1. Six Sigma Overview

2. 4 Sigma Process Capability 99.38% Current Standard
6 Sigma Process Capability 99.99966% World-Class
Long-Term Yield
3 Sigma Process Capability 93.32% Historical Standard
The Classical View of Performance
• Six-Sigma is a philosophy:
• Why isn’t “99% acceptable” good enough...??
– 20,000 lost articles of mail every hour.
– 15 minutes each day of unsafe drinking water.
– 5,000 incorrect surgical procedures per week.
– 4 or more accidents per day at major airports.
– 200,000 wrong drug prescriptions each year.
– 7 hours each month without electricity.

3. History of 6 Sigma
• 6 Sigma manufacturing philosophy came from Motorola
They recognised that sufficient process improvement would not
occur using a conventional approach to quality. It was developed
to help them reduce variation within a process by focusing effort
on improving inputs to a process rather than reacting to outputs.
• The process was failing the customer expectations
– Traditionally, processes aimed for process capability of 3 to 4
sigma (Cpk=1.0 to 1.33 or 93% to 99.3% acceptable)
– The customer received 6200 defective product per million at best
– Processes now aim for 6 sigma (Cpk=2)
– The customer would receive 3.4 defective product per million
On target, minimum process variation

4. 6 sigma Process Capability
“What is it (CPK)”
• 3 Sigma ( Process capability of 1 CPK )
– if the process (lorry) slightly varies then the scrap or damage will
occur
• 6 Sigma ( Process capability of 2 CPK )
– if the process (lorry) varies, there will be no scrap or damage
Curbs
= required
process tolerances
CPK of 2
(6 sigma)
CPK of 1
(3 sigma)

5.  Variation exists in everything. Even the
best machine cannot make every unit
exactly the same.
 Improved capability, becomes a necessity,
due to the need of :
• improved designs
• lower costs
• better performance
 All of this leads to the need of tighter
tolerances
 This means that the ability to operate to a
tight tolerance, without producing defects
becomes a major advantage
Understanding Variability

6. Improvement methodology
On target,
minimum process variation
KPIV
Key
Process
Input
Variables
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw materials,
components, etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality
Characteristics:
Outputs

7. D M A I CD M A I C
Define
Measure
Analyze
Improve
Control
Improvement methodology

8. Define
Improvement methodology
• Define terms of reference (Charter the
project)
– Team / customer / project charter
– Brain storming
– Mind maps
– Affinity diagrams
– High level Process Maps
– Systematic diagrams / Fault tree
– Business Process Mapping
• Define customer requirements (Voice of
the customer)
– QFD Quality Function Deployment
•To develop a team charter.
•To define the customers
and their requirements
(CTQ Critical to Quality).
•To map the business
process to be improved
Characteristics
Importance out of 10
Product / customers

9. Define
• Define terms of reference (charting a project)
– What you can deliver to the customer and the support you need
from the customer to facilitate a successful improvement (contract
of engagement)
• Brain storming, Mind maps, Affinity diagrams, High level Process
Maps, Systematic diagrams / Fault tree, Business Process Mapping
– Tools to explore a problem, project or current thinking.
– Tools to group those ideas logically.
– Then define a route map to improvement, the risk involved and
how to mitigate that risk.
• Define customer requirements (Voice of the customer)
– QFD Quality Function Deployment, is a method of defining what
the customer needs, what is critical to there business success &
prioritise objectives to meet the customer need.

10. Measure
Improvement methodology
• Voice of the process
– Data Collection - 7 quality tools
– Tally charts
– Bar charts
– Pareto
– Run charts
– Control charts
– Cause & effect
– Check sheets
– Evaluate measurement systems
• Gauge R&R
• Select measures of performance
– Quality Function Deployment
•To measure and
understand baseline
performance for the
current process

11. Measure
• Voice of the process (7 quality tools)
– Tally charts, Bar charts, Pareto, Run charts, Control charts, Cause
& effect, Check sheets.
• Evaluate measurement systems Gauge R&R
– Every process has variation and measurement system, tools &
cmm are no exception.
– Typical your measurement process needs to be ACCURATE,
REPEATABLE & REPRODUCIBLE to less than 10% of the
tolerance you are trying to measure to & proven to be so.
• Select measures of performance
– QFD Quality Function Deployment is a method of defining what
the customer needs and what is critical to there business success
and prioritising performance measures to support the customers
need.

12. Analyze
Improvement methodology
• Investigate source of variation
(Special cause / Common causes)
– Stratification of data to get information
– Cause & effect
– CP & CPK
– Fault tree
– Contingence analysis
– FMEA (Failure Mode Effect Analysis)
– Design of experiments (DOE)
– Detailed process maps
Seek to:-
Prioritise
Understand
Clues
Causes
Monitor improvements
Look for signals

13. Lost
Shoe
Lost
Nail
Lost
Horse
Lost
Soldier
Lost
Battle
Why Battles are LostWhy Battles are Lost
Current Window of Consideration
Cause Failure
Mode
Effect
FMEA
•Identifies the ways in which a product or process can fail
•Estimates the risk of specific causes with regard to these failures
•Prioritizes the actions that should be taken to reduce the chance of failure
FMEA
(failure mode effect analysis)

14. factors which shift the average
factors which affect variation
factors which shift the average and affect
variation
factors which have no effect
A1 A2
D1=D2
B1
B2
C1
C2
DOE - (design of experiments)
will help us identify...

15. DOE - (design of experiments)
Measure the Process
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw
Materials,
components,
etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality
Characteristics:
Outputs
LSL USL
Establish the
performance
baseline
Process
Step/Input
Potential Failure Mode Potential Failure Effects
S
E
V
Potential Causes
O
C
C
Current Controls
D
E
T
R
P
N
Actions
Recommended
Load DMF/DMF
Load Accuracy MischargeofDMF Viscosity out of spec 7 SOP not Followed 5
Operator Certification/ Process
Audit
5 175
Fool proofthis process
usinginput from TQL
Team
Steam to
DICY/Scale
Accuracy
ScaleNot Zeroed MischargeDMF 3 Faulty Scale 2 None 9 54
Include Daily sign-off of
Scale funtionin Shift
set-up verification.
Load DMF/DMF
Load Accuracy MischargeofDMF Viscosity out of spec 7 EquipmentFailure 2
Maintenance Procedure (SOP
5821)/VisualCheck
3 42
Steam to
DICY/Scale
Accuracy
Scale> 0 Low DMF Charge 3 Waterin Jacket 2 Visual Check ofJacket(SOP 5681) 4 24
Steam to
DICY/Scale
Accuracy
Scale Inaccurate High DMFCharge 3 Tank Hanging Up 2 Visual Check (SOP 5681) 4 24

16. DOE - (design of experiments) Analyse the
Process
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw
Materials,
components,
etc.
Uncontrollable Inputs
Y1, Y2, etc.
Quality
Characteristics:
Outputs
LSL USL
Key Outputs: Variable How Measured When Measured
1
2
3
Noise Variables: Variable How Measured When Measured
1
2
3
4
5
Controllable Inputs Variable How Measured When Measured
1
2
3
4
5
Overall Sampling Plan:
Run Temperature Pressure
1 Hi Hi
2 Hi Hi
3 Lo Hi
4 Lo Hi
5 Hi Lo
6 Hi Lo
7 Lo Lo
8 Lo Lo
3 .52 .51.5
Capability Histogram
4321
3 .0
2 .5
2 .0
1.5
Xbar and R Chart
S u b g r
Means
M U =2 .3 7 6
U C L =2 .5 6 8
L C L =2 .18 3
0 .9
0 .6
0 .3
0 .0
Ranges
R =0 .5 16 2
U C L =0 .9 6 2 1
L C L =0 .0 7 0 2 7
4321
Last 4 Subgroups
3 .0
2 .5
2 .0
1.5
Subgroup N um ber
Values
41
2 .9 19 5 81.8 3 17 5
Cp: 2.76
CP U: 2.99
CP L: 2.53
Cpk : 2.53
Capability Plot
Proc ess Toleranc e
Spec ific ations
St D ev : 0.181306
III
III
3 .52 .51.5
Norm al Prob P lot
C ap ab ility us ing P o o le d S tand ard D e viatio n

17. DOE - (design of experiments) Improve the
Process
Uncontrollable Inputs
The Process
X1 X2 X3
Controllable Inputs
N1 N2 N3
Inputs:
Raw
Materials,
components,
etc.
Y1, Y2, etc.
Quality
Characteristics:
OutputsX
X
X
LSL USL
LSL USL
ScrewRPM
PrimWdth
Nip FPM
Three Factor Design

18. DOE - (design of experiments) Control the
Process
The Process
X1 X2 X3
Controllable Inputs
Inputs:
Raw
Materials,
components,
etc.
N1 N2 N3
Uncontrollable Inputs
Y1, Y2, etc.
Quality
Characteristics:
Outputs LSL USL
Check
Lists
Error
Proofing
Work
Instructions
5 C’s

19. Analyze
• Investigate source of variation (Special cause / Common causes)
– Special cause variation are the one off, occasional and obvious
cause of a process / quality problems.
– Common cause variation are the day in day out causes of process
problems, because the process is not stable enough, they are
hidden (these form 80% of process problems)
– Conventional non-conformance management systems seek to solve
special cause variation (e.g. concessions) - but these only represent
15 - 20% of the total variation.
– 6 Sigma addresses all variation.

20. Improve
Improvement methodology
• Prioritise improvements
– Impact Vs Effort
– Brainstorming
– Affinity diagrams
– Solution selection matrix
• Tactical implementation plans
– Deliver improvements (reduce variation
systematically)
Customer protection
Get control
Improve process

21. Improve
• Prioritise improvements
– Tool commonly in uses are, Impact Vs Effort,
Brainstorming, Affinity diagrams, Solution selection
matrix.
– These tools help define the best method to meet the
customer need (as defined in the QFD)
• Tactical implementation plans
– Deliver improvements to reduce variation
systematically i.e. make a change, note the
improvement and make the next improvement.
– Critical we need to establish that any change is a
change for the good.

22. Control
Improvement methodology
• Control the process
– Recover
• Control plans
• Escalation process
– Prevent
• Poke yoke (mistake/ error proof)
– Monitor
• Control charts
• Checksheets
• Documentation and Standardisation

23. Control
• Control the process
– Recover, Control plans, Escalation process.
– Prevent by Poke yoke (fool proof the process) to fundamentally
remove the rood causes of process variation.
– Monitor, Control charts, Checksheets, Documentation and
Standardisation, to ensure that stable process is maintained and
that the process does not degrade.
• The objective is to remove the root causes of process variation,
management are only left with a few critical input variables in the
process that need controlling and not all inputs as before.

24. Where does 6 Sigma fit with Lean
Lean
improvements
6 Sigma
improvements
• Lean and 6 Sigma both seek to
deliver business improvement
• They are different in the
methods used and tools
employed
– Lean typically address the
total manufacturing
environment
– 6 sigma typical address the
root cause of process
variation
• There is significant benefit
from using the most appropriate
tools and improvement
methodology to meet the
customer requirements