J0444
OPERATION MANAGEMENT
Six Sigma
Universitas Bina Nusantara
History
• Carl Frederick Gauss (1777-1885) introduced the Normal Curve
concept.
• Walter Shewhart (1920): Six Sigma as a measurement standard in
product variation
• Bill Smith, an engineer from Motorola terminologized the “Six
Sigma”
• In the late 1970's, Mikel Harry, a senior engineer at Motorola's
Government Electronics Group (GEG), began to experiment with
problem solving through statistical analysis. Using his
methodology, GEG began to show dramatic results
• Dr. Mikel Harry and Richard Schroeder, were responsible for
creating the unique combination of change management and datadriven methodologies that transformed six sigma from a simple
quality measurement
Konsep Six Sigma
s
 Metric
 Benchmark
•
•
The “Sigma Value” is a Metric. It
Indicates How Well a Business
Process is Performing.
•
“Six Sigma” is a Philosophy Aimed at
Increasing the Sigma Value of All
Business Processes.
 Philosophy
 Tool
 Symbol
 Goal
 Value
Used to Describe the Distribution of
Any Process.
•
 Vision
 Method
Letter in the Greek Alphabet.
What is Six Sigma
• Measure of Quality
• Process For Continuous
Improvement
• Enabler for Culture Change
Measure of Quality
Example #1: Manufacturing Steel Rolling
Mill
Sheet Thickness is a CTQ
(Critical to Quality Parameter)
Nominal Thickness = 1000 mm
Minimum Spec
= 950 mm
Maximum Spec
= 1050 mm
Scrap Production averages 100 meter / Coil
Measure of Quality
Lower
Specification
Limit
Scrap
Upper
Specification
Limit
Scrap
No Less Than
No More Than
950mm
1050mm
Steel Strip
Thickness
Quite some
Variation
-Ending up as
Scrap
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Standard Deviation
Let’s Look at some
Basic Statistics
25mm
Mean Thickness = 993 mm
Standard Deviation = 25 mm
Mean Thickness
993mm
On Average it’s OK - it’s a Variation issue
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Standard Deviation
25mm
How Capable is
our Process to
Produce within
Spec?
Sigma Rating = Spec Width / 2* SD
= 100 / 50
Spec Width (1050-950)
100mm
=
2
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Reducing
Variation is
Clearly the Key to
Improving
Process
Spec Width
Capability
100 mm
Std Dev
25 mm
2s
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Reducing
Variation is
Clearly the Key to
Improving
Process
Spec Width
Capability
100 mm
Std Dev
17 mm
3s
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Reducing
Variation is
Clearly the Key to
Improving
Process
Spec Width
Capability
100 mm
Std Dev
12 mm
4s
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Reducing
Variation is
Clearly the Key to
Improving
Process
Spec Width
Capability
100 mm
Std Dev
10 mm
5s
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
Reducing
Variation is
Clearly the Key to
Improving
Process
Spec Width
Capability
100 mm
Std Dev
8 mm
6s
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
6 Sigma Lingo
2s
Spec
Width
Spec
100
Standard
Deviation
25
Unit : Each Measurement
Sigma DPMO
Level
2
308,500
%
In
69.1
Defect : Measurement out of
Spec
Defect Opportunities per Unit :
1
Quality expressed as DPMO
( Defects per Million
Opportunities)
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
6 Sigma Lingo
3s
Spec
Width
Spec
100
100
Unit : Each Measurement
Standard Sigma
Deviation Level
DPMO
%
In
25
2
308,500
69.1
17
3
66,800
93.3
Defect : Measurement out of
Spec
Defect Opportunities per Unit :
1
Quality expressed as DPMO
( Defects per Million
Opportunities)
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
6 Sigma Lingo
4s
Spec
Width
Spec
100
Unit : Each Measurement
Standard Sigma
Deviation Level
DPMO
%
In
25
2
308,500
69.1
100
17
3
66,800
93.3
100
12
4
6,200
99.4
Defect : Measurement out of
Spec
Defect Opportunities per Unit :
1
Quality expressed as DPMO
( Defects per Million
Opportunities)
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
6 Sigma Lingo
5s
Spec
Width
Spec
100
Unit : Each Measurement
Standard Sigma
Deviation Level
DPMO
%
In
25
2
308,500
69.1
100
17
3
66,800
93.3
100
12
4
6,200
99.4
100
10
5
233
99.98
Defect : Measurement out of
Spec
Defect Opportunities per Unit :
1
Quality expressed as DPMO
( Defects per Million
Opportunities)
Measure of Quality
Lower
Specification
Limit
Upper
Specification
Limit
6 Sigma Lingo
6s
Spec
Width
Spec
100
Unit : Each Measurement
Standard Sigma
Deviation Level
DPMO
%
In
25
2
308,500
69.1
100
17
3
66,800
93.3
100
12
4
6,200
99.4
100
10
5
233
8
6
3
100
99.9997
99.98
Defect : Measurement out of
Spec
Defect Opportunities per Unit :
1
Quality expressed as DPMO
( Defects per Million
Opportunities)
Measure of Quality
Example #2: Product Delivery
PT X deliver their products to it’s customer
five times, their delivery time data are
PT Y deliver their products to it’s customer
five times, their delivery time data are
•21 days,
•14 days,
•15 days,
•12 days,
•12 days,
•12 days,
•10 days, and
•12 days, and
•2 days.
•10 days.
The AVERAGE (Mean) of Their Delivery
Time is:
21 + 15 + 12 + 10 + 2 = 60/5 = 12 DAYS
The AVERAGE (Mean) of Their Delivery
Time is:
14 + 12 + 12 + 12 + 10 = 60/5 = 12 DAYS
Measure of Quality
PT X The AVERAGE (Mean) of Their
Delivery Time is: 12
DAYS
Lower
Specification
Limit
Upper
Specification
Limit
But…
Standard Deviation = 7.0
PT Y The AVERAGE (Mean) of Their
Delivery Time is: 12
DAYS
And….
Standard Deviation = 1.4
Lower
Specification
Limit
Upper
Specification
Limit
Measure of Quality
Baseline Improved (?)
12
24
14
7
16
8
20
25
14
10
11
30
16
Mean 15.8
27
7
15
4
18
6
23
6
2
24
2
6
5
Example #2: Service Time
• Using mean-based thinking, we improve
average performance by 29%, and break
out the champagne…..
• BUT….our customer only feels the
VARIANCE,….and cancel the next orders!
What the Company Feels
11.2
11.2
SD
7.0
9.0
15.8
What Customer Feel
Measure of Quality
Improved (?)
11
11
10
10
12
11
11
11
11
12
12
12
10
Mean 11.07
SD
0.76
• Now it is improved….the Mean is 11,
and the STD is below 1….
• but UNFORTUNATELY, what the
customer wants is 9 days (or what
competitors can do is 9 days)….so it
is not variance issue anymore, but
now about the Process Centering
issue
Variation is the enemy!
• Variation reduction = Defect
reduction
• Quality measurement =
measurement of defect on the
process/products
• Six Sigma process = Defect
reduction until 3.14 out of 1 Million
products/process
23
Variation Reduction
A Process is
“A Distribution of Distributions”
Goal: Reduce Process Width-Variation is the Enemy
24
The Athletic View of
Performance
• Consider a goalkeeper who
plays 50 games a year and
faces 40 shots on goal each
game.
• A defect is when the
opposition scores.
• A 6s goalkeeper will be scored
against once in every 147 years
25
Is 6 Sigma Impossible?
• US airline baggage handling: 30-50,000 lost items per million, ~ 3 3.5s
• Average Companies: 30-50,000 defects per million ~ 3 - 3.5s
• World-Class Companies: <1000 defects per million 5 - 5.5s
US airline
fatality rate:
< ½ per million flights, > 6s
Process for
Continuous
Improvement
Nature Of The Problem
Off-Target
XX
XX
X
X
X
XX
Center
Process
On-Target
Variation
X X
X X
X X
X
XX X
X
X
XXX
X
X
X
XXX
X
Reduce
Spread
Process for Continuous
Improvement
Y = f {X1, X2, X3, …Xn}
Output
(Dependent
Variable)
Process
(Independent Variables)
Identifying Variation
Sources
X3
X1
Process
X4
X2
Xn-2
Xn-1
OUTPUT
Y
Xn
Y = f ( X1, X2, X3, X4, … , Xn-2, Xn-1, Xn)
Inside the Box Xs
Controllable
Outside the Box Xs
Un-Controllable
29
Six Sigma
approach is
focus on
process…
Fixing process so they
will produce perfection
on products and services
Define
Measure
Analyze
Six Sigma
Methodology
DMAIC
For improve existing process/products
Improve
Control
Define
Measure
Analyze
Design
Verify
Six Sigma
Methodology
DMADV
For new process/products
(sometime called DFSS,
Design For Six Sigma)
Define Phase
• Voice of Customer (VOC)?
• Problems?
• Unit, Defects, Opportunities?
33
Measure Phase
•
•
•
•
Collect data baseline
Identify frequency of defects?
Baseline process capability?
Target or benchmark process capability?
34
Analyze Phase
•
•
•
•
Why, when, where defects occurs?
Data analysis
Process analysis
Identify Vital X’s
35
Improve Phase
• How to reduce defects?
• Fix problems
• Collect improved data
36
Control Phase
• Calculate new process capability
• Verify statistically improvement made
• Implement process control
37
The 6 Sigma Success Factors
Business Process
Framework
Quantifiable
Measures &
Results
 Establishing these factors
provides the seeds of
success.
Six Sigma
Projects
Incentives &
Accountability
Committed and
Involved
Leadership
Full Time 6 Sigma
Team Leaders
 They need to be integrated
consistently to fit each
business.
 They are all necessary for the
best result
Strategy
Integration
 The most powerful success
factor is “committed
leadership.”
What Is Six Sigma
Projects?
• Project needs to be done by Every Employee (Green Belt)
• Project using Six Sigma methodology (DMAIC/DMADV)
• Project that making Improvement (DPMO reduction)
• Project that has a measurable unit and defect
• Project that has a measurable impact
• Project that start with Customer (internal/external) CTQ
Harvesting the Fruit of Six
Sigma
Start With Low Hanging Fruit
Sweet Fruit - 6s
Design for Six Sigma (DFSS)
Process Entitlement
Bulk of Fruit - 4 to 5s
Process Improvement
Six Sigma Tools
Low Hanging Fruit - 3 to 4s
Basic Quality Tools
Ground Fruit - up to 2s
Logic and Intuition