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Overview of Six Sigma DMAIC Process
Define – Define the project targets and customer (internal and external)
deliverables.
Measure – Measure the process to determine the current process performance
baseline).
Analyze – Find out the root causes of the defects.
Improve – Improve the process by eliminating defects.
Control – Control the future performance.
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Define
Inputs
Important stake
holder
Business Need
/ Business
Case
Tools and Techniques
Benchmarking
Market research data
Historical quality
information
Team experience
Quality Function
Deployment
CTQ flow down
Kano customer satisfaction
levels
Customer value analysis
Outputs
VOC
KPI
Balance
scorecard
Financial
measures
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Define
Inputs
VOC
KPI
Balance
scorecard
Financial
measures
Tools and Techniques
Charter negotiations
Templates
Expert judgment
Decomposition
GANTT chart
CPM & PERT
Outputs
Project charter
Performance
metrics
WBS
Network
diagrams
Project
management
plan and
baselines
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Measure
Inputs
Network
diagrams
Project
management
plan and base
lines
Project charter
Performance
metrics
Tools and Techniques
Business process
management
SIPOC
Process maps and
flowcharts
Outputs
Processes
Process
characteristics
Process flow
metrics
Process inputs
and outputs
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Measure
Inputs
Processes
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Ishikawa diagrams
Relational matrices
Prioritization matrix
Outputs
Current
process
performance
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Measure
Inputs
Continuous and
discrete data
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Measurement scale
Data integrity and
accuracy
Prioritization matrix
Data collection methods
Check sheets
Coded data
Automated gauging
Outputs
Sampling
strategies
Error
frequencies
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Measure
Inputs
Continuous and
discrete data
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Measuring instruments
Gauge R and R study
Control chart method
Calibration systems
Outputs
Measurement
systems
analysis
Measurement
correlation
Measurement
error
Gauge
Acceptance
criteria
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Measure
Inputs
Continuous and
discrete data
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Descriptive (Enumerative)
statistics
Population parameters and
sample statistics
Central limit theorem
Central tendencies
Stem-and-leaf plots
Box and Whisker
plots
Histograms and
frequency polygons
Probability plots
Run chart
Scatter diagram
Outputs
Frequency
distributions
Measures of
dispersion
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Measure
Inputs
Continuous and
discrete data
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Inferential (analytical) statistics
Probability
Mutually exclusive
Independent
Conditional
Combinations,
permutations
Continuous distributions and
probability distribution
functions
Uniform
Normal
Bivariate normal
Lognormal
Exponential
Weibull
Chi-square
Student’s t
F
Discrete distributions and
mass functions
Binomial
Poisson
Hypergeometric
multinomial
Outputs
Frequency
distributions
Measures of
dispersion
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Measure
Inputs
Continuous and
discrete data
Process
characteristics
Process flow
metrics
Process inputs
and outputs
Tools and Techniques
Process capability studies
Sigma level – short term
and long term
Outputs
Cp, cpk
Pp, ppk
Cpm
Process
performance
metrics
DPU
PPM
DPMO
FPY
RTY
COPQ
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Analyze
Inputs
Measurement
systems
Process
capability
indices
Process
parameters
affecting CTQs
Process
performance
metrics
Cost of poor
quality (COPQ)
Tools and Techniques
Failure Mode and Effect
Analysis (FMEA)
Tree diagram
Gap analysis
Root cause analysis
Five Whys
Pareto Chart
Fault tree analysis
Cause-and-effect
analysis
Outputs
Potential
causes of
defects
Risk Priority
Number (RPN)
Corrective
action to be
taken
Comparison of
current and
future state
Value added
and non-value
added
activities
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Analyze
Inputs
Validating
potential
causes
Tools and Techniques
Testing of hypothesis
Point and interval
estimation
Biased / Unbiased
estimator
Confidence intervals
Null / alternative
hypothesis, type 1 and
type 2 error, power of a
test
Test for means,
variances, and
proportions (one sample
and two sample)
Goodness of fit test
ANOVA (One-way
ANOVA and Two-way
ANOVA)
Non-parametric tests
Outputs
Validated
causes
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Analyze
Inputs
Validating
potential
causes
Tools and Techniques
Correlation and regression
analysis
Variables and
relationships
Correlation
coefficient
Simple linear
regression model
Method of least
squares
Residuals
Simple linear
regression
hypothesis testing
(Test for correlation
coefficient, slope
parameter)
Sources of variation
Coefficient of
determination
Multiple linear
regression
Outputs
Relationships
between
variables
Best fitted and
validated
model
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Analyze
Inputs
Potential
causes of
defects
Non-value
added activities
Validated
causes
Tools and Techniques
Kanban
Poka-Yoke
5S
Standard operations
(work)
Kaizen and Kaizen
Blitz
SMED
Continuous flow
manufacturing (CFM)
Theory of constraints
(TOC)
Outputs
Waste
elimination
Cycle-time
reduction
Decreased
inventory
Decreased
operating
expenses
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Improve
Inputs
Potential
causes of
defects
Non-value
added activities
Validated
causes
Tools and Techniques
Design of experiment
(DOE)
DOE terminologies
DOE planning
process
Types of
experiment designs
Interaction
One factor
experiments
Completely
randomized one
factor experiments
Randomized block
experiments
Latin square designs
Yales order
Fractional factorial
experiments
Outputs
Identification of
best solution
(through
experimentation)
for
implementation
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Improve
Inputs
Identification of
best solution
(through
experimentation)
for
implementation
Tools and Techniques
Pilot runs
Simulations
Models
Prototypes
Implementation
strategies
Risk analysis and
mitigation
Scenario
planning
FMEA
SWOT analysis
Outputs
Implementation
plan
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Control
Inputs
Identification of
solutions for
implementation
Implementation
plan
Tools and Techniques
Statistical process control
(SPC)
Special and common
cause of variation
Rational sub-
grouping
Variable control
charts (X-bar and R,
X-bar and s, I-MR)
Attribute control
charts (p, np, u, c)
CUSUM chart
MAMR chart
Total productive
maintenance (TPM)
Lean tools (5S, visual
factory, Kaizen, Kanban,
Poka-yoke)
Outputs
Implemented
solutions
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Control
Inputs
Implemented
solutions
Tools and Techniques
Measurement system
improvement
Measurement
system analysis
(MSA)
Process capability
analysis
Graphical data
analysis
Statistical testing
Process audit
Product audit
Internal audit
Outputs
Revised
measurement
system
Control plan for
sustaining
benefits
Improved
process
capability
Lessons
learned
Training plan
deployment
Documentation