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Quality

Six Sigma

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Definitions

Management philosophy focused on business process

improvements to:

• Eliminate waste, rework, and mistakes

• Increase customer satisfaction

• Increase profitability and competitiveness

Statistical measure to objectively evaluate processes.

Six Sigma is a set of tools— The Six Sigma expert uses qualitative

and quantitative techniques to drive process improvement. A few

such tools include statistical process control (SPC), failure mode

and effects analysis and flowcharting.

Definitions

Six sigma is an organized and systematic problem-solving

method for strategic system improvement and new product and

service development that relies on statistical methods and the

scientific method to make dramatic reductions in customer

defined defect rates and/or improvements in key output

variables. (Linderman et al (2003)-Journal of Operations Mgt)

“Six Sigma: A comprehensive and flexible system for achieving,

sustaining and maximizing business success. Six Sigma is

uniquely driven by a close understanding of customer needs,

disciplined use of facts, data, and statistical analysis and diligent

attention to managing, improving, and reinventing business

processes.” (Pande, P.S., Neuman, R.P., & Cavanagh, R.R. (2000). The Six Sigma Way: How GE,

Motorola and other Top Companies are Honing Their Performance. New York, New York: McGraw Hill.)

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Brief history

1979-Motorola quality imperative roots of six sigma

1981-Motorola quest to improve 10 fold in 5 years

1988-Motorola wins MBQA

1992-Motorola, Texas Instruments,IBM, and others

start to deveop the 6sigma Black Belt program

1995-GE starts its 6 sigma program

1997/8-GE invests large sums with huge payoffs

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Brief history

Before Six-Sigma methodology, 3-sigma tolerance levels (for any process)

used to be the benchmark for quality measurements.

One of Motorola's most significant contributions was to change the discussion of

quality from one where quality levels were measured in percentages (parts per

hundred) to a discussion of parts per million.

Motorolas’s Process Capability measured in sigmas

Aim: improve every process – whether for products or services – to have a 6-

sigma capability, that is, the number of defects (nonconformances) produced in

the process is less than 3.4 ppm (DPMO-defects per million opportunities).

The Six-Sigma Process started at the production function was later extended

throughout the company. Many other companies followed: GE, Honeywell,HP,

Boing,...

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Statistical concept

The starting point for the six-sigma capability is the normal

probability distribution and the areas lying under different

regions of the normal curve.

The following table shows the proportions of a normal

population under different regions of the normal distribution

curve.

The expected non-conformances are 0.002 parts per million

(two parts per billion) for a process which specification are

located at between +6 and -6 sigmas from the center. The

process is said to have a six-sigma capability.

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Proportions of a normal population

Range around µ

% of products in conformance

% of non conforming products

Non conformance out of a million

-1σ to + 1σ

-2σ to + 2σ

-3σ to + 3σ

-4σ to +4σ

-5σ to + 5σ

-6σ to + 6σ

68.26

95.46

99.73

99.9937

99.999943

99.9999998

31.74

4.54

.27

.0063

.000057

.00000002

317400

45400

2700

63

.57

.002

Static Process (no movement of mean)

6s

m (Mean)

0.01ppm

LSL

s

USL

Distance between USL and LSL is 12 .(12 times of )

Probability of out-of-spec is 0.02ppm

12s

6s

0.01ppm

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(Motorola) Six-Sigma Table (long-term) (values may be slightly different from table to table)

yield %: DPMO: Sigma :

30.2 697,000 1.0

69.2 308,000 2.0

93.3 66,800 3.0

99.4 6,210 4.0

99.98 230 5.0

99.9997 3.4 6.0

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Statistical concept

Which one - 0.002 (normal curve) or 3.4 ppm?

The difference occurs because that the process’ mean can drift1.5 sigma in either direction in the long run. The area of anormal distribution beyond 4.5 sigma from the mean is indeed3.4 parts per million.

Thus, to accommodate 1.5 sigma shift, they (Motorola) aimed at6 sigma capability.

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Process not centered:1.5 sigma shift (or ‘drift’)

Statistical concept

In six sigma methodology ~99.9997% (or more) of

process data lies within +/- six sigma from the mean,

thus having only 3.4 defects per million opportunities

(DPMO).

Now, ~99.9997% value is actually for 4.5 sigma level

in Normal curve, but keeping in view the 1.5 sigma

process shift, the process’ sigma level is actually six.

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Statistical concept

Six Sigma short-term capability occurs when the process is

centered on the target and there is no distribution shift

(variability due to common causes). It also assumes continuous

uniform process with no changes.

Six Sigma long-term capability assumes that the process mean

changes due to variability (random and special causes) . This

change could result in an average of 1.5 sigma distribution shift

in either direction for long-term performance.

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DPMO calculation

DPO-defects per opportunity

D/ (U*O)

D: number of defects observed in a sample

U: number of units in a sample

O: number of defect opportunities per unit

DPMO= DPO*106

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example

Consider that in 100 invoices there are 10

with defects. Also, there are 5 opportunities

for errors (defects) for every invoice.

Then:

DPO= 10/ (100*5) = 0.02

DPMO= 0.02*106 = 20,000 sigma=3.55

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The Six-Sigma System

Six themes

Three strategies

Improvement processes

Road Map

The organization for six-sigma

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Six themes for Six-Sigma

Focus on the Customer

Data and fact-driven management

Process focus

Proactive Management

Boundaryless collaboration

Drive for perfection

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Three strategies

Process Improvement (DMAIC)

Process design/redesign (DMADV)

Process management

Not mutually exclusive

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Improvement-DMAIC

DMAIC methodology is aimed at improving a Process or

product (through reduction in Variation) in an incremental

fashion:

Define -> Measure -> Analyse -> Improve -> Control -> Define...

Define

Identify the problem(s)

Identify requirements (VOC: Critical to Quality-CTQ-

characteristics)

Define the Goals:

Involving customers (VOC, QFD), employees

Strategic (e.g., increase market share,...); Operation

(increase output); Project (e.g., reduce the defects

level)

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DMAIC

Measure

Validate problem/process

Refine problem/goal

Measure key steps/inputs

Measure the existing system: start from the current

baseline; use reliable metrics; use proper Tools;

understand the data.

Analyse

Develop causal hypothesis

Identify root causes (the ‘vital few’)

Validate hypothesis

RCA

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DMAIC

Improve

Develop ideas to remove root causes

Test solutions

Standardize solutions

Measure the results

Iterate whenever necessary

Control

Establish standard measures to maintain performance

Create and use documentation

Correct problems as needed

DMAIC-Exemples of tools/methologies used

(Thomas Pyzdek)

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DMAIC exemple

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DFSS-Designing For Six-Sigma

The DMADV model is the Design for Six Sigma (DFSS) model

used to create major new features of existing products, services,

or processes, or to create entirely new products, services, or

processes. It has 5 phases:

Define -> Measure -> Analyse -> DESIGN-> Validate -> Define

Some authors refer to the Process as DMEDI

(D_M_Explore_D_Implement)

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The Roadmap

Five steps to implementing Six-Sigma

1-Identify core processes and key customers

2-Define customer requirements

3-Measure current performance

4-Prioritize, analyze, implement improvements

5-Expand and integrate the Six-Sigma system

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Organizing Six-Sigma

Key Roles

Leadership Team

Champions

Mentors (master ‘Black Belts’)

Experts (‘Black Belts’)

Participants (Green Belts)

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Organizing Six-Sigma

The Leadership Group

Be actively involved from outset

Develop a strategic plan

Establish Roles and Infrastructure

Establish supporting policies

Job descriptions

Reward/Compensation systems

Career paths

Select projects

Prioritize projects and allocate resources

Facilitate, guide, manage

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Organizing Six Sigma

The Champions

Find appropriate projects

Represent projects to the leadership

Provide coaching

Ensure allocation of resources

Resolve issues

Master Back Belts

Coach and support project leaders

Work as a change agent

Train others in the use of Six-Sigma tools

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Organizing Six Sigma

Black Belts

Highly trained experts

Manage project leaders

Lead project teams

Green Belts

Trained in the use of statistical tools

Lead project teams

Participate on project teams

Fad... Or not!

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References

Quality Mgt-Goetsch/Davies (Ch. 1)

The Certified Manager of Quality Handbook-Westcott (Ch. 13).

First Course in Quality Engineering-Krishnamoorthi (Ch. 5)

DMAICtools

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