SQM-Mod 4

8/3/2019 SQM-Mod 4

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Amity Business School

Philosophy of…

Six-Sigma

• Six sigma is a philosophy of doing any business (providing any product or service) encompassing the methodologies of defect prevention rather than

detection.

• Six sigma uses statistical tools that can vary from “ Pareto chart” to

“designed experiments”. It provides a foundation for continuousimprovement and world class improvement efforts.

• Products could be any goods or service and continuous improvement

would cover quality, costs, speed, productivity and customer satisfaction

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Customers Perspective of Six-Sigma

CUSTOMER

• Meeting or exceeding customer requirements to achieve customer satisfaction is

the most acceptable way to define quality today. This definition, however is more

appropriately the fundamental objective.

PROCESSES

• Process management includes the continuous study of the relationship between

variations and outputs and sources of variation which may be present in the

process. Statistical tools provide a way to study the process and effect of sources of

variation.

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SIX-SIGMA

Concept of Six-Sigma Quality

“ An approach to measuring and improving product and servicesquality addressing cost, quality, productivity, delivery times and customersatisfaction resulting in beefed up bottom lines”

• Realization of many fundamentals of „Total Quality Management‟ notably the integration of human and process elements of improvement.

• Only one ultimate goal- Zero Defect

•

It does not matter how rare the disease is. If you have got it, that‟s all that matters

• Understanding of a management strategy and its deployment down thelines and how it can transform the organization.

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SIX-SIGMA Quality

Originally conceived by Motorola in ‟87 and later successfully used by Boeing,Caterpillar, Corning Digital Equipment, IBM, Raytheon, Whirlpool & GE

… The name is derived from the fact that the specification limits

are six process-standard deviation away from the targeted mid-

point of the tolerance range

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Six-sigma …..The numeric significance

-1.5

Mean Level 3 sigma 4 sigma 5 sigma 6 sigma

1.5 off center 66,803 6200 233 3.4

SIX-SIGMA represents 3.4 defects per million opportunities

-3 +3

- 6 + 6

Process Variability

Mean 0

3.4 PPM

+1.5

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SIX-SIGMA … Implementation

DMAIC Model Recognized benchmark for six-sigma implementation is General Electric

It employs following five phases;

1. Define (D)

- Identify customers and their priorities- Identify a project suitable for six-sigma based on business objectives

as well as customers need and feedback.

- Identify CTQs ( critical to quality characteristics) that the customer

considers to have the most impact on quality

2. Measure (M)

- Determine how to measure the process and how is it performing

- Identify the key internal processes that influence the CTQs and

measure the defects currently generated relative to those processes

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SIX-SIGMA Implementation (contd.)

3. Analyze (A)- Determine the most common cause of defect

- Understand why defects are generated by identifying the key variables

that are most likely to create process variations

4. Improve (I)- Identify means to remove the causes of the defects

- Confirm the key variables and quantify their effect on the CTQs.

- Identify maximum acceptable range of the key variables and system

to measure deviations of the variables

- Modify the process to stay within the acceptable range.

5. Control (C)

- Determine how to maintain the improvements- Put tools in place to ensure that the key variables remain within the

maximum acceptable range under the modified process.

….. The approach appears to be similar to other quality improvement approaches.The key difference is the emphasis on customer requirements and aggressive use of advanced statistical tools and methodologies.

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Design of Experiments DOE

• In using SPC tools, we constantly strive for reducing variation. Thisis done by detecting and reducing un-expected variation (Significant Events). Most SPC tools are passive in their approach in identifying opportunities for improvements. Essentially the way we learn from basic SPC tools i.e) to increase the opportunity to see a significant

event.• Control charts can be very effective at increasing the chances of

observing a significant event, but if not properly, it may just as likely hide significant events (eg: improper sampling).

•

To over simplicity, Basic SPC tools and techniques wait for an event to happen and help you observe it. This passive method of detaining knowledge will not be enough to allow us to compete in future.

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Improved observation…….. ……….ensures that naturally occurring

informative events are brought to the notice of perceptiveobservers and increase the probability of observingnaturally occurring informative events so that appropriate

actions can be taken.

Design of Experiments (DOE)

Mean

UCL

LCL

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Induction of Occurrence of informative events

–

An EXPERIMENT is an invitation for an informativeevent to occur.

– The manipulation of controllable factors

(INDEPENDENT VARIABLE) at different levels to seetheir effect on same response (DEPENDENT VARIABLE)

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COMMON METHODS

– Trial and error

– One factor at a time

– Full factorial

– Fractional factorial

– Others


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TRIAL AND ERROR

Problem - Mileage of car is 20 kmplWould like to get>30kmpl

Solution thought of

– Change the petrol octane

–

Change the brand of petrol – Change petrol pump

– Drive slow

– Tune up car

– Wash and wax car

– New tyres

– Change tyre pressure

– Take up body wt reduction program at home

• What if it works?

• What if it doesn’t?

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OFAT

Speed Mileage Octane Tyre Pr. 55 25 85 30

65 23 85 30

55 27 91 30

55 27 85 35

• How many runs?

• Is it realistic if co variable

What if there is a co-relation between factors?

• Problem

– Time and money

– Noise in data – Unrealistic in factory environment

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FULL FACTORIAL

An experimental strategy that allows us to answerquestions most completely. Full factorials examine

every possible combination of factors at the levels

tested. The enable us to:

Determine main effects of the factors manipulated as

selected response variables.

Determine effects of factor evaluation as selected

response variables.

Determine levels to set factors for best results.

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PROBLEM : Mileage is 20, Would like to get > 30.

SPEED (A) OCTANE (B) TYRE PRESS(C)

MILEAGE (Y)

55 85 30 Y1

65 85 30 Y2

55 91 30 Y3

65 91 30 Y4

55 85 35 Y5

65 85 35 Y6

55 91 35 Y7

65 91 35 Y8

• How many runs?

• How many observations at each level?

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COMPARISON OF METHODS

•

There are many methods of experimentation. Some method suchas trial and error is deficient and will not facilitate an increase inknowledge. Other methods such as OFAT are inefficient and maylead to error on conclusion

• Statistically designed experiments are efficient procedure for

discovering relationship between independent factors (processparameters), such as temperature, pressure, time, speed etc andresponse variable (Product Parameter)such as size, variation ,ductility, shrinkage etc

•

The independent factors are varied in specific fashion and theeffect of these changes on the response is measured. The fashion inwhich two independent variables are manipulated may be thoughtof as the experimental design.

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LIMITATIONS OF FULL FACTORIAL

– The limitations are not in theory but in practicality. The resources (i.e.

time & cost) necessary to run full factorial designs can be significant.

Full factorials can be used when investigating a small number of

variables (2-4), but are not recommended when investigating a large

number of factors (5 or more). The number of runs needed increase

exponentially with the number of factors, making the costs involvedprohibitive.

– This does not means that full factorials are not useful, but they are to be

used at the proper time.

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FACTORS LEVELS SYMBOL EXPERIMENTS

2 2 2^2 4

3 2 2^3 8

7 2 2^7 128

15 2 2^15 32,768

2 3 3^2 9

3 3 3^3 27

7 3 3^7 2,187

LEVELS OF EXPERIMENTS IN FULL FACTORIAL

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FRACTIONAL FACTORIAL

A Fractional Factorial as it sounds, looks

at only fractional of all the possible combination contained

in full factorial. Therefore, if there are many factors being

investigated, information can be obtained with much lessinvestment. It is the Fractional factorial that has

significantly increased the use of experimentation

throughout the world. The resources required to complete

a fractional factorial are manageable and not muchrelevant information is given up. The success is proven.

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PROBLEM:

Mileage is 20 Required is > 30

SPEED

(A)

OCTANE

(B)

TYRE

PRESS. (C)MILEAGE

(Y)

55 85 35 Y1

65 85 30 Y2

55 91 30 Y3

65 91 35 Y4

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FRACTIONAL FACTORIAL ( CONTD.)

OBSERVATIONS

• How Many Runs?

• How Much Information?

• Is there a balance?

LIMITATIONS

• Give up some information

• Inexperience in Use

• Fear of Statistics

HENCE

“ WE NEED A SYSTEMATIC EXPERIMENT STRATEGY FOR LOOKING AT MANY FACTORS AT THE SAME TIME”

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Amity Business School DOE (contd)

Other Methods of Experimentation

• STANDARD ORDER DESIGN (2^n)

…… also called Yates order….manipulates main effects

• RANDOMIZATION

…. Allows equal opportunity for an event to occur

…. Usually impractical

• RUN ORDER

….. Brings about an order in randomization

• ROSSES RULES OF ANALYSIS

….. Practical importance consideration

A i B i S h l

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SIX-SIGMA … The organization

Leadership/ Sponsorship Leadership system, top level commitment, deployment

involvement, training , reward & recognition system

Champion

Fully trained business leaders who promote, sponsor &

support the improvement projects

Master Black belts

Fully trained quality leaders responsible for six-sigma

projects strategy, training, mentoring, deployment & Results

Black Belts Fully trained six-sigma experts who lead the projects, ensure

results and mentor the green belts

Green Belts

Black belts in making & working with black belts.

A i B i S h l

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SIX-SIGMA …some things to remember

• Real power comes when you are able to combine „people power with „process

power‟

• Everyone can see clearly what he/she can do better

• Six-sigma does not teach the art of „managing a problem‟ but the science of

„eliminating the problem‟

• The front liners see and hear things that guys in the offices don‟t.

• Cost of „training people‟ is a very small percentage of what „trained, developed &

motivated‟ workforce can get you back.

• Pick the one that hurts you the most. If you can fix it , fix it. And it will reward you

the most.

•

You would have lot more credibility with your people if you could back up what you say, with figures.

• Six-sigma is not „doing it better‟. It is „eliminate the bad‟

• Two ways of winning…. “Spectacular Performance” Or “Fewer Mistakes”

SQM-Mod 4

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