

5

6

MaximumLimit

MinimumLimit

MaximumLimit

MinimumLimit

Interpretation of HistogramInterpretation of Histogram





b) Comb type

c) Positively skew type d) Left–hand precipice type

Types of Histogram :Types of Histogram :

a) General type





Types of Histogram :Types of Histogram :

e) Plateau type f) Twin–peak type

g) Isolated–peak type





Uses of Histogram :Uses of Histogram :

1) To know the pattern of variation.

2) To assess states of control

3) To assess conformance to specifications

4) To assess spread or variation with reference to specification.

5) To assess process capability.

6) To get clues for bringing process under control - whether to shift mean or to reduce variation or both.

7) To get clues for possible assignable causes for observed variation -mixture of lots, suppliers, instruments /measurements errors, bias of written results etc.





0

10

20

30

40

50

A B C D E

16%

48%

18%12%

6%Q

ualit

y D

efec

tive

(Nos

)Q

ualit

y D

efec

tive

(Nos

)

Types of DefectTypes of Defect

StratificationStratification





Stratification is the process of separation of data into

categories. It is normally done for identifying the categories

contributing to the problem tackled.

What is Stratification :What is Stratification :





Types of Stratification :Types of Stratification :

0

10

20

30

40

50

A B C

16 %

48%

15%

SupplierSupplier

Def

ectiv

e %

Def

ectiv

e %

A.A. Material Based : Material Based :

Defective Quality Defective Quality -- Supplier Wise.Supplier Wise.





0

10

20

30

40

50

A B C D C

Types of Stratification :Types of Stratification :B.B. Quality Based : Quality Based :

Qua

lity

Def

ectiv

e(N

os)

Qua

lity

Def

ectiv

e(N

os)

Type of DefectType of Defect

Defects Data For Each Hour in a ShiftDefects Data For Each Hour in a Shift

16%

48%

18%12%

6%





0

5

10

15

20

25

30

A B C

5%

22%

3%

Types of Stratification :Types of Stratification :C.C. Worker Based :Worker Based :

No

of D

efec

tive

No

of D

efec

tive

WorkerWorker

Defective AssembliesDefective Assemblies





0102030405060708090

100

A B

43%57%

Types of Stratification :Types of Stratification :D.D. Machine Based :Machine Based :

Prod

uctio

n %

Prod

uctio

n %

MachineMachineProduction Machine WiseProduction Machine Wise





0

10

20

30

40

50

A B C D E

Types of Stratification :Types of Stratification :E.E. Processing Based :Processing Based :

Pow

er C

onsu

mpt

ion

%Po

wer

Con

sum

ptio

n %

Process AreaProcess AreaPower Consumption Process Area WisePower Consumption Process Area Wise

12%

32%25%

5%

26%





Scatter DiagramScatter Diagram

3.4

3.5

3.63.7

3.8

3.9

4

4.1

4.24.3

4.4

4.5

100 150 200 250 300 350 400 450 500 550 600 650

Ove

rall

ratin

g of

the

Sess

ion

Average Experience of Training Team (in days)

4.0 y axis430 x axis





What is Scatter Diagram :What is Scatter Diagram :

Scatter diagram is a graphical representation of

relationship between two variables. It can be between a Cause

and Effect and between causes.

In 1837 J.F.W.Herswchal,an Englishman, used scatter diagram.

In 1950s Dr.K.Ishikawa popularized the use of scatter diagram.





Steps to draw Scatter Diagram :Steps to draw Scatter Diagram :

1) Collect paired data (x,y)

2) Find the maximum and minimum values forboth the x and y.

3) Plot the data.

4) Enter all necessary items.





4.5

4.4

4.3

4.2

4.1

4.0

3.9

3.8

3.7

3.6

3.5150 200 250 300 350 400 450 500 550 600 650

Dependent variable (“effect”)

* Looking for relationshipsnot cause & effect

Independent variable (“cause”)

The measurement scales generally increase as you move up

the vertical axis and to the right on the horizontal axis.

The horizontal (x axis) and vertical (y axis) lines of the diagrThe horizontal (x axis) and vertical (y axis) lines of the diagram:am:





Ove

rall

ratin

g of

the

Sess

ion

Average Experience of Training Team (in days)

3.43.53.63.73.83.9

44.14.24.34.44.5

100 150 200 250 300 350 400 450 500 550 600 650

4.0 y axis430 x axis

Examples of Scatter Diagram :Examples of Scatter Diagram :





a. Positive relationship

b. No correlation.

c. Negative correlation.

d. Positive and Negative correlation.

e. Negative and Positive correlation.

Possibilities after plotting the pointsPossibilities after plotting the points





0

2

4

6

y

0 2 4 6 x0

2

4

6

y

0 2 4 6 x

n = 30 r = 0.9

Positive Correlation May Be Present

n = 30 r = 0.6

No Correlation

n = 30 r = 0.0

Positive Correlation

Negative Correlation

n = 30 r = 0.9

0

2

4

6

y

0 2 4 6 x

Negative Correlation May Be Present

0

2

4

6

y

0 2 4 6 x0

2

4

6

y

0 2 4 6 x

n = 30 r = 0.6





The Journey is Never Ending




7 qc tools-trg module- act--advance cluster

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