LEAN SIGMA_SUNYSB_May08.ppt

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Presented by: Joe Labas, ASQ CSSBB – May 8, 2008 1 of 44
SUNY- Stony Brook
Quality Management - EMP 517
Introduction to
Six Sigma (6)
and Lean
“Lean-Sigma”

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1. Why?
2. What is it?
 How Six Sigma is a step forward
 Where it came from
 How it’s different
3. How to get started
4. Roles, “Belts” and Certifications
5. How to integrate Lean and Six Sigma
Six Sigma: 6

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WHY Six Sigma?
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
%
Revenue
Savings
Motorola
1986 - 2001
GE
1996 - 1999
Honeywell
1998 - 2000
Ford
2000 - 2002
Company
Reported* Six Sigma Savings As % of Revenue
* from Annual Reports / Company web sites

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WHY Six Sigma?
The Pharma Sigma Value
For most pharma companies, the process quality level
was between 2 and 3 sigma in 2002
OPPORTUNITY?

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WHY Six Sigma?
“Quality costs are the costs associated with preventing,
finding, and correcting defective work. These costs are
huge, running at 20% - 40% of sales.” - J.M. Juran

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WHAT is Six Sigma ?
2 Simple Questions:
1. Are your processes predictable?
2. Are they capable?

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Six Sigma: 6
A management philosophy and a
disciplined problem-solving
methodology backed by powerful
statistical tools using a cross-
functional team approach to reduce
service errors or process defects to
3.4 ppm opportunities or less.
Three distinct levels:
1. Philosophy: Variation Reduction
2. Methodologies: DMAIC , DMADV/IDOV
3. Metric: 3.4 dpmo
DFSS

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The Six Sigma Philosophy
What is the enemy of quality?
EXCESS VARIATION !
All improvement comes from
understanding THEN reducing variation
If the Variation is due to:
• COMMON Causes (Chance/Inherent/Random/Natural)
- System “ NOISE”
Then the Process is: In Control/Predictable/Stable
• SPECIAL Causes (Assignable/Non-random)
- “ SIGNALs”
Then the Process is: Out of Control/Unpredictable/Unstable
THE PROCESS MUST FIRST BE PREDICTABLE BEFORE
DETERMINING IF IT IS CAPABLE!

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Statistical Thinking & Six Sigma
Statistical Thinking Principle Six Sigma Tools
All work occurs in a system of
interconnected processes
Process Maps, Value Stream
Mapping, SIPOC Diagrams,
Cause and Effect Matrix, Failure
Mode Effects Analysis (FMEA),
Quality Function Deployment
(QFD)
Variation exists in all processes Descriptive Statistics,
Measurement System Analysis
(MSA), Enumerative Statistics,
Multi-Vari Charts, Cause and
Effect Diagrams, Box Plots,
Process Capability Analysis
Understanding and reducing
variation are the keys to
improvement and success
Control Charts, Design of
Experiments (DOE), Hypothesis
Testing, Correlation, Regression
Analysis, Pareto Charts

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Variation Reduction
“Predictable & Capable”
BNL Division "X" - OSHA Reportable Injuries
UCL = 17.6
"Average" = 7.9
0
2
4
6
8
10
12
14
16
18
20
2000 2001 2002 2003 2004 2005 2006
FY
Number
of
Injuires
Prediction
Limit
Goal
"Signal" Rules:
1) Any value beyond control limits
2) 8 successive values above/below Average
3) 3 of 4 values in upper or lower 25% of the limits
WHAT ABOUT THE OPPORTUNITIES?

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Variation Reduction - “The Taguchi Way”
Traditional View Six Sigma View
The Loss, $, due to performance variation is proportional to
the square of the deviation of the performance characteristic
from its nominal value: L(x) = k(x-t)2

12
Outputs vs. Inputs
The process output, Y, is a
function of all the inputs, X
Y = f(X)
Determine the “vital few” X’s
AND the interrelationships
that impact Y
THEN
Optimize the levels of the
vital few inputs

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Six Sigma: 6 History
• early 1800’s - Carl Frederic Gauss – Gaussian Distribution = Normal Curve =
Bell curve
• 1920’s - Walter Shewhart – Control Charts, ± 3 (99.73%) ; 2 Types of
Variation: Common Cause and Special Cause
• mid 1940’s/50’s – Deming and the war effort; Japan & SPC
• early 1980’s – Process capability indices popular– Cp, Cpk
• mid to late 1980’s – Six Sigma is born: Bill Smith (Engineer), Dr. Mikal
Harry (Statistician) & Rich Schroeder (Executive), Motorola –
manufacturing focus (“Six Sigma” – federally registered trademark of
Motorola)
• 1994 – “Six Sigma Academy” founded by Dr. Harry; Asea Boveri Brown (Rich
Schroeder) one of first clients
• 1995 – CEO Larry Bossidy of Allied Signal/Honeywell (Rich Schroeder) –
enterprise focus: all business processes
• 1996 – CEO Jack Welch, GE hires Six Sigma Academy
• late 1990’s books, consulting, training, lectures, conferences, “Certifications”
• 2001 - first ASQ Certified SSBB exam

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How “6” Started
On January 15, 1987, CEO Bob Galvin established Six Sigma
as the required capability level to approach the standard of 3.4
DPMO. This new standard was to be used in everything, that
is, in products, processes, services and administration.
Motorola’s Stated Goals:
“Improve product and service quality ten times by 1989,
and at least one hundred fold by 1991. Achieve Six
Sigma capability by 1992…achieve a culture of continual
improvement to assure Total Customer Satisfaction.
There is only one ultimate goal: zero defects in
everything we do.”

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Why “6”?
The Motorola Way
Ensuring that process variation (as measured by  ) is half the
design tolerance (spec. width / process width = 2.0) while allowing
the mean to shift as much as 1.5 standard deviations.

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PPM Defective As a Function of
Process Off-centering (Shifting)
Process Quality Level
Off-Centering 3  3.5  4  4.5  5  5.5  6 
0 2700 465 63 6.8 0.57 0.034 0.002
.25  3577 666 99 12.8 1.02 0.1056 0.0063
.5  6440 1382 236 32 3.4 0.71 0.019
.75  12288 3011 665 88.5 11 1.02 0.1
1.0  22832 6433 1350 233 32 3.4 0.39
1.25  40111 12201 3000 577 88.5 10.7 1
1.5  66803 22800 6200 1350 233 32 3.4
1.75  105601 40100 12200 3000 577 88.4 11
2.0  158700 66800 22800 6200 1300 233 32
from: P. R. Tadikamalla, Quality Progress, Nov. ‘94
In most cases, controlling the process to target is
easier and less expensive than reducing the process
variability. This table helps assess the trade-offs.

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Is 99.9% “Good” Enough?

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The 6 Metric
 Traditional ±3 sigma (99.73%) yields:
• 54,000 incorrect drug prescriptions per year
• 40,500 newborn babies dropped each year
* 2700 ppm
 “Good Enough” quality (99.9%):
• 20,000 incorrect drug prescriptions per year
• 18,250 newborn babies dropped each year
* 1000 ppm
 “Six Sigma quality” (99.9996%) yields:
• One incorrect drug prescription every 25 years
• 3 newborn babies dropped each century
* 3.4 ppm (“Statistical” Six Sigma = 2 ppb (w/o the shift))

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The Six Sigma Methodology and
“The Scientific Method”

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The Six Sigma Methodology
The History of Problem-Solving /
Process Improvement Models
?
DESIGN for
SIX SIGMA
DFSS
(DMADV)
SIX SIGMA
DMAIC
QI STORY GLOBAL 8D MOTOROLA
SIX STEPS
CI CYCLE
Define Define Reason For
Improvement
Establish the
Team
Id & select
problem
PLAN
Measure Measure Current Situation Describe the
Problem
Develop an
“ICA” (contain)
Id root causes
Analyze Analyze Analysis Define / Verify
Root Causes
Develop
alternative
solutions
DO
Design Improve Counter-
measures
Choose / Verfiy
“PCA”
Select & plan
solution
Implement
solution
Results Implement /
Validate PCA
Evaluate
solution
CHECK
Verfiy Control Standardization Prevent
Recurrence
Standardize
solution
ACT
Future Plans Recognize
Team

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Six Sigma Methodologies
DMAIC (“Corrective”)
Define the customers (internal and external), project goals, scope, and
deliverables using: VOC, QFD (House of Quality); Flow Charts;
Process Maps; VSM, SIPOC Diagrams…
Measure the process to determine current performance; id input AND
output variables using: Measurement System Analysis / R&R
Study; Multi-Vari Analysis; Control Charts…
Analyze the results to determine the root cause(s) of the “defects” and
the relationships between input and output variables using: 7 QC
Tools; Regression Analysis; Hypothesis Testing; DOE…
Improve the process by eliminating defects; experiment to establish
cause-effect relationships; optimize the inputs using: DOE; FMEA;
Mistake-proofing; Benchmarking; Action Plans…
Control future process performance; placed on inputs NOT outputs (i.e.
NO inspection) using: Control Plans; Mistake-proofing; TPM;
SPC; Audits…

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Six Sigma Methodologies
DMADV (“Preventive”)
DMADV (a.k.a. DFSS) – using the VOC
Define the customer, the project goals and deliverables
Measure to determine customer needs and specifications
Analyze the process options to meet the customer needs
Design (detailed) the process to meet the customer needs
Verify the design performance and ability to meet
customer needs

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Six Sigma: 6
How is it Different…?
The Language
of
Management!
+
=
80-90% of quality problems
can be solved with simple
tools. Six Sigma also
contains more sophisticated,
statistical tools for the more
complex, chronic problems

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Six Sigma: 6
How is it Different…?
 Structured, disciplined, statistical problem-
solving
 Dedication of varied resources to the task
of continuous performance improvement of
ANY process
 Voice of the Customer (VOC) drives the
business and projects are aligned
 Driven from a business perspective
 Quantifiable, bottom-line returns - $ $ $

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Organizing for
Six Sigma
(Yellow/White)

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Six Sigma
Getting Started - Alignment
The “Voice of the Customer” (VOC) &
Policy Deployment
"The best Six Sigma projects begin not inside the business
but outside it, focused on answering the question - how can
we make the customer more competitive? What is critical
to the customer's success?…One thing we have discovered
with certainty is that anything we do that makes the
customer more successful inevitably results in a financial
return for us.”
- Jack Welch, GE’s 1997 Annual Meeting

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Six Sigma
Translating the “Voice of the
Customer” using QFD
Once customer needs are identified, preparation of
the product planning matrix or "house of quality“
can begin.
Quality Function Deployment (QFD) is a structured
approach to defining customer needs or
requirements and translating them into specific
plans to produce products to meet those
requirements. The "voice of the customer" is the
term to describe these stated and unstated
customer needs or requirements.

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Six Sigma
Translating the “Voice of the
Customer” using QFD
The House of Quality

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Getting Started:
Six Sigma and the Product Life Cycle

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Lean Thinking
 A focus on the removal of waste in every
step/task/activity of a process.
 Waste is defined as anything not necessary (non-
value added) to produce a product or service.
 Lean is a process improvement strategy that
facilitates an organization’s ability to become
highly responsive to customer demand while
producing top quality products or services in the
most efficient manner possible. The goal is to
achieve perfection through the total elimination
of waste in the value stream. Lean uses
incremental improvement to constantly expose
waste to balance operational and standard
workflows. Most notable examples are the supply
chains established by Toyota and Honda.

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Lean Thinking – “TIM WOODS”
Eliminate anything which does not add
value (8 Wastes):
• Transportation - unnecessary
• Inventory - obsolete
• Motion – unnecessary; layout
• Waiting - delays
• Overproduction – see inventory
• Over processing / over specifying
• Defects – scrap; rework…
• Skills – underutilization…

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The Evolution
of Six Sigma and Lean
Lean OR Six Sigma?
Lean Six Sigma
“Lean Sigma” Kaizen Blitz

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Integration of
Six Sigma and Lean
Leadership, Creativity, Innovation
• Waste, Non-Value Add
• Speed, Cycle Time
• Standardization
• Inventory Reduction
• Logistics Cost Reduction
• Kaizen
• Complex Problems
• Variation Reduction
• Stability, Predictability
• Process Capability
• Defect Prevention
• Design Excellence
Teaming and Employee Involvement
• Value Stream Mapping
• Pull Systems / 1-Piece Flow
• Kanban / Work Cells
• Visual Controls
• 5S
• Setup Reduction
• TPM
• Process Mapping
• Statistical Methods
• FMEA
• MSA / Gage R&R
•Cp & Cpk Analysis
•ANOVA
• DOE
Focus on
Improvement
Closed Loop
Performance
Knowledge
of
Tools
LEAN SIX SIGMA

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The Integration
of Six Sigma and Lean
Six Sigma Green Belt Certification
Body of Knowledge
B. Lean principles in the organization
1. Lean concepts and tools
Define and describe concepts such as value chain,
flow, pull, perfection, etc., and tools commonly
used to eliminate waste, including kaizen, 5S,
error-proofing, value-stream mapping,
2. Value-added & non-value-added activities
Identify waste in terms of excess inventory, space,
test inspection, rework, transportation, storage,
etc., and reduce cycle time to improve throughput.
3. Theory of constraints
Describe the theory of constraints.

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Lean Sigma
Statistical Thinking Principles:
1. All work occurs in a system of interconnected processes
2. Variation (and waste) exists in all processes
3. Understanding and reducing variation are the keys to improvement and
success
All improvement comes from understanding THEN reducing WASTE and
VARIATION in a process
What is the enemy of quality (productivity, efficiency…)?
NON-VALUE ADDED WORK and EXCESS VARIATION !
Lean Sigma
A management philosophy and disciplined problem-solving
METHODOLOGY backed by powerful tools using a cross-
functional team approach to eliminate waste and reduce service
errors / process defects to 3.4 ppm opportunities or less
(“world-class”).

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Lean Sigma: Expected Results

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Is Lean Sigma for You?
What are your company’s “brutal facts”?
(specifically in the areas of quality, costs and delivery)
Quality, price and delivery are controlled by
process capability.
Process capability is greatly limited by variation and
waste.
Decreasing process variation and non-value added work
leads to a decrease in defects, costs and cycle time.
Define a current problem (or opportunity)
that needs the rigor of a Lean Sigma
project…

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Lean Sigma Project Cycle

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Six Sigma: 6
More Info:
www.
isixsigma.com
sixsigmaforum.com (ASQ)
sixsigmaexchange.com
industryweek.com

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Six Sigma: 6
Opposing views:
http://money.cnn.com/2006/07/10/magazines/for
tune/rule4.fortune/index.htm
http://www4.asq.org/blogs/financial-services-six-
sigma/2007/01/even_the_wsj_doesnt_understand
.html

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“Progress”

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Lean Sigma Case Study –
Health Care
 Project Selection
“Cardiac catheterization labs represent a
significant capital investment for many hospitals.
Realizing a ROI is increasingly challenging, given the
introduction of advanced technologies and limitations
in reimbursement. To meet the challenges…hospitals
are pursuing strategies such as Six Sigma and Lean
techniques to improve throughput, maximize
equipment utilization and increase efficiency.
New York-Presbyterian Hospital recently
embarked on a comprehensive initiative aimed at
improving throughput in their cardiac catheterization
labs…”
- source: www.isixsigma.com

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Health Care
DEFINE
Improving first case start time was selected as a project by the Children's
Hospital of New York since it contributed to a significant amount of lost
productivity. The failure of the first case to start on time was delaying
subsequently scheduled cases and contributing to staff, physician and patient
dissatisfaction.
The Project Charter included:
Business Case and Problem Statement – Baseline data indicated that 62 % of the
first cases were not starting on time representing 267 hours of lost staff productivity and
unused capacity annually.
Project Scope –The start point of the cycle was patient's arrival at the hospital and the
end point of the patient's entrance into the cath lab. The charter also described areas
outside of the team's scope, such as lab turnaround time, which was the focus of another
team.
Goal Statement – A goal of 80 percent on-time starts was established.
Team Members – The team for the project included the cath lab director, staff,
cardiologists and anesthesiologists. The vice president of operations served as project
sponsor and oversaw the work of the team.
Timeline – A timeline including frequency of meetings, dates and times was agreed
upon at the team's first meeting and proved essential to keeping the project on track.

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Health Care
Cont’d
DEFINE - The project charter provided the team with focus and direction.
The team then developed a map describing the current process…
The process map pointed to one opportunity for immediate improvement –
streamlining the nursing assessment. Discussion during the process mapping
revealed some redundancy in the information gathered during the phone call the
day before and the nursing assessment completed the day of the procedure. The
team agreed that initiating the nursing assessment during this phone call would
eliminate duplicate data collection, and shorten the time needed to complete the
assessment the day of the procedure.

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Health Care
MEASURE
The team brainstormed using a fishbone diagram to identify all
the potential contributors to delaying the start of the first case.
Some of the factors identified included:
Patient arriving on time; Registration process; Transportation;
Timeliness of patient prep; Completion of assessments by the
cardiologist, anesthesiologist and nursing
Data was then collected to identify those factors having the
most significant impact on delaying the start of the first case.

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Health Care
ANALYZE
Regression analysis, a statistical tool used to model and
predict the relationship between variables, revealed that
the time it took to complete the cardiology
assessment was a key driver in whether the first case
would be completed on time.
The R-sq adjusted value showed that it accounted for about
60 percent of the variation in the process. Here is a table
showing the “first case start” statistical analysis:

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Health Care
ANALYZE
X Test Results
Statistically
Significant?
Nurse Test for Equal Variances p=.725 No
Nurse Moods Median p=.583 No
Nurse Regression p=.762 No
Latest Assessment Time Moods Median p=.432 No
Latest Assessment Time Test for Equal Variances p=.132 No
Latest Assessment Time Regression p=.177 No
Anesthesia Yes/No Moods Median p=.710 No
Anesthesia Yes/No Test for Equal Variances p=.318 No
Oral Pre-Med Yes/No Test for Equal Variances p=.981 No
Oral Pre-Med Yes/No Moods Median p=.288 No
Anesthesiologist Moods Median p=.389 No
Anesthesiologist Test for Equal Variances p=.013 Yes
Anesthesiologist Regression p=.625 No
Patient Arrival Test for Equal Variances p=.909 No
Patient Arrival Moods Median p=.615 No
Difference vs. Card. Assessment Regression p=.042 Yes
Time Patient on Table vs. Card. Assessment Regression p=0.00 Yes
Difference vs. Anesthesia Yes/No Regression p=.532 No
Difference vs. Nursing Assessment Regression p=.658 No
“highly”
significant

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Health Care
IMPROVE
The team used this information to discuss and develop plans to ensure the
cardiology assessment could be completed in a timelier manner. For
example, since the cardiologist typically initiates the cardiology assessment,
the director of cardiology explored other responsibilities and obligations
that might be interfering with timely completion of the assessment. As part
of developing a revised process, the team also completed a new process
flow map indicating a target completion time for each step in the process
that ultimately would lead to the desired case start time.
As shown in the table below, re-measurement of the process indicated a
dramatic improvement in the number of first cases starting on time and a
reduction in variation.
Data Categories Baseline Data Improve/Control Data
On-Time First Case Start 38 Percent 83 Percent
Baseline Z 1.44 2.47
Median 13 Minutes 0 Minutes
Mean 38.24 Minutes 6.33 Minutes
Standard Deviation 55.62 Minutes 22.4 Minutes

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Health Care
CONTROL
“Process control mechanisms were implemented to ensure
the changes could be sustained, and that the gains
achieved from improvement activities would not be lost
over time. The Control Plan outlined the procedure for
monitoring the critical X (completion of cardiology
assessment) as well as the number of on-time first case
starts. Regular reporting to the project's executive sponsor
reinforced the importance of the initiative and insured that
changes would become imbedded into the organization's
culture.”

LEAN SIGMA_SUNYSB_May08.ppt

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