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(Lean) Six Sigma: What is
It?
Gustavo DiazPrincipal, DQC, LLC
(954) 296-8446
2© 2020-2021 DQC, LLC. All Rights Reserved.
Presentation Outline
What is Six Sigma?
Phases of Six Sigma - DMAIC Define Measure Analyze / Evaluate Improve Control
What about the Belts?
3© 2020-2021 DQC, LLC. All Rights Reserved.
A Vision and Philosophical commitment to our customers to offer the highest quality, lowest cost products and services
A Metric that demonstrates quality levels at 99.9997%performance for products, services and processes
A Benchmark of our product and process capability for comparison to “best in class” organizations (σ levels)
A practical application of statistical tools and methods to help us measure, analyze, improve, and control our business processes based on data.
What is Six Sigma?
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What Six Sigma is Not
Just about statistics and number crunching
A quality program
Only for technical people
Used when the solution is known (low-hanging fruit)
Used for “firefighting”
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1. Reduces dependency on “tribal knowledge”
- Decisions based on facts and data rather than opinions
2. Attacks the high-hanging fruit (the hard stuff)- Eliminates chronic problems (common cause variation)
- Improves customer satisfaction
3. Provides a disciplined approach to problem solving- Changes the company culture
4. Creates a competitive advantage (or disadvantage)
5. Improves customer loyalty and… profits!
Why Companies Need Six Sigma?
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99.9% is already VERY GOOD!
But what could happen at a quality level of 99.9% (i.e., 1,000 ppm),
in our everyday lives (about 4.6σ)?
• More than 3,000 newborns accidentally falling
from the hands of nurses or doctors each year
• 4,000 wrong medical prescriptions each year
• 400 letters per hour which never arrive at their destination
• Two long or short landings at American airports each day
How good is good enough?
How can we get these results?
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13 wrong drug prescriptions per year 10 newborn babies dropped by doctors
/nurses per year Two short or long landings per year in all
the airports in the U.S. One lost article of mail per hour
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Six Sigma as a Metric
Sigma = σ = Deviation( Square root of variance )
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7
Axis graduated in Sigma
68.27 %
95.45 %
99.73 %
99.9937 %
99.999943 %
99.9999998 %
result: 317,300 ppm outside (deviation)
45,500 ppm
2,700 ppm
63 ppm
0.57 ppm
0.002 ppm
between + / - 1σ
between + / - 2σ
between + / - 3σ
between + / - 4σ
between + / - 5σ
between + / - 6σ
σ
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3 Sigma vs. 6 Sigma
The 3 σ Company The 6 σ Company
Spends 15~25% of sales dollars on cost of failure and recovery
Spends ~5% of sales dollars on cost of failure and recovery
Relies on inspection to find defects Relies on capable process that don’t produce defects
Does not have a disciplined approach to gather and analyze data
Uses Measure, Analyze, Improve, Control and Measure, Analyze, Design, Verify
Benchmarks themselves against their competition
Benchmarks themselves against the best in the world
Believes 99% is good enough Believes 99% is unacceptable
Defines CTQs internally Defines CTQs externally
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Sigma and PPM
2
3
4
5
6
308,537
66,811
6,210
233
3.4
σ PPM
Process Capability
Defects per Million Opportunities
Focusing on σ requires thorough process understanding and breakthrough thinking
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Motorola ROI 1987-1994
• 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.
Six Sigma ROI
General Electric ROI 1995-1998
• Company wide savings of over $1 Billion.
• Estimated annual savings to be 6.6 Billion by the year 2000.
Six Sigma History
Evolution of Quality after the 1990s
12
Companies Companies3MAmazonAmerican ExpressAtosAutoliv BAE Systems Bank of America Becton Dickinson Bechtel Boeing Caterpillar Inc. Computer Sciences Corporation Convergys Cooper Tire & Rubber Company Credit Suisse Damco Deere & Company Dell Denso Evonik Industries
Ford Motor Company General Electric HoneywellInventec Lionbridge MaerskMcKesson Corporation Motorola Mumbai's dabbawalas Northrop Grumman PolyOne Corporation Raytheon Sears Shop Direct Tata ConsultingTata SteelUnipart United States Army United States Marine Corps The Vanguard Group Wipro
© 2020-2021 DQC, LLC. All Rights Reserved.
13© 2020-2021 DQC, LLC. All Rights Reserved.
Six Sigma as a Philosophy
Internal &ExternalFailure Costs
Prevention &Appraisal
Costs
Old Belief4σC
osts
Internal &ExternalFailure Costs
Prevention &Appraisal
Costs
New BeliefCos
ts4σ
5σ
6σ
Quality
Quality
Old Paradigm
High Quality = High Cost
New Belief
High Quality = Low Cost
σ is a measure of how much variation exists in a process
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Six Sigma Tools
Process Mapping Tolerance Analysis
Structure Tree Components Search
Pareto Analysis Hypothesis Testing
Gauge R & R Regression Analysis
Rational Subgrouping Design of Experiment (DoE)
Baselining SPC
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Project defined in Business Terms
Cross Functional Team as problem solvers and empower to make decisions
DMAIC Problem Strategy used
Qualitative and Statistical tools used
Sustained Business Results Achieved
What Does Six Sigma Look Like?
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Six Sigma Principles
Customer Focus
Leadership
Innovative and Proactive
Team oriented
World Class Quality
Fact Driven decision-making
Process Management
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Breakthrough Strategy
Characterization Phase 2:Measure
Phase 3:Analyze
Optimization
Phase 4:Improve
Phase 5:Control
Projects are worked through these 5 main phases of the Six Sigma methodology.
Phase 1:Define
Problem-Solving Methodology
DEFINE PHASE
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19© 2020-2021 DQC, LLC. All Rights Reserved.
Define Phase
Define Customer requirement(s) impacted by the problem or defect
Prioritize Customer requirement(s)
Create Problem Statement (What? Who? Where? When? Why? How?)
Define Business Process (mapping)
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ReduceComplaints
(int./ext.)
ReduceCost
ReduceDefects
Problem Definitions need to be based onquantitative facts supported by analytical data.
What are the Goals?
What do you want to improve? What is your ‘Y’?
Problem Definition
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Define Phase Tools
Customer Survey CTQ Diagram Customer Requirement Analysis SIPOC Model Kano Analysis Quality Functional Deployment (QFD) Literature Review (benchmarking) Gate Review
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Define Phase Deliverables
Project or Gate Review
Project Charter Prioritized impacted customer requirement(s) Business Case (5W-1H) Problem Statement (Project) Goal Statement Scope of process Risk analysis
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Project Charter
Business Case
Problem Statement
Goal Statement
Team Members (selection and development)
Team Role & Responsibility
Action plan vs. budget
MEASURE Phase
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25© 2020-2021 DQC, LLC. All Rights Reserved.
Measure Phase
Identify measurement and variation Determine data type Develop data collection plan Perform measurement system analysis (MSA) Perform data collection (rational subgrouping) Perform process capability analysis (Cp/Cpk)
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To understand where you want to be, you need to know how to get there.
Map the Process
Measure the Process
Identify the variables - ‘X’
Understand the Problem -’Y’ = function of variables X’s
Y = f(X’s)
Measure Phase
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DefineProblem
UnderstandProcess
CollectData
ProcessPerformance
Process Capability- Cp/Cpk- Run Charts- DPMO, CoPQ
Understand Problem(Control or Capability)
Data Types- Defectives- Defects- Continuous
Measurement Systems Evaluation (MSE)
Define Process-Process Mapping
Historical Performance
Brainstorm Potential Defect Causes
Customerrequirements
Defect Statement
Project Goals
Measure Phase
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How do we know our process?
Process Map
Historical Data
Fishbone
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Measure Phase Tools
SIPOC-RM CTQ-R Check Sheet MSA Basic Statistics Rolled Throughput Yield (RTY) Process Capability (short & long-term) DPMO Sigma level COPQ calculation
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Measure Phase Deliverables
Project or Gate Review
Customer satisfaction Effectiveness of process (Six Sigma principle) Efficiency of process (Lean principle) Baseline sigma (Yield, DPMO, CP, Cpk) Cost of poor quality (CoPQ)
ANALYZE Phase
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32© 2020-2021 DQC, LLC. All Rights Reserved.
Analyze / Evaluate Phase
Data Analysis
Process Analysis
Formulate Hypothesis
Test the hypothesis
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Analyze / Evaluate Phase
Run charts Pareto charts Relation Diagram Process Analysis (QFD, FMEA, XY Matrix) Descriptive Statistics
Histograms, bar charts Scatter diagrams C-E diagrams
Hypothesis Testing Chi-square T-Test ANOVA Correlation & Regression Normality Non-parametric testing
In many cases, the data sample can be transformed so that it is approximately normal. For example, square roots, logarithms, and reciprocals often take a positively skewed distribution and convert it to something close to a bell-shaped curve
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35© 2020-2021 DQC, LLC. All Rights Reserved.
Statistical Analysis
0.0250.0200.0150.0100.0050.000
7
6
5
4
3
2
1
0
Freq
uenc
y
0.0250.0200.0150.0100.0050.000
30
20
10
0
Fr
eque
ncy
Is the factor important?
Do we understand the impact of the factor?
Has our improvement made an impact?
What is the true impact?
Hypothesis Testing
Regression Analysis
5545352515 5
60
50
40
30
20
10
0
X
Y
95% PI
Regression
Apply statistics to validate actions & improvements
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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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Analyze / Evaluate Phase
Project or Gate Review
Validated root cause statement
Planning for a pilot
Continue data collection and deployment of SPC
IMPROVE Phase
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39© 2020-2021 DQC, LLC. All Rights Reserved.
Improvement Phase
Generate Improvement alternatives
Validate Improvement
Create “should be” process map
Update FMEA
Perform Cost/Benefit analysis
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Improvement Phase
Brain Storming
Innovation and Creativity
Multi-criteria Weighting (Pugh matrix)
Mistake-proofing (Poka-yoke) the process
Change Management tools
DOE
Cost/Benefit Analysis
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Improvement Phase
Project or Gate Review
Validated pilot study results
Cost benefit analysis
Control phase planning
Communication planning
CONTROL Phase
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43© 2020-2021 DQC, LLC. All Rights Reserved.
Control Phase Goals
Develop control strategy and control plan
Continue with communication and control plans
Update procedures and training plan
Monitoring results
Corrective action as needed
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Control Phase
1. Select potential causal variable(s), X’s. Proven vital few X’s
2. Define Control Plan- 5Ws for optimal ranges of X’s
3. Validate Control Plan- Observe response variable (Y)
4. Implement / Document Control Plan5. Audit Control Plan6. Monitor Performance Metrics
How to create a Control Plan?
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Control Phase
Control Phase Activities:
- Confirmation of Improvement- Confirmation team solved the practical problem- Benefit validation- Buy into the Control plan- Quality plan implementation- Procedural and system changes- Statistical process control (SPC) implementation- Closure documentation- Audit process- Scoping next project (leverage phase)
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Control Phase
Project / Gate Review
Communication Plans Control Plans SPC deployment Full solution(s) implementation Standard Operating Procedures (SOPs) Work instructions Risk analysis
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How do we select the correct Control Chart?
Type Data
Ind. Meas. or subgroups
Normally dist. data
Interest in sudden mean changes
Graph defects of defectives
Oport. Area constant from sample to sample
X, Rm
p, np
X - RMA, EWMA or CUSUM and Rm
u
C, u
Size of the subgroup constant
p
If mean is big, X and R are effective too
Ir neither n nor p are small: X - R, X - Rm are effective
More efective to detect gradual changes in long term
Use X - R chart with modified rules
VariablesAttributes
Measurement of subgroupsIndividuals
Yes
No
No
Yes
Yes
No
Yes
No
Defects Defectives
Control Phase
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49© 2020-2021 DQC, LLC. All Rights Reserved.
Improvement fully implemented and process re-baselined.
Quality Plan and control procedures institutionalized.
Owners of the process: Fully trained and running the process.
Any required documentation done.
History binder completed. Closure cover sheet signed.
Score card developed on characteristics improved and reporting method defined.
Project Closure
Six Sigma Belts and Stakeholders
Leadership Responsibilities
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