1_Introduction to Six Sigma

IBM-09: Six Sigma Tools and Techniques

A. Ramesh PhD

Department of Management Studies

Indian Institute of Technology Roorkee

[email protected]

Lecture 1: Introduction

Class Venue and Time

Room No.LHC204

Monday From 8 AM - 8.55 AM

Wednesday - From 8 AM - 8.55 AM

Friday - From 8 AM - 8.55 AM

Welcome!!!

About me!!!

Flow of Presentation

1. Course content

2. Evaluation scheme

3. Six Sigma

4. Definition of quality

5. Dimensions quality

6. History of quality

1. Course content

Module 1(10 Hours) - Introduction

History, definition, dimensions, responsibility for quality

Six Sigma Basics Overview & Implementation

Define phase, Measure phase, Process Flow Charting/Process Mapping

Basic Tools

Probability

Overview of Distributions and Statistical Process

Probability and Hazard Plotting

Six Sigma Measurements

Basic Control Charts

Process Capability and Process Performance Metrics

Module 2 (12 Hours) - Six Sigma Analysis Phase

Visualization of Data,

Confidence Intervals and Hypothesis Tests,

Inferences : Continuous Response,

Inference : Attribute (Pass/Fail) Response,

Comparison Tests : Continuous Response, Comparison Tests : Attribute (Pass/Fail) Response,

Bootstrapping,

Variance Components,

Correlation and Simple Linear Regression,

Single Factor (One Way) Analysis of Variance (ANOVA) and Analysis of Means (ANOM),

Two-Factor (Two-Way) Analysis of Variance,

Multiple Regression

Logistic Regression, and Indicator Variables.

Module 3 (10 Hours) - Six Sigma Improve Phase

Benefiting from Design of Experiments (DOE)

Understanding the Creation of Full and Fractional Factorial

2K DOEs

Planning 2K DOEs Design and

Analysis of 2K DOEs

Response Surface Methodology

Module 4 (10 hours) - Lean Six Sigma

Lean and its Integration with Six Sigma process,

Integrating of Theory of Constraints

Design for Six Sigma Manufacturing applications, Service/Transactional Applications

DFSS Overview and Tools

Product DFSS, Process DFSS

Management of Six Sigma

Change Management

Project Management and Financial Analysis, Team Effectiveness, Creativity

References

S.

No.

Name of Authors/Book/Publisher Year of

Publication

/ Reprint

1 Breyfogle, Forrest: Implementing Six Sigma : Smarter Solutions Using

Statistical Methods, New York John Wiley & Sons

1999

2 Harry, Mikel and Rich Schroeder, Six Sigma : The Breakthrough Management

Strategy Revolutionizing the Worlds Top Corporations, New York

Doubleday

2000

3 Besterfield, D C and Besterfield C, Total Quality Management, Pearson

Education Asia

1999

4 Montgomery, D.C, Statistical Quality Control- A modern introduction, 6th

Edition, Wiley India

2010

5 Feigenbaum, Total Quality Control, 3rd Edition, McGraw Hill 1991

6 Hansen B L, and Ghare P M, Quality Control and Application, Prentice Hall

India

1993

2. Evaluation Scheme

Evaluation Scheme

Midterm Evaluation : 35 %

End Term Evaluation : 50 %

Mini Project : 10 %

Surprise Quizzes : 05 %

What is six sigma?

Six Sigma is. . .

A performance goal, representing 3.4 defects for every million opportunities to make one

A series of tools and methods used to improve or design products, processes, and/or services

A statistical measure indicating the number of standard deviations within customer expectations

A disciplined, fact-based approach to managing a business and its processes

A means to promote greater awareness of customer needs, performance measurement, and business improvement

Whats in a name?

Sigma is the Greek letter representing the standard deviation of a population of data.

Sigma is a measureof variation

(the data spread)

What does variation mean?

Variation means that a process does not produce

the same result (the Y)

every time.

Some variation will exist in all processes.

Variation directly affects customer experiences.

Customers do not feel averages!

-10

-5

0

5

10

15

20

Measuring Process PerformanceThe pizza delivery example. . .

Customers want their pizza delivered fast!

Guarantee = 30 minutes or less

What if we measured performance and found an average delivery time of 23.5 minutes? On-time performance is great, right? Our customers must be happy with us, right?

How often are we delivering on time?Answer: Look at

the variation!

Managing by the average doesnt tell the whole story. The average and the variation together show whats happening.

s

x

30 min. or less

0 10 20 30 40 50

Reduce Variation to Improve Performance

Sigma level measures how often we meet (or fail to meet) the requirement(s) of our customer(s).

s

x

30 min. or less

0 10 20 30 40 50

How many standard

deviations can you

fit within

customer

expectations?

4.20

The Empirical Rule If the histogram is bell shaped

Approximately 68% of all observations fall

within one standard deviation of the mean.

Approximately 95% of all observations fall

within two standard deviations of the mean.

Approximately 99.7% of all observations fall

within three standard deviations of the mean.

21

Empirical Rule

Data are normally distributed (or approximately normal)

1 2

395

99.7

68

Distance from

the Mean

Percentage of Values

Falling Within Distance

4.22

Chebysheffs TheoremNot often used because interval is very wide.

A more general interpretation of the standard deviation is derived from

Chebysheffs Theorem, which applies to all

shapes of histograms (not just bell shaped).

The proportion of observations in any sample that lie within k standard deviations

of the mean is at least: For k=2 (say), the theorem states that at least 3/4 of all observations lie within 2 standard deviations of the mean. This is a lower bound compared to Empirical Rules approximation (95%).

Centered normal distribution between Six Sigma limits

23

Effects of a 1.5 shift

24

The Six Sigma Evolutionary Timeline

1736: French mathematician Abraham de Moivre publishes an article introducing the normal curve.

1896: Italian sociologist Vilfredo Alfredo Pareto introduces the 80/20 rule and the Pareto distribution in Cours dEconomie Politique.

1924: Walter A. Shewhart introduces the control chart and the distinction of special vs. common cause variation as contributors to process problems.

1941: Alex Osborn, head of BBDO Advertising, fathers a widely-adopted set of rules for brainstorming.

1949: U. S. DOD issues Military Procedure MIL-P-1629, Procedures for Performing a Failure Mode Effects and Criticality Analysis.

1960: Kaoru Ishikawa introduces his now famous cause-and-effect diagram.

1818: Gauss uses the normal curve to explore the mathematics of error analysis for measurement, probability analysis, and hypothesis testing.

1970s: Dr. Noriaki Kano introduces his two-dimensional quality model and the three types of quality.

1986: Bill Smith, a senior engineer and scientist introduces the concept of Six Sigma at Motorola

1994: Larry Bossidy launches Six Sigma at Allied Signal.

1995: Jack Welch launches Six Sigma at GE.

Six Sigma Companies

Six Sigma and Financial Services

4- Definition of Quality

Definition of Quality

Perfection

Providing a

good usable

productConsistency

Elimination

of waste

Fitness for

use

Doing it

right the first

time

Delighting or

pleasing the

customer

Total

Customer

Service and

satisfaction

Defining Quality

Quality is a predictable degree of uniformity and

dependability, at low cost and suited to the market

Deming

Quality is fitness for use

Juran

Quality is conformance to requirements

Crosby

30

Defining Quality

The degree to which a set of inherent

characteristics fulfills requirements.

ISO 9000:2000

31

Quality can be Quantified

Q = P/E

Where Q = Quality

P = Performance

E = Expectations

If Q is greater than 1.0, then the customer has a

good feeling about the product or service.

32

What Is Quality?

The degree of excellence of a thing

(Websters Dictionary)

The totality of features and characteristics

that satisfy needs ( ASQC)

Fitness for use

Modern definition of quality

Quality is inversely proportional to variability

5. Dimensions quality

36

Dimensions of Quality (Garvin (1987) 1. Performance

Will the product do the intended job?

2. Reliability

How often the product fail?

3. Durability

How long the product last?

4. Serviceability

How easy it to repair the product?

5. Aesthetics

What does the product look like?

6. Features

What does the product do?

7. Perceived quality

What is the reputation of the company or its product?

8. Conformance to standards

is the product made exactly as the designer intended?

Service Quality Dimensions and

Examples

Dimension Examples

1. Tangibles Were the facilities clean, personnel neat?

2. Convenience Was the service center conveniently located?

3. Reliability Was the problem fixed?

4. Responsiveness Were customer service personnel willing and able

to answer questions?

5. Time How long did the customer wait?

6. Assurance Did the customer service personnel seem

knowledgeable about the repair?

7. Courtesy Were customer service personnel and the cashier

friendly and courteous?

DMAIC The Improvement

Methodology

Define Measure Analyze Improve Control

Objective:

DEFINE the

opportunity

Objective:

MEASURE current

performance

Objective:

ANALYZE the root

causes of problems

Objective:

IMPROVE the

process to

eliminate root

causes

Objective:

CONTROL the

process

to sustain the gains.

Key Define Tools:

Cost of Poor

Quality (COPQ)

Voice of the

Stakeholder

(VOS)

Project Charter

As-Is Process

Map(s)

Primary Metric

(Y)

Key Measure

Tools:

Critical to Quality

Requirements

(CTQs)

Sample Plan

Capability

Analysis

Failure Modes

and Effect

Analysis (FMEA)

Key Analyze

Tools:

Histograms,

Boxplots, Multi-

Vari Charts, etc.

Hypothesis Tests

Regression

Analysis

Key Improve

Tools:

Solution

Selection Matrix

To-Be Process

Map(s)

Key Control

Tools:

Control Charts

Contingency

and/or Action

Plan(s)

What is the problem? The problem is the Output (a Y

in a math equation Y=f(x1,x2,x3) etc).

What is the cost of this problem

Who are the stake holders / decision makers

Align resources and expectations

Define DMAIC ProjectWhat is the project?

Six Sigma

Project

Charter

Voice of the

Stakeholder

Stakeholders

$

Cost of Poor

Quality

Define As-Is ProcessHow does our existing process work?Move-It! Courier Package HandlingProcess

Acco

un

tin

gF

ina

lizin

gD

eliv

ery

Out-Sort SupervisorOut-Sort ClerkAccounts

SupervisorAccounts

Receivable ClerkWeight Fee ClerkDistance Fee ClerkIn-Sort SupervisorIn-Sort ClerkMail ClerkCourier

Observ e packageweight (1 or 2) onback of package

Look upappropriate

Weight Fee andwrite in top middlebox on package

back

Take packagesf rom Weight FeeClerk Outbox toA/R Clerk Inbox.

Add Distance &Weight Fees

together and writein top right box on

package back

Circle Total Feeand Draw Arrow

f rom total tosender code

Take packagesf rom A/R Clerk

Outbox toAccounts

Superv isor Inbox.

Write Total Feef rom package in

appropriateSender column onAccts. Supv .s log

Add up Total # ofPackages and

Total Fees f romlog and createclient inv oice

Deliv er inv oice toclient

Submit log toGeneral Managerat conclusion of

round.

Take packagesf rom Accounts

Superv isorOutbox to Out-

Sort Clerk Inbox.

Draw 5-point Starin upper right

corner of packagef ront

Sort packages inorder of Sender

Code bef oreplacing in outbox

Take packagesf rom Out-Sort

Clerk Outbox toOut-Sort

Superv isor Inbox.

Observ e senderand receiv er

codes and makeentry in Out-SortSuperv isors log

Deliv er Packagesto customers

according to N, S,E, W route

Submit log toGeneral Managerat end of round

Submit log toGeneral Managerat end of round

Does EVERYONE

agree how the current

process works?

Define the Non Value

Add steps

Define Customer RequirementsWhat are the CTQs? What motivates the customer?

Voice of the Customer Key Customer Issue Critical to QualitySECONDARY RESEARCH

PRIMARY RESEARCH

Surveys

OTM

Market Data

Indust

ry I

nte

lLis

tenin

g P

ost

s

Industry Benchmarking

Focus Groups

Customer Service

Customer Correspondence

Obser-vations

Measure Baselines and CapabilityWhat is our current level of performance?

Sample some data / not all data

Current Process actuals measured

against the Customer expectation

What is the chance that we will succeed

at this level every time?50403020100

95% Confidence Interval for Mu

26.525.524.523.522.521.520.519.5

95% Confidence Interval for Median

Variable: 2003 Output

19.7313

8.9690

21.1423

Maximum3rd QuartileMedian1st QuartileMinimum

NKurtosisSkewnessVarianceStDevMean

P-Value:A-Squared:

26.0572

11.8667

25.1961

55.290729.610023.147516.4134 0.2156

1000.2407710.238483

104.34910.215223.1692

0.8540.211

95% Confidence Interval for Median

95% Confidence Interval for Sigma

95% Confidence Interval for Mu

Anderson-Darling Normality Test

Descriptive Statistics

Others

Amou

ntLa

te

41779

4.017.079.0

100.0 96.0 79.0

100

50

0

100

80

60

40

20

0

Defect

Count

PercentCum %

Pe

rce

nt

Co

unt

Pareto Chart for Txfr Defects

Measure Failures and RisksWhere does our process fail and why? Subjective opinion mapped into an objective risk profile number

Failure Modes and Effects Analysis (FMEA)

Process or

Product Name:Prepared by: Page ____ of ____

Responsible: FMEA Date (Orig) ______________ (Rev) _____________

Process

Step/Part

Number Potential Failure Mode Potential Failure Effects

S

E

V Potential Causes

O

C

C Current Controls

D

E

T

R

P

N

Actions

Recommended Resp. Actions Taken

S

E

V

O

C

C

D

E

T

R

P

N

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

0 0

Process/Product

X1

X2

X4

X3

etc

Six Sigma

Analyze Potential Root CausesWhat affects our process?

y = f (x1, x2, x3 . . . xn)

Ishikawa Diagram (Fishbone)

Analyze Validated Root CausesWhat are the key root causes?

Other s

Amou

ntLa

te

41779

4.017.079.0

100.0 96.0 79.0

100

50

0

100

80

60

40

20

0

Defect

Count

PercentCum %

Perc

ent

Count

Pareto Chart for Txfr Defects

Six Sigma

y = f (x1, x2, x3 . . . xn)

Critical Xs

Othe

r

Cleric

al

Curre

ncy

2 312

11.817.670.6

100.0 88.2 70.6

15

10

5

0

100

80

60

40

20

0

Defect

Count

PercentCum %

Perc

ent

Count

Pareto Chart for Amt Defects

Process

Simulatio

n

Data Stratification

Regression Analysis

Experimental Design

Improve Potential SolutionsHow can we address the root causes we identified?

Address the causes, not the symptoms.

y = f (x1, x2, x3 . . . xn)

Critical Xs

Decision

Evalu

ate

Clarify

Gen

erate

Divergent | Convergent

Improve Solution SelectionHow do we choose the best solution?

Time

Qualit

y

Cost

Solution Sigma Time CBA Other Score

Six Sigma

Solution

Implementatio

n Plan

Solution Selection Matrix

Nice

Try

Nice

Idea X

SolutionRight Wrong

Imple

menta

tion

Bad

G

ood

Control Sustainable BenefitsHow do we hold the gains of our new process?

Some variation is normal and OK

How High and Low can an X go yet not materially impact the Y

Pre-plan approach for control exceptions

0 10 20 30

15

25

35

Observation Number

Indiv

idual V

alu

e

Mean=24.35

UCL=33.48

LCL=15.21

Process Owner: Date:

Process Description: CCR:

Measuring and Monitoring

Key

Measure

ments

Specs

&/or

Targets

Measures

(Tools)

Where &

Frequency

Responsibility

(Who)

Contingency

(Quick Fix)Remarks

P1 - activity

duration,

min.

P2 - # of

incomplete

loan

applications

Process Control System (Business Process Framework)

Direct Process Customer:

Flowchart

Customer Sales Branch ManagerProcessingLoan Service

Manager

1.1

Applic

ation &

Revie

w1.2

Pro

cessin

g1.3

Cre

dit r

evi

ew

1.4

Revie

w1.5

Dis

clo

sure

Apply forloan

Reviewappliation forcompleteness

ApplicationComplete?

Completemeeting

informationNo

DFSS The Design MethodologyDesign for Six Sigma

Uses

Design new processes, products, and/or services from scratch

Replace old processes where improvement will not suffice

Differences between DFSS and DMAIC

Projects typically longer than 4-6 months

Extensive definition of Customer Requirements (CTQs)

Heavy emphasis on benchmarking and simulation; less emphasis on baselining

Key Tools

Multi-Generational Planning (MGP)

Quality Function Deployment (QFD)

Define Measure Analyze Develop Verify

Champions

Promote awareness and execution of Six Sigma within lines of business and/or functions

Identify potential Six Sigma projects to be executed by Black Belts and Green Belts

Identify, select, and support Black Belt and Green Belt candidates

Participate in 2-3 days of workshop training

Black Belts

Use Six Sigma methodologies and advanced tools (to execute business improvement projects

Are dedicated full-time (100%) to Six Sigma

Serve as Six Sigma knowledge leaders within Business Unit(s)

Undergo 5 weeks of training over 5-10 months

Green Belts

Use Six Sigma DMAIC methodology and basic tools to execute improvements within their existing job function(s)

May lead smaller improvement projects within Business Unit(s)

Bring knowledge of Six Sigma concepts & tools to their respective job function(s)

Undergo 8-11 days of training over 3-6 months

Evolution of Quality Management (13/19)

6 Sigma

QMS

Taguchi

DOE

SPC

Inspection

1930 1940 1975 1985 1990 2000

Thank You