lean six sigma presentation

8/6/2019 Lean Six Sigma Presentation

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Lean Six Sigma Tools

( A Collection )


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Acknowledgement

Globalization and Technological advancements poses challenges andopportunities for business around the world. Comapnies have adapt to newsituations and change and improve their business processes to remaincompetetive in the market. Six Sigma and Lean Principles are tools used bycompanies around the world to attain operation excellence and improve theirbottom line by elimination defects and waste in their products and services . The

collection of these slides from various sources introduce Six Sigma and LeanPrinciples and the tools used for their implementation. We acknowledge withthanks all contributions for using in this presentation on 'Lean Six Sigma Tools'.


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Lean Six Sigma


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How Six Sigma was born

Bill Smith, a senior quality engineer at Motorola was working with a type ofcircuit board called a bay station board. The product had a much higherfailure rate than predicted, despite having been designed with meticulousattention. Smith came to realize that it was the accumulation of a lot of littledefects made during the manufacturing process not inherent design flaws that caused the high rate of early-life failures. Eliminating the source of thosedefects was therefore the only way the company could deliver higher quality to

its customers.

Smith also realized that the company needed a standard metric ofquality that could be used across all its manufacturing processes. With hisinnate zeal for perfection, he settled on a measure of variation sigma. Smithmet with Galvin in late 1985 to promote the notion of having a six sigmatolerance in terms of defects so that even shifts in process performance would

not produce defects.After listening to Smith, Galvin directed Jack Germain, Motorolas firstcorporate vice president of quality, to build on Smiths ideas. And Six Sigmawas born. In 1987 the company trademarked the term, making it official.

Everyone soon came to see that six sigma meant being near-perfect, saidMor.


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Corporate Commitment

Motorola is committed to developing these leaders

We provide these people with extensive training in statisticaland interpersonal tools, skilled guidance and management

support

Once their development has achieved a level worthy ofrecognition, we even have a term for those exceptionalindividuals :

Six Sigma Black Belts

Chris Galvin


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Distinguish Vital Few

from Trivial Many

Y = Dependent Variable Output, Defectx = Independent Variables Potential Causex* = Independent Variable Critical Cause

Define the Problem /Defect Statement

Y= f ( x1*

, x2, x3, x4*

, x5. . . Xn)

Process

(Parameters)

Material

Methods

People

Environment

Output

Machine

Measurements


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Six Sigma as a Method

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To get results, should we focus our behavior on the Y or X

Y X1Xn

Dependent Independent

Output Input-Process

Effect Cause

Symptom Problem

Monitor Control


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Eliminate Trivial ManyEliminate Trivial Many

Qualitative Evaluation Technical Expertise Graphical Methods Screening Design of Experiments

Qualitative Evaluation Technical Expertise Graphical Methods Screening Design of Experiments

Identify Vital FewIdentify Vital Few Pareto Analysis Hypothesis Testing Regression Design of Experiments

Pareto Analysis Hypothesis Testing Regression Design of Experiments

Quantify

Opportunity

Quantify

Opportunity % Reduction in Variation Cost/ Benefit % Reduction in Variation Cost/ Benefit

Our Goal:

Identify the Key Factors (xs)


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Graph>Box plot

75%

50%

25%

Graph>Box plot

Without X values

DBP

Box plots help to see the data distribution

Day

DBP

10

9

10

4

99

94

109

104

99

94

Operator

DBP

10

9

10

4

99

94

Shift

DBP

10

9

10

4

99

94


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Statistical Analysis

0.0250.0200.0150.0100.0050.000

7

6

5

4

3

2

1

0

New

c

i

e

Freq

uenc

0.0250.0200.0150.0100.0050.000

30

20

10

0

Mac

ine6 mt

s

Frequenc

Is the factor really important?

Do we understand the impact forthe factor?

Has our improvement made animpact

What is the true impact?

Hypothesis Testing

Regression Analysis

55453525155

60

50

40

30

20

10

0

X

Y

R-

q =

6.0

Y = 2.19469 + 0.918549X

95%

I

Regression

Regression

lot

Apply statistics to validate actions & improvements


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Design of Experiments (DOE)Design of Experiments (DOE)

To estimate the effects of independent Variables onResponses.

TerminologyTerminology

FactorAn independent variable

Level A value for the factor.

Response - Outcome

X Y

PROCESS


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Why use DoE ?Why use DoE ?

Shift the average of a process.

Reduce the variation.

Shift average and reduce variation

x1 x2


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CONTROL PHASE - SIX SIGMA

Control Plan Tools:

1. Basic Six Sigma control methods.- 7M Tools: Affinity diagram, tree diagram, process

decision program charts, matrix diagrams,interrelationship diagrams, prioritization matrices,activity network diagram.

2. Statistical Process Control (SPC)- Used with various types of distributions

- Control ChartsAttribute based (np, p, c, u). Variable based (X-R, X)Additional Variable based tools

-PRE-Control-Common Cause Chart (Exponentially BalancedMoving Average (EWMA))


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PRODUCTMANAGEMENT

OVERALL

GOAL OFSOFTWARE

KNOWLEDGE OFCOMPETITORS

SUPERVISION

PRODUCT

DESIGN

PRODUCT

MANAGEMENT

PRODUCTDESIGN

PRODUCTMANAGEMENT

INNOVATION

OUTPUT

DIRECTORY

ORGANIZATION

INTUITIVEANSWERS

SUPPORT

METHODS TO MAKEEASIER FOR USERS

CHARACTERISTICS:

Organizing ideas into meaningfulcategories

Data Reduction. Large numbers of qual.Inputs into major dimensions or categories.

AFFINITY DIAGRAM


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MATRIX

DIAGRAM

Patientsche

duled

Attendantassigned

Attendantarrives

Obtainsequ

ipment

Transportsp

atient

ProvideThe

rapy

Notifiesofreturn

Attendantassigned

Attendantarrives

Arrive at scheduled time 5 5 5 5 1 5 0 0 0 0

Arrive with proper equipment 4 2 0 0 5 0 0 0 0 0

Dressed properly 4 0 0 0 0 0 0 0 0 0

Delivered via correct mode 2 3 0 0 1 0 0 0 0 0Take back to room promptly 4 0 0 0 0 0 0 5 5 5

IMPORTANCE SCORE 39 25 25 27 25 0 20 20 20

RANK 1 3 3 2 3 7 6 6 6

5 = high importance, 3 = average importance, 1 = low importance

HOWS

WHATS

RELATIONSHIPMATRIX

CUSTOMERIMPORTANCE

MATRIX


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Motorola ROI1987-1994

Reduced in-process defect levels by a factor of 200.

Reduced manufacturing costs by $1.4 billion.

Increased employee production on a dollar basis by 126%.

Increased stockholders share value fourfold.

AlliedSignal ROI

1992-1996

$1.4 Billion cost reduction.

14% growth per quarter.

520% price/share growth.

Reduced new product introduction time by 16%.

24% bill/cycle reduction.


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General Electric ROI

1995-1998

Company wide savings of over $1 Billion.

Estimated annual savings to be $6.6 Billion by the year 2000.


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The normal Distribution


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Lean Manufacturing Tools

Lean manufacturing tools are adapted to help businesses with the process ofbecoming lean. These tools include the following:

Five S: The name derives from five Japanese words beginning with S. Thepurpose of this tool is to simplify your work environment, reduce waste, andimprove safety, quality, and efficiency.

Kanban: This tool is used in pull systems as a signaling device to trigger action.Traditionally it used cards to signal the need for an item. It can trigger themovement, production, or supply of a unit in a production chain.

Poka-yoke: This is a mechanism that helps an equipment operator avoidmistakes. Its objective is to eliminate product defects by preventing, correcting,or drawing attention to human errors as they occur.

Heijunka: This is a system designed to level the production volume and

production by product type. A heijunka boxis basically a board with boxes thatlays out times with cards that let employees know what they are doing at specifictimes during the production schedule.


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Crosby's response to the quality crisis was the principle

of"doing it right the first time" (DIRFT). He would alsoinclude four major principles:

the definition of quality is conformance to

requirements

the system of quality is prevention

the performance standard is zero defects

the measurement of quality is the price of

nonconformance

Crosby's prescription for quality improvement was a 14-

step program. His belief was that a company thatestablished a quality program will see savings returnsthat more than pays off the cost of the quality program

("quality is free").


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y 5 Whys

y Analysis of variance

y ANOVA Gauge R&R

y Axiomatic design

y

Business Process Mappingy Cause & effects diagram (also known as fishbone orIshikawa

diagram)

y Chi-square test of independence and fits

y Control chart

y Correlation

y Cost-benefit analysis

y CTQ tree

y

Design of experiments

y Failure mode and effects analysis (FMEA)

y General linear model

y Histograms

y Quality Function Deployment (QFD)

y Pareto chart

y Pick chart

y

Process capabilityy Quantitative marketing research through use of Enterprise

Feedback Management (EFM) systems

y Regression analysis

y Root cause analysis

y Run charts

y SIPOC analysis (Suppliers, Inputs,Process,Outputs,Customers)

y Taguchi methods

y

Taguchi Loss Functiony TRIZ

Quality management tools and

methods used in Six Sigma


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The following example demonstrates the basic process:My car will not start. (the problem)Why? - The battery is dead. (first why)Why? - The alternator is not functioning. (second why)Why? - The alternator belt has broken. (third why)Why? - The alternator belt was well beyond its useful service life and has never

been replaced. (fourth why)Why? - I have not been maintaining my car according to the recommended serviceschedule. (fifth why, a root cause)Why? - Replacement parts are not available because of the extreme age of myvehicle.(sixth why, optional footnote)I will start maintaining my car according to the recommended service schedule.

(solution)

5Why


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CustomerCentricity

The Six Sigma culture is customer-centric; its goalis to delight customers. The quality of a product orservice is measured from the customers perspective,by its contribution to their success. This

customer focus comes through the Six Sigma drivers: Voice of the Customer: What the customer says that they

want

Requirements: Voice of the Customer input that is

translated into specific, measurable elements

Critical to Quality (CTQ): Requirements that are most

important to customers

Defect: Failing to deliver to a customers CTQ

Design for Six Sigma: Designing products andprocesses

basedon customer requirements

Critical Success Factors for Six

Sigma


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Joseph JuranBorn 1904Joseph Juran is an internationally acclaimed quality guru, similar toEdwards Deming, strongly influencing Japanese manufacturingpractices. Joseph Jurans belief that qualitydoes not happen byaccident gave rise to the quality trilogy:

o

Quality planningoQuality controloQuality improvement

The key steps in implementing company-wide strategic goals are:Identify customers and their needs both internal and external and work to meet those needsCreate measures of quality, establish optimal quality goals andorganise to meet them.Create processes capable of meeting quality goals in realoperating conditions.

Failure mode and effects


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Failure mode and effects

analysis

A failure modes and effects analysis (FMEA), is a procedure in productdevelopment and operations management for analysis of potential failuremodes within a system for classification by the severity and likelihood of thefailures.

Failure modes are any errors or defects in a process, design, or item,

especially those that affect the customer, and can be potential or actual.ffects analysis refers to studying the consequences of those failures.


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Example FMEA Worksheet

Function Failure

mode

Effects S

(severit

y

rating)

Cause(s) O

(occurren

ce rating)

Current

controls

D

(detection

rating)

CRIT

(critical

charact

eristic

RPN

(risk

priority

number

)

Recomme

nded

actions

Responsibili

ty and

target

completion

date

Action

taken

Fill tub High level

sensor

never

trips

Liquid

spills on

customer

floor

8 level

sensor

failed

2 Fill

timeout

based on

time to fill

to low

level

sensor

5 N 80 Perform

cost

analysis

of adding

additional

sensor

halfway

between

low and

high level

sensors

Jane Doe

level

sensor

disconnec

ted

10-Oct-10


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Bibliography

(2008). (): -companies, ,.4,.1, 2008., ,..(2004).

,(2007). ,

(2009). Taking Lean Six SigmaBeyond Manufacturing: Improvement, & .(2009). , , , (2000).HoneywellAerospaceElectricalSystem,Singapore

, . (2002). . - : ://.--./. & (2004). ,

SeanP. Goffnett(2004). Understanding : Education , ,. 20, . 4, - 2004. (- 2007). 20 ,-://../-

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