Six Sigma aims to reduce defects and variation in processes to improve customer satisfaction and increase profits. It originated to improve manufacturing but was later applied more broadly. The Six Sigma process involves Define, Measure, Analyze, Improve, and Control (DMAIC) to first identify issues and their causes, test solutions, and ensure gains are sustained. Key aspects include defining critical metrics, measuring current performance, analyzing processes statistically to determine root causes of defects, improving processes by addressing these causes, and controlling processes ongoing to maintain results.

1. Purpose of six sigma :Purpose of six sigma :
To make customer happier and increase profitsTo make customer happier and increase profits

2.  Six Sigma originated as a set of practices
designed to improve manufacturing processes
and eliminate defects, but its application was
subsequently extended to other types of
business processes as well.In Six Sigma, a
defect is defined as anything that could lead to
customer dissatisfaction

3.  Continuous efforts to achieve stable and
predictable process results (i.e. reduce process
variations)
 Manufacturing and business processes have
characteristics that can be measured, analyzed,
improved and controlled.
 Achieving sustained quality improvement
requires commitment from the entire
organization, particularly from top-level
management.

4.  1987 Motorola Develops Six Sigma
 Raised Quality Standards
 Other Companies Adopt Six Sigma
 GE
Promotions, Profit Sharing (Stock Options),
etc. directly tied to Six Sigma training.

5.  Delighting Customers.
 Reducing Cycle Times.
 Keeping up with Technology Advances.
 Retaining People.
 Reducing Costs.
 Responding More Quickly.
 Structuring for Flexibility.
 Growing Overseas Markets.

6.  Generated sustained success
 Project selection tied to organizational strategy
 Customer focused
 Profits
 Project outcomes / benefits tied to financial
reporting system.
 Full-time Black Belts in a rigorous, project-
oriented method.
 Recognition and reward system established to
provide motivation.

7. It is a Philosophy
– Anything less than ideal is
an opportunity for
improvement
– Defects costs money
– Understanding processes
and improving them is the
most efficient way to
achieve lasting results
It is a Process
– To achieve this level of
performance you need to:
Define, Measure, Analyse,
Improve and Control
It is Statistics
– 6 Sigma processes will
produce less than 3.4
defects per million
opportunities

8. • Know What’s Important
to the Customer (CTQ)
• Reduce Defects
(DPMO)
• Center Around Target
(Mean)
• Reduce Variation
(Standard Deviation)

9. • Y
• Dependent
• Output
• Effect
• Symptom
• Monitor
• X1 . . . XnX1 . . . Xn
• IndependentIndependent
• Input-ProcessInput-Process
• CauseCause
• ProblemProblem
• ControlControl
f(X)f(X)Y=Y=
The focus of Six sigma is to identify and control XsThe focus of Six sigma is to identify and control Xs

10. • Define
• Measure
• Analyze
• Improve
• Control
• DefineDefine
• MeasureMeasure
• AnalyzeAnalyze
• DesignDesign
• VerifyVerify
DMAICDMAIC DMADVDMADV
• Existing Processes • New ProcessesNew Processes
• DFSSDFSS

11. Key Concepts

12.  CTQ characteristics for the process, service or
process
 Measure of “What is important to Customer”
 6 Sigma projects are designed to improve CTQ
 Examples:
 Waiting time in clinic
 Spelling mistakes in letter
 % of valves leaking in operation

13.  A nonconforming unit is a defective unit
 Defect is nonconformance on one of many possible
quality characteristics of a unit that causes
customer dissatisfaction.
 A defect does not necessarily make the unit
defective
 Examples:
 Scratch on water bottle
 (However if customer wants a scratch free bottle, then
this will be defective bottle)

14.  Circumstances in which CTQ can fail to meet.
 Number of defect opportunities relate to
complexity of unit.
 Complex units – Greater opportunities of defect
than simple units
 Examples:
 A units has 5 parts, and in each part there are 3
opportunities of defects – Total defect opportunities
are 5 x 3 = 15

15.  Number of defects divided by number of defect
opportunities
 Examples:
 In previous case (15 defect opportunities), if 10 units
have 2 defects.
 Defects per unit = 2 / 10 = 0.2
 DPO = 2 / (15 x 10) = 0.0133333

16.  DPO multiplies by one million
 Examples:
 In previous case (15 defect opportunities), if 10 units
have 2 defects.
 Defects per unit = 2 / 10 = 0.2
 DPO = 2 / (15 x 10) = 0.0133333
 DPMO = 0.013333333 x 1,000,000 = 13,333
Six Sigma performance is 3.4 DPMO
13,333 DPMO is 3.7 Sigma

17.  Proportion of units within specification divided
by the total number of units.
 Examples:
 If 10 units have 2 defectives
 Yield = (10 – 2) x 100 /10 = 80 %
 Rolled Through Yield (RTY)
 Y1 x Y2 x Y3 x ……. x Yn
 E.g 0.90 x 0.99 x 0.76 x 0.80 = 0.54

18. What is Sigma?

19.  Shot a rifle?
 Played darts?
What is the point of these sports?
What makes them hard?

20. Jack
Jill
Who is the better shooter?
 Shot a rifle?
 Played darts?

21.  Deviation = distance between
observations and the mean (or
average)
Observations Deviations
10 10 - 8.4 = 1.6
9 9 - 8.4 = 0.6
8 8 - 8.4 = -0.4
8 8 - 8.4 = -0.4
7 7 - 8.4 = -1.4
averages 8.4 0.0
Jack
8
7
10
8
9
Jill

22.  Deviation = distance between
observations and the mean (or average)
Observations Deviations
7 7 - 6.6 = 0.4
7 7 - 6.6 = 0.4
7 7 - 6.6 = 0.4
6 6 - 6.6 = -0.6
6 6 - 6.6 = -0.6
averages 6.6 0.0
Jack
Jill
7
6
7
7
6

23. Sigma
level
DPMO
Percent
defective
Percentage yield
1 691,462 69% 31%
2 308,538 31% 69%
3 66,807 6.7% 93.3%
4 6,210 0.62% 99.38%
5 233 0.023% 99.977%
6 3.4 0.00034% 99.99966%
7 0.019 0.0000019% 99.9999981%

24.  Variance = average distance between
observations and the mean squared
Observations Deviations
10 10 - 8.4 = 1.6
9 9 – 8.4 = 0.6
8 8 – 8.4 = -0.4
8 8 – 8.4 = -0.4
7 7 – 8.4 = -1.4
averages 8.4 0.0
Squared Deviations
2.56
0.36
0.16
0.16
1.96
1.0
Variance
Jack
8
7
10
8
9
Jill

25.  Variance = average distance between
observations and the mean squared
Observations Deviations
7 7 - 6.6 = 0.4
7 7 - 6.6 = 0.4
7 7 - 6.6 = 0.4
6 6 – 6.6 = -0.6
6 6 – 6.6 = -0.6
averages 6.6 0.0
Squared Deviations
0.16
0.16
0.16
0.36
0.36
0.24
Variance
Jack
Jill
7
6
7
7
6

26.  Standard deviation =
square root of
variance
Average Variance Standard
Deviation
Jack 8.4 1.0 1.0
Jill 6.6 0.24 0.4898979
Jack
Jill
But what good is a standard deviation

27. The world tends to
be bell-shaped
Most
outcomes
occur in the
middle
Fewer
in the
“tails”
(lower)
Fewer
in the
“tails”
(upper)
Even very rare
outcomes are
possible
Even very rare
outcomes are
possible

28. Add up the dots on the dice
0
0.05
0.1
0.15
0.2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Sum of dots
Probability
1 die
2 dice
3 dice
Here is why:Here is why: Even outcomes that are equallyEven outcomes that are equally
likely (like dice), when you addlikely (like dice), when you add
them up, become bell shapedthem up, become bell shaped

29. Normal distributions are divide up
into 3 standard deviations on
each side of the mean
Once your that, you
know a lot about
what is going on
And that is what a standard deviation
is good for
“Normal” bell shaped
curve

30.  Common Causes:
 Random variation within predictable range (usual)
 No pattern
 Inherent in process
 Adjusting the process increases its variation
 Special Causes
 Non-random variation (unusual)
 May exhibit a pattern
 Assignable, explainable, controllable
 Adjusting the process decreases its variation

31.  Process and Control limits:
 Statistical
 Process limits are used for individual items
 Control limits are used with averages
 Limits = μ ± 3σ
 Define usual (common causes) & unusual (special
causes)
 Specification limits:
 Engineered
 Limits = target ± tolerance
 Define acceptable & unacceptable

32. Another View
LSL USL USLLSL
Off-Target Large Variation
On-Target
Center
Process
Reduce
Spread
The statistical view of a problem
USLLSL LSL = Lower spec limit
USL = Upper spec limit
LSL = Lower spec limit
USL = Upper spec limit

33. Good quality:
defects are
rare (Cpk>1)
Poor quality:
defects are
common (Cpk<1)
Cpk measuresmeasures “Process Capability”
If process limits and control limits are at the same location, Cpk = 1. Cpk ≥ 2 is exceptional.
μ
target
μ
target

34. Good quality: defects are rare (Cpk>1)
Poor quality: defects are common (Cpk<1)
Cpk = min
USL – x
3σ
=
x - LSL
3σ
=
3σ = (UPL – x, or x – LPL)
= =
14 20 26
15 24
24 – 20
3(2)
= =.667
20 – 15
3(2)
= =.833

35. 1 122 3 4 5 6 7 8 9 10 11
1σ 1σ 1σ 1σ 1σ1σ
6σ
LSL USL
+6σ−6σ
A Six Sigma Process –
Predictably twice as good as what
the customer wants

36. 2 3 4 5 6 7 8 9 1210 16151413111
LSL USL
6 Sigma curve
3 Sigma curve

37. 2 3 4 5 6 7 8 9 1210 16151413111
LSL USL
SD = 1
1.5 SD 1.5 SD

38. 3
4
5
6
7
66810
6210
233
3.4
0.02
Sigma
DPMO
On one condition :
Calculate the defects
and estimate the
opportunities in the
same way...

39. 0
100,000
200,000
300,000
400,000
500,000
600,000
1.5 2.5 3.5 4.5 5.5
# of Sigmas
#ofDefectperMillion
Sigma Defects
numbers per million
1.5s 500,000
2.0s 308,300
2.5s 158,650
3.0s 67,000
3.5s 22,700
4.0s 6,220
4.5s 1,350
5.0s 233
5.5s 32
6.0s 3.4

40. Components of Six Sigma

41. Two components of Six
Sigma
1. Process Power
2. People Power

43. P
DC
A
Plan
DoCheck
Act
Act on what
was learned
Check the results
Plan the change
Implement the
change on a small
scale.

44. Practical
Problem
Statistical
Problem
Statistical
Solution
Practical
Solution

45.  Define
 What is important?
 Measure
 How are we doing?
 Analyze
 What is wrong?
 Improve
 Fix what’s wrong
 Control
 Ensure gains are maintained
to guarantee performance

46. D
Define
M
Measure
A
Analyze
I
Improve
C
Control
Identify and state the practical problem
Validate the practical problem by collecting data
Convert the practical problem to a statistical one, define
statistical goal and identify potential statistical solution
Confirm and test the statistical solution
Convert the statistical solution to a practical solution

47. D
Define
M
Measure
A
Analyze
I
Improve
C
Control
VoCVoC - Who wants the project and why ?
The scope of project / improvement (SMART Objective)
Key team members / resources for the project
Critical milestones and stakeholder review
Budget allocation

48. Ensure measurement system reliability
Prepare data collection plan
Collect data
- Is tool used to measure the output variable flawed ?
- How many data points do you need to collect ?
- How many days do you need to collect data for ?
- What is the sampling strategy ?
- Who will collect data and how will data get stored ?
- What could the potential drivers of variation be ?
D
Define
M
Measure
A
Analyze
I
Improve
C
Control

49. How well or poorly processes are working compared with
- Best possible (Benchmarking)
- Competitor’s
Shows you maximum possible result
Don’t focus on symptoms, find the root cause
D
Define
M
Measure
A
Analyze
I
Improve
C
Control

50. Present recommendations to process owner.
Pilot run
- Formulate Pilot run.
- Test improved process (run pilot).
- Analyze pilot and results.
Develop implementation plan.
- Prepare final presentation.
- Present final recommendation to Management Team.
D
Define
M
Measure
A
Analyze
I
Improve
C
Control

51. Don’t be too hasty to declare victory.
How will you maintain to gains made?
- Change policy & procedures
- Change drawings
- Change planning
- Revise budget
- Training
D
Define
M
Measure
A
Analyze
I
Improve
C
Control

52. Step Consequences if the step is omitted
1. Define
2. Measure
3. Analyze
4. Improve
5. Control

53.  Benchmark
 Baseline
 Contract / Charter
 Kano Model
 Voice of the
Customer
 Quality Function
Deployment
 Process Flow Map
 Project
Management
 “Management by
Fact” – 4 What’s
 7 Basic Tools
 Defect Metrics
 Data Collection,
Forms, Plan,
Logistics
 Sampling
Techniques
 Cause & Effect
Diagrams
 Failure Models &
 Effect Analysis
 Decision & Risk
Analysis
 Statistical Inference
 Control Charts
 Capability
 Reliability Analysis
 Root Cause
Analysis
 5 Why’s
 Systems Thinking
 Design of
Experiments
 Modelling
 Tolerancing
 Robust Design
 Process Map
Statistical Controls
 Control Charts
 Time Series
Methods
Non Statistical
Controls
 Procedure
adherence
 Performance
Mgmt
 Preventive activities
 Poke yoke
Define
What is wrong?
Define
What is wrong?
Measure
Data & Process
capability
Measure
Data & Process
capability
Analyze
When and where
are the defects
Analyze
When and where
are the defects
Improve
How to get
to six sigma
Improve
How to get
to six sigma
Control
Display
key measures
Control
Display
key measures

54. Two components of Six
Sigma
1. Process Power
2. People Power
Tell me, I forget. Show me , I remember. Involve me, I understand.

55. Master
Black
Belt
Black Belts
Green Belts
Team Members /
Yellow Belts
Champions
Mentor, trainer, and coach of Black Belts and others
in the organization.
Leader of teams implementing the six sigma
methodology on projects.
Delivers successful focused projects using
the six sigma methodology and tools.
Participates on and supports
the project teams, typically in
the context of his or her existing
responsibilities.

56. Champion
Black
Belt
Black
Belt
Black
Belt
Green
Belt
Green
Belt
Green
Belt
Green
Belt
Green
Belt
Yellow
Belt
Yellow
Belt
Yellow
Belt
Yellow
Belt
Master
Black
Belt

57. Senior
Executives
Champions /
Process owners
Black-Belt
Green Belt
Employees
(Yellow-Belt)
Executive overview
2/3 Days Provide Leadership
Champions
Training - I
2 days
Champions
Training –II
3 days
Process Mgmt. &
Project
champion
Week
2
Week
3
Week
4
Training /
Facilitation
skills
Project-work
Master Black-Belt
-As Trainer
-Coach teams
-Facilitate
improvement projects
1 Week Green-Belt Training
- Part of project teams
- Sometime lead the
teams
1 / 2 Days core training on
Six-Sigma
- General process
control &
improvement
- Project Team
Member
Black-Belt
Project work
Position in Six Sigma
Organisation
Typical
Training
Expected Role
Post Training
+
(Total 5 days)
Week
1

58. • Plans improvement projects
• Charters or champions chartering
process
• Identifies, sponsors and directs Six Sigma
projects
• Holds regular project reviews in
accordance with project charters
• Includes Six Sigma requirements in
expense and capital budgets

59. • Identifies and removes organizational and
cultural barriers to Six Sigma success.
• Rewards and recognizes team and
individual accomplishments (formally and
informally)
• Communicates leadership vision
• Monitors and reports Six Sigma progress
• Validates Six Sigma project results
• Nominates highly qualified Black Belt
and/or Green Belt candidates

60. Roles Responsibilities
-Enterprise Six Sigma expert
-Permanent full-time change
agent
-Certified Black Belt with
additional specialized skills or
experience especially useful in
deployment of Six Sigma
across the enterprise
- Highly proficient in using Six Sigma
methodology to achieve tangible business
results.
-Technical expert beyond Black Belt level
on one or more aspects of process
improvement (e.g., advanced statistical
analysis, project management,
communications, program administration,
teaching, project coaching)
-Identifies high-leverage opportunities for
applying the Six Sigma approach across
the enterprise
-Basic Black Belt training
-Green Belt training
-Coach / Mentor Black Belts

61. Roles Responsibilities
- Six Sigma technical expert
- Temporary, full-time change
agent (will return to other duties
after completing a two to three
year tour of duty as a Black Belt)
- Leads business process
improvement projects where Six
Sigma approach is indicated.
- Successfully completes high-impact
projects that result in tangible benefits
to the enterprise
- Demonstrated mastery of Black Belt
body of knowledge
- Demonstrated proficiency at achieving
results through the application of the
Six Sigma approach
- Coach / Mentor Green Belts
- Recommends Green Belts for
Certification

62. Roles Responsibilities
- Six Sigma Project originator
- Part-time Six Sigma change
agent. Continues to perform
normal duties while participating
on Six Sigma project teams
- Six Sigma champion in local
area
- Recommends Six Sigma projects
- Participates on Six Sigma project
teams
- Leads Six Sigma teams in local
improvement projects

63. Roles Responsibilities
- Learns and applies Six Sigma
tools to projects
- Actively participates in team tasks
- Communicates well with other team
members
- Demonstrates basic improvement tool
knowledge
- Accepts and executes assignments as
determined by team

64. • Hard Savings:
– Cost Reduction
• Energy Saving
• Raw Material saving
• Reduced Rejection, Waste, Repair
– Revenue Enhancement
• Increased production
• Yield Improvement
• Quality Improvement

65. • Hard Savings:
– Cash flow improvement
• Reduced cash tied up in inventory
• Reduced late receivables, early payables
• Reduced cycle time
– Cost and Capital avoidance
• Optimizing the current system / resources
• Reduced maintenance costs
Types of Savings

66. • Soft Savings:
– Customer Satisfaction / Loyalty
– Employee Satisfaction
Types of Savings

67. • Direct Payroll
– Full time (Black Belts, Master Black Belts)
• Indirect Payroll
– Time by executives, team members, data
collection
• Training and Consulting
– Black Belt course, Overview for Mgmt etc.
• Improvement Implementation Costs
– Installing new solution, IT driven solutions etc.

68. • Three basic qualifications:
– -There is a gap between current and desired /
needed performance.
– The cause of problem is not clearly
understood.
– The solution is not pre-determined, nor is
the optimal solution apparent.
How many projects out of 20 now
qualify as Six sigma projects?