QC Tools Best

8/10/2019 QC Tools Best

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Stratification

Divide and Conquer


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Stratification

A technique used to divide data into

subcategories or classification to

provide useful insight into the

problem.


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Meaning of Stratification

Root Word is Strata which means

Group

Division

Subclass

Levels Layers

Stratification is an act of dividing databased on group, division, sub class,

causes etc.


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Rationale & Benefits

Data comes from difference sources.

E.g. : Different Machines, Instruments,Cities, Operators etc.

Data sometimes masks real

information.

Stratification helps in gettingmeaningful information from data.

Divide the data and Conquer theInformation.


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Reached late to office on following dates

(unstratified data) 2/7, 6/7, 9/7, 16/7, 23/7, 30/7

Stratified data by day of the week. Mon 5 Tue 0 Wed 0 Thu 0 Fri 1 Sat 0

Example : Late to Work


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Example : PCB Rejection

323033Rejection

5/64/63/6Date

Unstratified Data


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Example : PCB Rejection

1

0

3

10

Lunch1

2

1

153/6

0

2

1

11

0

0

2

144/6

14:30 5:30

13:30 4:30

02:30 3:30

121:30 2:30

1:00 1:30112:00 1:00

111:00 12:00

010:00 11:00

169:00 10:00 5/6Time

Stratified Data


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E.g. Accidents in Machine Shop

12

10

13

9

1112

0

2

4

6

8

10

12

14

Jan Feb Mar Apr May Jun

Month

No.ofA

ccidents


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After Stratification

98

12

8

1110

32

1 1 0

2

0

2

4

6

8

10

12

14

Jan Feb Mar Apr May Jun

Month

No.ofA

ccidents

Press Shop

Welding


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Steps in Stratification

1. List all conditions

2. Collect and Stratify Data

3. Interpret the Data


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Step 1 : List all Conditions

List all conditions that may seem to be

the cause of the problem.

Shift

Location

Raw Material Source

Operator

Product

Machine Inspection Equipment

Day of Week

Time of Day

Material Batch

Inspector

Production Batch


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Step 2 : Collect and Stratify Data

Collect additional data based on

classification, if necessary.

Stratify data based on the

classification


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Step 3 : Interpret the Data

Calculate average of each classification

or plot appropriate graph.

Look for significant differences OR

abnormalities in data.

Generate a list of possible causes.


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Pareto ChartVital Few and Trivial Many


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Pareto Chart

Pareto Chart is a diagram that shows the

order of the largest number of occurrences

by item or by classes, and the cumulative

sum total.


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Genesis of Pareto Chart

Vilfredo Pareto (1848

1923), an Italian economistdiscovered in 1897 that80% of a nations wealthwas owned by 20% of thepopulation.

Dr. Joseph M. Juranapplied this principle to

Quality Management andcalled it the ParetoPrinciple.


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Pareto Principle

20%

80%

Inputs

CausesEffort

Outputs

EffectsResults


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Rationale and Benefits

Pareto Principle : 80 % of the problems

comes from 20% of the causes.

Distinguishes between vital few and

trivial many.

Displays relative importance of causesof a problem.

Helps the team to focus on those causes

that will have the greatest impact whensolved.


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Causes for Starting Late to Office

0

20

40

60

80

100

120

140

Newspaper Bathroom

Delay

Overslept Garage

Door

Iron Clothes Others

Causes

Freq

uency

0%

20%

40%

60%

80%

100%

CumulativePercentage78%

C f S f D f t


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Causes for Surface Defects

0

20

40

60

80

100

120

140

160

Stain Scratch Peeling Crack Pinhole Gap OthersCauses

Frequ

ency

0%

20%

40%

60%

80%

100%

Cumulative

Percentage

84%

P t C t R


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Pareto on Customer ResponseWhat did you like least after the surgery ?

0

10

20

30

40

50

60

Waiting Nursing No Privacy No

Empathy

Pain No Info. Others

Causes

Frequency

0%

20%

40%

60%

80%

100%

CumulativePercentage

76%

St i ki P t Ch t


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Steps in making a Pareto Chart

1. Select the problem.

2. Collect data.3. Sort data & calculate cumulative

percentage.

4. Draw the axes.5. Construct the bars.

6. Draw the cumulative percentage line.

7. Title and label the chart.8. Identify Vital Few from the Trivial

Many and plan further action.


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Step 1 : Select the Problem

Select the problem for investigation.

Decide what data will be necessary and

how to classify them.

Determine the method of collecting data

and period of data collection.

Design a separate Check Sheet if

necessary.

Eg : Causes for Service Complaints ofComputer System.


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Step 2 : Collect Data

52Virus Attack

3Rodent Problem

12Others

5Loose Connection4Email not functioning

9Operating System Corrupted

3System Re-configuration

6Bad Configuration

8Boot Problems

23Server Crash

11Print Problems

FrequencyCauses

St 3 S t D t & C l l t


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Step 3 : Sort Data & CalculateCumulative Percentage

136Total

K

J

I

H

G

FE

D

C

B

A

Code

89%1213System Re-configuration

87%1184Email not functioning

84%1145Loose Connection

80%1096Bad Configuration76%1038Boot Problems

70%86+9=959Operating System Corrupted

75/136 = 55%52+23=7523Server Crash

52/136 = 42%5252Virus Attack

12

3

11

Freq-

uency

136

124

75+11=86

Cumulative

Freq.

91%Rodent Problem

100%Others

63%Print Problems

Cumulative

% age

Causes

St 4 C t t th A


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Step 4 : Construct the Axes

0

20

40

60

80

100

120

A B C D E F G H I J KCauses

Frequency

0%

20%

40%

60%

80%

100%

Cumulative

Percentage

136

136 = 100%

St 5 D th B


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Step 5 : Draw the Bars

0

20

40

60

80

100

120


Frequency

0%

20%

40%

60%

80%

100%

Cumulative

Percentage

136

Step 6 : Draw the Cumulative


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Step 6 : Draw the CumulativePercentage Line

0

20

40

60

80

100

120


Frequency

0%

20%

40%

60%

80%

100%

Cumulative

Percentage

136


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Step 7 : Label & Title the Chart

0

20

40

60

80

100

120


Frequency

0%

20%

40%

60%

80%

100%

CumulativeP

ercentage

136 Pareto of Service Complaints


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Step 8 : Interpret the Chart

0

20

40

60

80

100

120


Frequency

0%

20%

40%

60%

80%

100%

CumulativeP

ercentage

136 Pareto of Service Complaints

70%


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Flat Pareto ??

0

20

40

60

80

100

120


Frequency

0%

20%

40%

60%

80%

100%

CumulativeP

ercentage


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Tips for Making a Good Pareto

Chart It is undesirable that others represent

a high percentage (should be < 10%).

If the cause of a problem can be solved

easily, implement it even if it belongs to

the trivial many.

Wherever possible, compare monetary

data with frequency data.

Draw the Pareto chart before and afterimprovement.


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Which problem to solve ?

0

200

400

600

800

1000

1200

A B C D E F G H I J K

PP

M

0%

20%

40%

60%

80%

100%

0

20

40

60

80

100

120

140

D B C E A G F J I H K

Rs.in'000

0%

20%

40%

60%

80%

100%Rejections by PPM Rejections by Rs.

B f d Aft I t


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Before and After Improvement

0

10

20

30

40

50

60

Waitin

g

Nursin

g

NoPrivacy

NoEmpath

y

Pain

NoInfo.

Others

Causes

F

requency

0%

50%

100%

0

10

20

30

40

50

60

Nursing

NoPriva

cy

NoEmpathy

Waiting

Pa

in

NoInfo.

Othe

rs

Causes

F

requency

0%

100%

Improvement


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Brainstorming

Creativity at Work

B i t i


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Brainstorming

Creativity and Collective Wisdom at

Work Place.

Diagnose, Solve and Prevent

Problems and Effect Improvements

B i t i C td


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Brainstorming Contd..

Technique for a team to creatively

and efficiently generate the greatest

possible number of ideas on any

topic.

F th f B i t i


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Brainstorming was first

effectively used andintroduced by Alex F.

Osborn of U.S.A. in

1941.

An Advertisement Exe-

cutive.

Author of Book Applied

Imagination.

Father of Brainstorming

B i t i


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Brainstorming

Brainstorming is a conference technique

of solving specific problems, amassing

information, stimulating creative

thinking, developing new ideas by

unrestrained and spontaneous

participation in discussion.

The Random House Dictionary

R ti l d B fit


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Person close to the job knows more

about the job.

Encourages OPEN thinking.

Enables people to participate in acreative way.

Minimizes domination by a few people.

Self Fulfilling.

T f B i t i


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Types of Brainstorming

A process in which

each team member

give ideas in turn.

A process in which

each team member

give ideas as theycome to mind.

Brainstorming

Structured UnStructured

St f B i t i


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Stages of Brainstorming

1. Stating the Problem.

2. Re stating the problem.

3. Brainstorming.

4. Evaluating the ideas produced.

P R i it


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PreRequisites

Relaxed and cordial atmosphere.

Information to all members about the

theme of the session.

All ideas should be recorded and

recalled, if necessary.

All should participate.

Fo r R les of Brainstorming


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Four Rules of Brainstorming

Encourage Wild

IdeasQuantity rather

than Quality Ideas

Four Rules of Brainstorming


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Four Rules of Brainstorming Contd.

Ride on Anothers

Idea PiggybackSuspend Judgement

Guidelines and Ground Rules


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Freewheeling is encouraged.

Wilder, Offbeat, Erratic, Stupid, Trailblazing, Impractical ideas are welcomed

Be open minded

Spontaneity required

Evoke fun atmosphere

Heart rules over Head



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Judgement Suspended.

Criticism Ruled out. Participation by All.

Quantity is encouraged. Structured or Unstructured.

Combination and Improvement ofIdeas. Cross Fertilisation.

Piggyback.

Six Persons - Six Minutes Formula.

Guidelines and Ground Rules Contd..


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Cause and Effect

DiagramIdentify and Cure Causes

Cause and Effect Diagram


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Cause and Effect Diagram

A diagram which representsmeaningful relationship between an

effect and its causes.

A diagram which shows the relation

between a Quality Characteristic

and the Cause Factors.

JIS Definition



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Enables a team to identify, explore and

graphically display all the possiblecauses related to a problem.

A cause and effect diagram is good forseeing the whole causal relationship.

Enables identification of root causesand not symptoms.

Father of Cause & Effect Diagram


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Father of Cause & Effect Diagram

Dr. Kaoru Ishikawa developed

the first cause and effect

diagram in 1943 while

consulting for Kawasaki Steel

Works.

Dr. Juran named it as

Ishikawa diagram.

Structure of C & E Diagram


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Structure of C & E Diagram

Effect

(Characteristic)

Big Bone

Back Bone

SmallBone

Medium SizedBone

Causes (Factors)

C & E Diagram is also known as


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C & E Diagram is also known asFishbone Diagram

Three Types of Cause and Effect


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Three Types of Cause and EffectDiagram

1. Dispersion Analysis type.

2. Process Flow Classification type.

3. Cause Enumeration type.

Note : Dispersion Analysis type andCause Enumeration type differ onlyin the method of construction.

Dispersion Analysis type Cause and


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p y ypEffect Diagram

workersMaterials

Wobble

ToolsInspection

Over

experienced

Experienced

Under-experienced

Personality

Content

Training

Knowledge

6.4

Small Large

Centralaxle

Material Quality 11.6

Uneven

F Cover

Axle holeInterval Loose Tight

Nuts

Threads

Material quality

G axle bearing

Large

6

2.6Size

9

MeasurementMeasuringtool

Errors

Judgement

Judgement

method

Training

Inspector

Experience

Off-centre

Adjustment Off-centre

Cover hole

G axle bearing cover

PlatingUneven

F cover

Punch width

F axle cover

Axle stopMetal drill

G axle cover

Process Flow Classification type


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ypCause & Effect Diagram

MaterialPipe

making CorrectingPlanning

WaterPressure

test

Bed

removingInspection

SteelPipe

scarsBench rolling

Movement

Polishing

Weight

Wire

Bunching

Arrange bench drop

Polish

Value

Movement

Difference

Weight

Carriage

Surface paint

Bench rolling

Position placement

Position placement

Group movement

Bench movement

Common aberration

Bunching

Loosening

Dropping

Bench movement

Conveyor

Roll

Flare

Impurity

Steps in Constructing Dispersion


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p g ptype C & E Diagram

1. State the undesirable effect.

2. Identify the main cause groups.

3. Identify causes and subcauses.

4. Identify potential root cause(s).

Step 1


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Step 1

State the undesirable effect and draw

the back bone and draw a line.

High Process

Rejection

EffectCauses

Step 2


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Step 2

High Process

Rejection

Machine Man

Material Method

Identify the main cause groups such as

man, machine, method, material,

measurement, tool.EffectCauses

Step 3


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Step 3

High Process

Rejection

Machine Man

Material Method

Identify the causes and sub causes.

Ask WHY several times.

High

Hardness

Not Specified

to VendorRod

Bent

Poor

Handling

No Inspection

EffectCauses

Step 4


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Step 4

High Process

Rejection

Machine Man

Material Method

Identify potential root cause(s).

High

Hardness

Not Specified

to VendorRod

Bent

Poor

Handling

No Inspection

EffectCauses

Identify Significance of Each Cause


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Identify Significance of Each Cause

High Significance

Moderate Significance

Weak Significance

Steps in Constructing Process Flow


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p gType C & E Diagram


2. Draw the main process flow diagram.

3. Identify the cause and subcauses at

each stage of the process.


Step 1


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Step 1

State the undesirable effect and draw a

verticle line.

Delay inDelivery

EffectCauses

Step 2


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Step 2

Draw the main process flow.

Delay inDeliveryMaterialReceipt Machining Assembly Inspection

EffectCauses

Step 3


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Step 3

Identify the cause and subcauses at each

stage of the process.

Delay in

Delivery

Material

ReceiptMachining Assembly Inspection

MaterialShortage

Material

Rejected

Vendor Tool

Damaged

MachineBreakdown

Capacity

Constraint AbsenteeismIncomplete

Assembly

High Cycle

TimeRectification

EffectCauses

Step 4


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Step 4

Identify potential root cause(s).

Delay inDelivery

MaterialReceipt

Machining Assembly Inspection

Material

Shortage

Material

Rejected

Vendor Tool

Damaged

MachineBreakdown

Capacity

Constraint AbsenteeismIncomplete

Assembly

High CycleTime

Rectification

EffectCauses

Steps in Constructing CauseC &


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gEnumeration Type C & E Diagram


2. List all possible causes using

brainstorming.

3. Arrange causes and subcauses showing

the relationship between cause and effect.


Step 1


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Step 1

State the undesirable effect.

Time for

Installation

of Machine

is High

Step 2


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Step 2

List all possible causes using brainstorming.

Parts notavailable on

timeDo not have

license

for stamping

Relevant Forms

not received

Performance

problems

during installation

Payment not

collected as per terms

Poor follow-up

by branch

Lack of

Funds

Civil work

notcommenced

No communication

to branch on civil

work

Customers

ProjectPostponed

Lorry not

available

Customer wants

see our installation

Time for

Installation

of Machine

is High

Step 3


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HO DelayBranch

Delay

Customer

DelayOthers

Parts not avai-

lable on timeDo not have license

for stampingPerformance problems

during installationPayment not


Poor follow-up

by branch

Poor information

on site readiness

Lack of Funds

Civil work notcommenced

No communication

to branch on civil

work

ProjectPostponed

Lorry not

availableCustomer wants


Time for

Installationof Machine

is High

Relevant Forms

not received

pArrange causes and subcauses suitably.

EffectCauses

Step 4


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pIdentify potential root cause(s).

HO

Delay

Branch

Delay

Customer

DelayOthers

Parts not avai-

lable on timeDonot have license

for stampingPerformance problems

during installationPayment not


Poor follow-up

by branch

Poor information

on site readiness

Lack of Funds

Civil work notcommenced

No communication

to branch on civil work

ProjectPostponed

Lorry not

availableCustomer wants


Time for

Installationof Machine

is High

Relevant Forms

not received

EffectCauses

Hints for Constructing a C & E


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gDiagram

Identify all the relevant causes

(factors) & the causes most strongly

influencing the effect (characteristic).

Express the effect (characteristic)

negatively.

The linking question between effect

and its cause is WHY ?.

Make the same number of cause andeffect diagrams as that of effects.


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Identifying Correlation

Scatter Diagram

Scatter Diagram


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A chart used to study and identify the

possible relationship between two

variables.

Scatter Diagram Contd..


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g

To identify the possible relationship

between the changes observed in twovariables.

To establish the Existence of correlation

Type of correlation

Strength of the relation



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To confirm a hypothesis (assumption) that

two variables are related.

Provide both visual and statistical means to

test the strength of a potential relationship.

Provide a good follow up to a cause and effect

diagram to find out if there is more than just

a consensus connection between causes andeffects.

Examples of Two Variables


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Cake height and Oven temperature.

Weight and Height of a person.

Population & Literacy levels in a state.

Weight error and Earthing voltage.

Nonconformance & Operator experience

Examples of Two Variables Contd


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Contd..

Hardness & Carbon content

Inspection Mistakes & Illumination levels

Elongation of threads & Moisture content

Childs height & Fathers height

Quality characteristic and the Factor

affecting it.

Weight & Height of a Person


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40

50

60

70

80

90

100

110

155 160 165 170 175 180 185 190

Weight(kg)

Height (cm)

Capacitance & Line Width


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0.5

1

1.5

2

2.5

3

3.5

30 40 50 60 70 80

Capacitanc

e(Pictofar

ads)

Line Width / Spacing (in microns)

Steps in making a Scatter Diagram


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p g g

1. Collect paired data.

2. Choose independent and dependent variable.

3. Draw the axes.

4. Plot the points

5. Label and title the chart

6. Interpret the chart.

Step 1: Collect Data


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Collect 50 100 paired data (X,Y) betweenwhich you want to study the relation, and

construct a data sheet

3.3 cm68o60...

...

3.0 cm57o32.8 cm49

o

2

3.2 cm60o1

Cake HeightOven TemperatureSample

Step 2 : Choose Independent andDependent Variables


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Dependent Variables.

Always choose X axis for the cause

and Y axis for the effect, when the two

variables consist of a factor and

quality characteristics.

Oven Temperature = Independent Cake Height = Dependent

Find the respective maximum andminimum values of the variable.

Step 3 : Draw the Axes.


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2

2.5

3

3.5

4

4.5

5

3 5 4 0 4 5 5 0 5 5 6 0 6 5 7 0

Independent Variable,Oven Temperature

Dependent Variable,

Cake Height

Step 4 : Plot the data


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2

2.5

3

3.5

4

4.5

5

35 40 45 50 55 60 65 70

Step 5 : Label & Title the chart


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Oven Temperature vs. Cake Height

Oven Temperature (oC)

CakeHeight(cm)

2

2.5

3

3.5

4

4.5

5

35 40 45 50 55 60 65 70

Step 6 : Interpreting the Chart


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Strong Positive Correlation

Increase in x, will increase y

1

1.5

2

2.5

3

3.5

35 40 45 50 55 60 65 70

Variabley,Dependent

Variable x, Independent

Step 6 : Interpreting the Chart Contd


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Contd..Strong Negative Correlation

Increase in x, will decreasey

-3.5

-3

-2.5

-2

-1.5

-1

35 40 45 50 55 60 65 70

Variabley,Dependent




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Contd..

1

1.5

2

2.5

3

3.5

35 40 45 50 55 60 65 70

Positive Correlation

Increase in x, may increasey

Va

riabley,De

pendent


Step 6 : Interpreting the Chart Contd..


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Contd..

-3.5

-3

-2.5

-2

-1.5

-1

35 40 45 50 55 60 65 70

Negative Correlation

Increase in x, may Decreasey

Variabley,De

pendent




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Contd..

1

1.5

2

2.5

3

3.5

30 35 40 45 50 55 60 65 70

No Correlation

V

ariabley,D

ependent



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Control Chart


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It is a type of run chart used for

studying process performance over

time in order to understand and

reduce variation.

Father of Control Chart


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Dr. Walter A. Shewhart

invented the control chart.

He was working in BellLabs on a project to make

all telephones alike.

Published the bookEconomic Control of

Quality of ManufacturedProductin 1931.

Principles of Variation


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1. Every process is subject to variation.

2. More the variation in the process, more

the loss to society.

3. Two types of causes affect variation.

a. Common Cause (also known as

Chronic cause, Chance cause)

Principles of Variation Contd..


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b. Special Cause (also known as

Sporadic cause, Assignable cause)

4. Action on variation entirely depends on

type of cause identified.

Common Cause


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The cumulative effect of many small and

individually uncontrollable causes of

variation in a process.

Special Cause

One or a few causes of variation thatresult in a large variation in the process.

Common vs. Special Cause


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Common Cause

Consists of manyindividual causes.

Results in relativelysmaller variation.

Process need not betampered with.

Process is consi-dered stable.

Special Cause

Consists of one or afew causes.

Results in largevariation.

Process needs to beinvestigated andcorrected.

Process is unstable.



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Control chart is used fordifferentiating between commoncauses and special causes of variation.

Control chart also helps in

determining whether the process is stable.

process is capable.

It helps in predicting processperformance.

Types of Data


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Variable Data

Data that can be measured.E.g.: Weight, Length, Diameter,

Hardness, Angle.

Attribute Data

Data that can be counted.

E.g.: Defects, Scratches, Dent, Spatters,

Blow holes, cracks.

Classification of Control Chart


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Control Chart

Variable Data

X R ChartX mR chart

mX mR Chart

Attribute Data

p chartc chart

np chart

u chart

Example of Control Chart


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24.75

25.00

25.25

25.50

25.75

26.00

26.25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Diameter(mm)

0.0

0.5

1.0

1.5

2.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Sub-group

R

ange(mm)

UCLx

LCLx

X

UCLR

LCLR

R

Parts of a Control Chart


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24.75

25.00

25.25

25.50

25.75

26.00

26.25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

X Axis

Variable Data

UCLx

LCLx

X

Sub-Group Control

Limits

Central

Line

Data Points

Diam

eter(mm)

Definition of Terms


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Sub Group

Smaller groups of sample data collectedover time.

Central Line The average of all the sub group

averages.

Control Limits

The outer limits of Process Variation.

Control Limit vs. Specification Limit


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Control Limit

Variation in the

process.

Noise of theprocess.

Limits change withsetting, correction,process changes etc.

Indicates Capability.

Specification Limit

Requirement of the

customer.

Voice of thecustomer.

Limits change onlywhen customerwishes to change.

IndicatesRequirement.

Steps in Constructing a ControlChart


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Chart

1. Collect the data.

2. Calculate subgroup average.

3. Calculate overall average.

4. Calculate the range.

5. Compute average of range.

6. Calculate control limits for X and R

7. Plot the chart.8. Interpret the chart.

Step 1: Collect Data


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Collect and stratify data into sub-groups.

59

11

25

35

X4

384229284

441611293

343137192

204432471

X5X3X2X1Sub-Group

Step 2: Calculate SubgroupAverage,X


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where n is the size of the subgroup.

nXXXXXX 543211

6.355

20354432471 X

Average, X

Step 3: Calculate the OverallAverage X


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k

XXXXX

4321

4

2.392.222.296.35 X

where k is the number of subgroups.

Average,X

Step 4: Calculate the SubgroupRange, R


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Range, R

R = Maximum Value Minimum Value

R1 = 47 20 = 37

Step 5: Calculate the Average ofRanges,R


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kRRRRR

4321

25.274

31331827

R

where k is the number of subgroups.

Ranges,R

Step 6: Compute Control Limits


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Control Limits for chart

Central Line =

Upper Control Limit :

Lower Control Limit :

A2 is the coefficient whose value depends onthe subgroup size

X

X

RAXUCLX 2

RAXLCLX 2

Step 6 : Control Limits for R Chart


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Central Line :

Upper Control Limit :

Lower Control Limit :

D3

and D4

are coefficients whose value

depend on the subgroup size.

RDUCLR 4

RDLCLR 3

R

Step 6: Coefficients for R chartX


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2.5342.00400.4836

2.3262.11400.5775

2.0592.28200.7294

1.6932.57401.0233

1.1283.26701.8802

d2D4D3A2n

R ChartChartSubgroup

Size

X

Step 7 : Plot the Control Chart


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Vertical Axis: and R values

Horizontal Axis : Subgroup number

Draw the central line : and R.

Draw the control limit lines.

X

X

Step 7 : Plot the Control Chart Contd..


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Plot the and R values and join the

points.

Write necessary items like name of the

process, product, size of the subgroup,work conditions, shift, etc.

X

Step 8 : Interpret the chart


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Process Stability

Look at the patternof variation.

Should be random

and not a systematic

pattern.

Look for presence of

special causes.

5 rules of special

cause identification.

Process Capability

Establish process

variation.

Compare with

customer speci-

fication and

establish process

capability.

Stable Process


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

- Random variation and no systematic pattern- No action required (if Cpk > 1.67)

Rule 1: Points beyond Control Limit


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

- Presence of special cause- Identify root cause and take action.

Rule 2: Run of 7 points on one sideof Central Line


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- Presence of special cause- Process has shifted.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

Rule 3: Six Consecutive PointsIncreasing or Decreasing


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g g

- Presence of special cause- Process is deteriorating.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

Rule 4: Periodicity


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- Presence of special cause- Periodic Interference in the process.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

Rule 5: Fourteen ConsecutivePoints Alternating Up and Down


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- Presence of special cause.- Identify root cause and take action.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

XbarorR

Process Capability


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Process Capability is a measure ofinherent variability of the process

when compared with the customerrequirements.



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Assess capability of a process to meet

customers requirement.

Assist in selecting or modifying aprocess.

Assist in selection of machine.

To build quality into the product andprocess rather than achieving qualityby inspection.

Process Capability Assessment


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Establish Process Variation

Process Variation = 6

d2 is a constant based on sub groupsize.

Refer slide number 101 / PST&T / O - 22

2d

R

Compare with CustomerSpecification


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LSLUSL

Cp 6

Capability =Customer Requirement

Process Variation

Cp > 1.33; Process is more capable

than customer requirement

Compare with CustomerSpecification Contd..


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Cp = 1.0; Process is just capable of

meeting customers require-ment

Cp< 1.0; Process is not capable of meeting

customers requirement

Compare with CustomerSpecification Contd..


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3)(

;3

)( LSLXXUSL

MinimumCpk

Cpk = Cp; Process is centred with respect

to customers requirement.

Cpk Cp; Process is NOT centred with

respect to customersrequirement.

Accidents in a Factory


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Total Accidents : 94

A - Accidents with respect to Head : 1

B - Accidents with respect to Face : 3

C - Accidents with respect to Body : 7

D - Accidents with respect to Hand : 9

E - Accidents with respect to Fingers : 69

F - Accidents with respect to Leg : 5

94

Cause PercentagePercentage Cummulative


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e ce tage Cu u at ve

Percentage

E 69 / 94 x 100 = 73.40% 73.40 %

D 9 / 94 x 100 = 9.57% 82.97 %

C 7/ 94 x 100 = 7.45% 90.42 %

F 5 / 94 x 100 = 5.32% 95.74%

B 3 / 94 x 100 = 3.19% 98.93%

A 1 / 94 x 100 = 1.07% 100.00%

100.00%

Pareto Chart90


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69

9 7 5 3

10

10

20

30

40

50

60

70

80

E D C F B A Causes

Frequency

73.4%

E : VITAL FEW D, C. F. B, A = TRIVIAL MANY

Pareto Chart


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VITAL FEW FROM TRIVIAL MANY

A PCB Rejected 30% @ Wave Soldering Stage

Causes :

A - Wrong Mounting - 3

B - Compt Missing - 2

C - Dry Solder - 16

D - Compt Jumping - 8

E - Wrong Polarity - 1

30

Pareto Chart


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Rearranging the same

Causes :

C 16 16 / 30 * 100 = 53.33% 53.34%

D 8 8 / 30 * 100 = 26.66% 80.00%

A 3 3 / 30 * 100 = 10.00% 90.00%

B 2 2 / 30 * 100 = 6.66% 96.66%

E 1 1 /30 * 100 = 3.33% 100.00%

Pareto Chart30

100%


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16

8

32

1

0

5

10

15

20

25

C D A B E

Causes

Fr

equency

80

C + D : 80%

A, B, E : 20%

90

96.6 100%

Percentage

Pareto Chart


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Eg : A casting machine had 32% rejection

Causes :

A Due to Workmanship : 3

B Due to Casting Quality : 8

C Due to Cutter Problem : 18

D Due to Machine problem : 2

E Due to Miscellaneous causes : 1

32

81.25%

Pareto Chart

Data Structuring


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Data Structuring

96.876.25312D

100.003.13321E

90.629.37293A

81.2525.00268B

56.2556.251818C

Cummulative

Percentage

PercentageCummulative

Total

NumberItem

Pareto Chart40 100


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12

3

8

18

0

5

10

15

20

25

30

35

C B A D E

0

20

40

60

80

81.25

C + B : 81.25% = Vital few

A, D, E = Trivial many

90.62 96.87

Cummulativ

ePercentage

56.25

25

9.37

6.25 3.13

Perc

entage

Cause & Effect Diagram


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Performance Planning

QualityHigh

Turnover

Monitoring

Identify

Assessment

Monitoring

Resignations

Transport

ExcessiveOvertime

Line Balance

Capacity

Efficiency

Bottle Neck

Scheduling

MRPWork Load

Shortage

RejectionsQC

Training

Rework

QC

Mgmt. Style

Scheduling

Wages

Environment

Cause & Effect Diagram depictingthe causes for Divorces

Family


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Divorce

Staying away

Incompatibility

Family

PressureEgo

Work

Sexual

Thought

Religious

Cultural

Social

Family

Demands(Like Dowry)

Over family

affiliation by

either spouse

Disliking FamilyMembers

Family

Torture

Popularity

Successful

Profession

Superior

Education

Special Talent

Rich Family

Background

Sexual

Monetary

Materialistic

Behavioural

Non

availability

PopularityInsecurity

Inability to

earn

Greed

Miser

Spend

Thrift

Spirituality

Affairs

Workaholic

CharacterIllness

(Like mental, psychological)

Failure in

expectations

Over

Possessiveness

Money

Distractions

Personal

Q.C.C - Case Studies

R d i R j ti


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Reducing Rejections

Reducing Cycle Time

Reducing Consumables Cost

Reducing Energy Cost

Design Change

Improving manufacturing process

Eratic behaviour of machine

Elimination of canteen Coupons

Q.C.C - Case Studies

f A


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Elimination of Leave Application

Elimination of mosquito menace in the colony

Raising blood donations

Reducing accidents

Improving management education

Improving security of goods in an organisation

Improving Environment of Organisation

Improving Safety provisions

Otto Bilz India Pvt. Ltd.World Class Manufacturing Goals &

Targets


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Targets

9.5 in 10

scale

9.0 in 10

scale

8.5 in 10

scale

To be measuredSupplier Satisfaction5.

9.5 in 10

scale

9.0 in 10

scale

8.5 in 10

scale

To be measuredEmployee Satisfaction4.

9.5 in 10

scale

9.0 in 10

scale

8.5 in 10

scale

7.3 in 10 ScaleCustomer Satisfaction3.

100%>98%>95%43.05%On time Delivery2.

100 PPM500 PPM2000 PPM43545 PPMQuality level1.

200520042003Present / 2002Goals

Sl.

No.

Targets


Targets


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Targets

40%35%25%16%New customer for

existing productNew product for

existing customer

10.

7 man-days

/ Employee

6 man-days

/Employee

5 man-days

/ Employee

5 man-days @

35%

Training Hrs /

Employee / Year

9.

1000 Nos.600 Nos.300 Nos.0Suggestion /Kaizen

8.

120 Nos.100 Nos.60 Nos.0SGA7.

>85%>75%>65%43%OEE6.

200520042003Present / 2002Goals

Sl.

No.

Targets


Targets


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Targets

ISO 14001 /TS 16949

OSHAS

PreparationCertification15.

30 days40 days45 days69 daysDebtors Turnover

Ratio

14.

160 hrs140 hrs125 hrs80 hrsStd hrs cleared /

Employee / month

13.

25 crores15 crores10 crores8 croresSales Turn over12.

251583.95Inventory Turn

over ratio

11.

200520042003Present / 2002Goals

Sl.

No.

Targets

Otto Bilz India Pvt. Ltd.World Class Manufacturing

Goals & Targets


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Goals & Targets

Rs.50000

@ 0.02

Rs.1 lakh

@ 0.07%

Rs.3 lakhs

@ 0.3%

Rs.4300000

@ 5.3%

Quality cost / Sales20.

5 Sigma4 SigmaInitiationThree6 Sigma19.

NilDeming Award18.

Award2006

Preparation

NilCII Excellence

award

17.

Golden

peacock

Implemen-

tation

NilGolden peacock

award

16.

200520042003Present / 2002Goals

Sl.

No.

Targets

Otto Bilz India Pvt. Ltd.World Class Manufacturing

Internal Goals & Targets


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Internal Goals & Targets

30%15%

20%

5%

7.04.53.252.14 lakhsValue added Per Employee5.

3%3.5%4%5%Energy cost to sales4.

-5%EVA % to Expected return3.

25%15%-1.3%Operating profit % to sales2.

02530 nos.Customer complaints1.

200520042003PresentGoals

Sl.

No.

Targets

EVA : Economic Value Addition

What is Kaizen ? Kaizen means continuous improvement


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Kaizen is basically small small improvements

carried out by the person who is doing the job in hisday to day work

Continuous improvement everyday throughinvolvement of everyone in the organisation is thekey for excellence.

Piling small improvements on top of each other

What is Kaizen ?The Kaizen philosophy implies that :


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Whatever we do can be continuously improved-be it

our working life or personal life.

Kaizen is something that anybody can do, everyoperator must devote time for making

improvements.

Kaizen means looking at everyday work in a newway, seeking out area, aspects of work to improveupon, it represents the struggles on the job, and the

means adopted to overcome these struggles withintuition, creativity, resourcefulness, common senseand determination to break the status quo.

What is Kaizen ? Kaizen in essence, means adopting a new way, not


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just of doing work, but a new way of thinking, one in

which problems are not shunned but eagerly sought

out, welcomed and solved.

Kaizen means creating a place where

employees feel better at work.

- Y. Yasuda

KAIZEN INNOVATIONBig StepsSmall Steps


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Technological Breakthrough

Investment

Result-Oriented

Fast-Growth Economy

Conventional Know-How

Efforts

Process-Oriented

Slow-Growth Economy

Cultural Differences Between Kaizenand Traditional Organisations

TraditionalKaizenItemSl


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RejectionTreasuresProblem focus of

solutions

8.

Critical of shop

floor

Serving Shop FloorSupport staff7.

End result onlyTrends of

Improvement

Measurements6.

Problem / Failure

Source

Improvement SourceShop floor (GEMBA)4.

Static and RoutineConstant ImprovementShop floor methods5.

CostsAssetsView of people3.

Product-OutMarket-InView of customer2.CrisisPreventiveManagement Culture1.

TraditionalKaizenItemSl.

No.

Cultural Differences Between Kaizenand Traditional Organisations

T aditio alKai eIteSl


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Functional control

Results only.Routine short term

Cross Functional

Support ProcessResults change long

term

Management Concern16.

Fast / SkimmingSlow / BroadeningMovement15.

InspectorCoachCareer approach14.

Do as toldOn-going learningDevelopment12.

SpecialiseDespecialiseSupervision13.

AdversaryPartnersAppraisal Unions11.

WeaknessStrengthsApproach to Employee10.Restricted / ClosedShared / OpenInformation9.

TraditionalKaizenItemSl.

No.


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Market-In

TQC

Industrial Robots

QC Circles Suggestion System

Automation

Discipline in the workplace

TPM

Kanban

Quality Improvement

Just-In-Time

Zero Defects

Small Group Activities

Labour-Management Relations

Productivity Improvement

New-Product Development

Documents

QC Tools Best