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Seminar dan Workshop System Six Sigma
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Transcript of Six sigma seminar
Seminar dan Workshop
System
Six Sigma
• The term “sigma” is used to designate the distribution or spread about the mean (average) of any process or procedure.
• For a process, the sigma capability (z-value) is a metric that indicates how well that process is performing. The higher the sigma capability, the better. Sigma capability measures the capability of the process to produce defect-free outputs. A defect is anything that results in customer dissatisfaction.
Two Meanings of Sigma
σ
• The term “Six Sigma” was coined by Bill Smith, an engineer with Motorola
• Late 1970s - Motorola started experimenting with problem solving through statistical analysis
• 1987 - Motorola officially launched it’s Six Sigma program
Origin of Six Sigma
Motorolathe company that invented Six Sigma
• Jack Welch launched Six Sigma at GE in Jan,1996
• 1998/99 - Green Belt exam certification became the criteria for management promotions
• 2002/03 - Green Belt certification became the criteria for promotion to management roles
The Growth of Six Sigma
GEthe company that perfected Six Sigma
Six Sigma Company Globaly
KOREAN TELECOM
Increasing trend of Six Sigma Adoption due to it’sProven Impact!
Globally Well Known Six Sigma Companies
Globally Well Known Six Sigma Companies
Perkin Elmer
General Electric (GE)“This is the most important initiative this Company has ever undertaken. (It) will fundamentally change our Company forever.”
John F. Welch, Jr..Letter to GE Officers, May 18, 1996• Start the initiative in 1995 as a Continuation of
GE initiatives• Build the organization of Quality (BB/MBB,
Quality Leaders, Champion• Become the new DNA of the company…they way
they work… the way they lead• GE’s Lighting unit repaired problems in its
billing to one of its top customers—Wal-Mart—cutting invoice defects and disputes by 98 percent, speeding payment, and creating better productivity for both companies.
• GE Capital’s service businesses streamlined the contract review process, leading to faster completion of deals—in other words, more responsive service to customers and annual savings of $1 million.
High
Low
Intensity of
Change
Time
Work-out TM/Town Meetingempowerment, bureaucracy busting, action
Action Work-OutsTM
Customized Work-OutsTM
Best Practice SharingProductivity/Best Practice
looking outside GE
Bullet Train ApproachProcess Improvementcontinuous improvement, re-engineering
Change Acceleration Processincrease success and accelerate change
Key Strategic Initiatives :QMI*NPI*, OTR*, SP*, Productivity, Globalization
Making Customers Winners :GE Tool Kit
* Quick Market IntelligenceNew Product IntroductionOrder to RemittanceSupplier Management
Six Sigma Quality
Digitization
Six Sigma Success Story
Six Sigma Started in 1999
2001 Six Sigma Update
1998 1999 2000 2001 2002 2003 2004
0
0.5
1
1.5
2
Revenue (US$ Bio)
1998
1999
2000
2001
2002
2003
2004
0
20406080
100120140160180200
Cash Flow (US$ Mio)
Six Sigma Success StoryPerkinElmer dipimpin oleh Gregory L. Summe, (48th) sebagai CEO mulai 1999. Greg pernah bekerja di Alliedsignal (sekarang
Honeywell) sebagai Presiden. juga pernahbekerja di General Electric dari sebagai DirekturCorporation.Pada th ‘01, Six Sigma training dilakukan olehinternal Trainer. Sampai tahun 2003 telahditraining GB sebanyak 180 orang (di Asia).
$600$500$450$380$200
$2500
$1200
$700
$170
Cost Benefit
1996
Cost Benefit
1997
Cost Benefit
1998
Cost Benefit
1999
Cost Benefit
2000
6 Sigma Cost6 Sigma BenefitDelighting Customers
GE Results from 6 Sigma
3 Billion$ in 2000 … Customers & Shareholders Love It!
$2500
$3.0B
$0.5B
$2.5B
Six Sigma Success Story
Gerakan kualitas yang menggunakan terobosanpaling baru dalam teknik dan metodologi, merupakaningkarnasi dari “best of the best” managemenkualitas yang tujuan utamanya adalah membantupencapaian Visi dan Misi bisnis yaitu menciptakanefisiensi, efektifitas, mengurangi variasi, mencegahcacat dan mengurangi pemborosan dalam bisnisproses demi kepuasan pelanggan, pemilikperusahaan, karyawan dan pemasok.
Six Sigma adalah…
Why Six Sigma ?
Total biayauntukProdukatauJasa
Profit
Total hargayang dibebankankepadaCustomer bagi Product atau Jasa
Actual Profit & Cost Breakdown
Results from Deploying Six Sigma
World Class
Process Capability
Now Driving World Class
Quality
Waste(COPQ)
Profit
Theoretical Costs:
Cost of doing things correctly the first time
Waste(COPQ)
Profit
Theoretical Costs:
Cost of doing things correctly the first time
COPQ = Cost of Poor Quality
Six Sigma - Four Dimensions
ToolsOrganization
Methodology
Process variation
LSL USL
Upper/Lower specification
limits
Regression•••••••• •••• •••••
•••••• •
• ••• •• ••••••••• •
•
•••••
Driven by customer
needs
Enabled by qualityteam.
Led by Senior Mgmt
Define Measure Analyze Improve ControlVendorVendorProcess BProcess BProcess AProcess ACustomerCustomer VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer
VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer VendorVendorProcess BProcess BProcess AProcess ACustomerCustomer
Process Map Analysis
05
101520253035
L K A F B C G R D0%
20%
40%
60%
80%
100%
Frequency Cumulative Frequency
Pareto Chart
Vision&
Metric
Develop products and services BETTER, FASTER, and at LOWER COST
Peranan Six Sigma…
A Vision,A Philosophy
A Metric,A Benchmark
Develop products and services BETTER, FASTER, and at LOWER COST -aggressively attack waste (cost of poor quality: COPQ)
A Defect Rate Measure Equal to 3.4 defects per million
A Method,A Tool for Improvement
Tool
A quality improvement and business strategy which focuses on reducing variation in all business processes
Problem Identification
Problem Selection/Finding
Project Identification
Project Selection
Set-up theTeam
Train The Team Project Kick-off
Project ExecutionProject Coaching
Project ReviewBy Champion (Owner)
Project ReviewBy Board of Director
Project Closing
Reward and Recognition
Start Here
•Formal event•At the end of Trng
•Working meeting•Coaching by BB/MBB(Weekly)
• Review Meetingw/ Champion (weekly
• Review Meetingw/ BOD (monthly)
• Formal event
• Company event•Interview•Data analysis
•Six Sigma problemselection criteria
•Confirmation
•Transform problem toproject
•Confirmation
•Six Sigma projectselection criteria
•Confirmation (Time,cost,effort)
•Project Team selectioncriteria
•Six Sigma Green/Black Belt Trng
SIX SIGMA MECHANISM
The Quality Team
Master Black Belt
Black Belt Black Belt
Green Belt
Green Belt
Green Belt
- Thought Leadership- Expert on Six Sigma- Mentor Green and Black Belts
- Backbone of Six Sigma Org- Full time resource- Deployed to complex or “high
risk” projects
- Part time or full time resource- Deployed to less complex projects in areas of functional expertise
Six Sigma Organization
Champion - Sponsor of a project
Management Roles in Six Sigma
• Identifying key business areas where breakthrough is needed
• Identifying area with the highest saving
• Identify the right six sigma candidates in accordance to selection criteria
• Provide support of resources to train and equip people to attain stretch goals
• Set measurement matrix and track progress
• Recognition and reward success
• Create opportunity and channel to propagate success stories to generate culture change
17
Six Sigma Leadership Team
• Trained in Six Sigma• Develop a Six Sigma Deployment Plan• Work with management to identify right Six Sigma candidates• Develop a Focused • Schedule training• Serve as mentors for candidates• Certify Six Sigma Candidates• Identify Mentors• Monitor project selection and progress• Work with management sponsors on reward system and
propagating success• Develop a Six Sigma Network to enhance communication• Review and Improve Six Sigma Process
18
Over View of Leader’s Roles
19
Champions Master BB Black Belts Green Belts
QualificationsSeniors executives and
Managers Familiarity with basic and advanced statistical tools
Technical Degree & Chief Engineer or Head of
Customer Service Master of Basic and Advance
statistical tools
Technical Background . Black Belt might be
Engineer with four years experience or more. Full time in Project
Management . Mastery of Basic Statistic tools
Technical and Support Background. Their current
positions are associated with the problem need to be solved. Familiarity with basic statistical
tools
Profile
Strong proponent of Six Sigma who asks the right
questions . Repeated Leader and mentor
of business issues. Management position
Excellent in the knowledge and
application of statistical tools.
Chief Engineer or Head of Customer Service
Master of Basic and Advance statistical tools
Respectable by co-worker and management.
Master of Basic and Advance tools able to turn
into information
Respected by co- worker peers.
Proficient in basic and advance tools , able to turn data into
information
Training4 days Mentor Training
Six Sigma Development and Deployment
Two week Six Sigma Master Training
Certified Black Belt
Four 1-week sessions with three with project to apply
project review in every session
Two 1 Week sessions with one month in between to apply
Project review in 2nd session
Numbers One Green Belt per 20 Employees
One Black Belt per 100 employees. 100 000
employees would require 1,000 Black Belts
One master Black per 30 black belts.
Master Blacks Belts can represent division
One champion per business group or manufacturing site
DDefine
MMeasure
AAnalyze
IImprove
CControl
The Methodology of Six Sigma
• A logical and structured approach to problem solving and processimprovement
• An iterative process (continuous improvement)
• A quality tool with focus on change management
EEffectiveness
= QQuality
Improvement
x AAcceptance
The Approach
Practical Problem
StatisticalProblem
Statistical Solution
Practical Solution
VoC - Who wants the project and why ?
The scope of project / improvement
Key team members / resources for the project
Critical milestones and stakeholder review
Budget allocation
Define
DDefine
MMeasure
AAnalyze
IImprove
CControl
Identify and state the practical problem
Ensure measurement system reliability
Prepare data collection plan
Collect data
- Is tool used to measure the output variable flawed ?- Do all operators interpret the tool reading in the same way ?
- 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 ?
Measure
DDefine
MMeasure
AAnalyze
IImprove
CControl
Validate the practical problem by collecting data
Understand statistical problem
Baseline current process capability
Define statistical improvement goal
Identify drivers of variation (significant factors)
Analyze
DDefine
MMeasure
AAnalyze
IImprove
CControl
Convert the practical problem to a statistical one, define statistical goal and identify potential statistical solution
Root Cause Analysis (fish bone)
• A brainstorming tool that helps define and display major causes, sub causes and root causes that influence a process
• Visualize the potential relationship between causes which may be creating problems or defects
ProblemBackbone
Primary CauseSecondary Cause
Root Cause
Analyze – Identify Drivers of Variation
Control – Impact Matrix
• A visual tool that helps in separating the vital few from the trivial many
Trivial ManyLow Control – Low Impact
Cost IneffectiveHigh Control – Low Impact
Cost IneffectiveLow Control – High Impact
Vital FewHigh Control – High Impact
Control
Impa
ctAnalyze – Identify Drivers of Variation
Select A Statistical TestHypothesis tests to find relationships between project Y and
potential X’s
Chi-Square Test
1 Sample t Test2 Sample t-Test(Compare Means of two
samples)ANOVA (Compare means of multiple samples)Homogeneity of Variance (Compare variances
XDiscrete
Logistic Regression
• Scatterplot • Simple Linear • Regression
XContinuous
YDiscrete
YContinuous
Map improved process
Pilot solution
Identify operating tolerance on significant factors
Improve
DDefine
MMeasure
AAnalyze
IImprove
CControl
Confirm and test the statistical solution
Ensure measurement system reliability for significant factors
Improved process capability
Sustenance Plan
- Is tool used to measure the input / process variables flawed ?- Do all operators interpret the tool reading in the same way ?
- Statistical Process Control- Mistake Proofing- Control Plan
Control
DDefine
MMeasure
AAnalyze
IImprove
CControl
Convert the statistical solution to a practical solution
Control Plan
• Have the new operating procedures and standards been documented ?
• What Statistical Process Control (SPC) tools will be used to monitor the process performance ?
• Who will review the performance of the output variable and significant factors on closure of the project and how frequently ?
• What is the corrective action or reaction plan if any of the factors were to be out of control ?
Control – Sustenance Plan
Process Capability & Control
A method for centering or targeting the process output
independent of the size of the target (width of specification
limits)
Process Control
A measure of the natural spread of the process compared to
the size of the target (width of specification limits)
Determines whether a process, given its natural variation, is
capable of meeting established customer requirements or
specifications
Process Capability
Process Capability & Control
Yes NoYe
sN
oControl
Cap
able
Histogram of Car Speed in Highway (Km/h)
0
20
40
60
80
100
36.0
to <=
38.0
38.0
to <=
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to <= 4
4.0
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to <= 4
6.0
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to <= 4
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to <=
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to <=
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52.0
to <=
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to <=
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56.0
to <=
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to <=
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60.0
to <=
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62.0
to <=
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64.0
to <=
66.0
66.0
to <=
68.0
68.0
to <= 7
0.0
70.0
to <= 7
2.0
72.0
to <= 7
4.0
74.0
to <=
76.0
76.0
to <=
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78.0
to <=
80.0
80.0
to <=
82.0
82.0
to <=
84.0
84.0
to <=
86.0
86.0
to <=
88.0
88.0
to <=
90.0
90.0
to <=
92.0
92.0
to <=
94.0
94.0
to <= 9
6.0
96.0
to <= 9
8.010
0.0 to
<= 102
.0
Class
# O
bser
vatio
nsHistogram dan Normal Distribution
s=10 Km/h
Mean=70 km/h
68%
95%
99%
Histogram of Car Speed in Highway (Km/h)
0
20
40
60
80
100
36.0
to <=
38.0
38.0
to <=
40.0
42.0
to <= 4
4.0
44.0
to <= 4
6.0
46.0
to <= 4
8.0
48.0
to <=
50.0
50.0
to <=
52.0
52.0
to <=
54.0
54.0
to <=
56.0
56.0
to <=
58.0
58.0
to <=
60.0
60.0
to <=
62.0
62.0
to <=
64.0
64.0
to <=
66.0
66.0
to <=
68.0
68.0
to <= 7
0.0
70.0
to <= 7
2.0
72.0
to <= 7
4.0
74.0
to <=
76.0
76.0
to <=
78.0
78.0
to <=
80.0
80.0
to <=
82.0
82.0
to <=
84.0
84.0
to <=
86.0
86.0
to <=
88.0
88.0
to <=
90.0
90.0
to <=
92.0
92.0
to <=
94.0
94.0
to <= 9
6.0
96.0
to <= 9
8.010
0.0 to
<= 102
.0
Class
# O
bser
vatio
nsSigma Level
s=10 Km/h
Mean=70 km/h USL
105
LSL
30
Sigma Level Lower=(Mean-LSL)/s=
(70-30/10=40/10=
4 Sigma
Sigma Level Upper=(USL-Mean)/s=
(105-70)/10=35/10=
3.5 Sigma
Process Capability: Precise & Accurate
AccurateYes No
Prec
ise
Yes
No
Target
Mean
Target
Mean
Target
Mean
Target
Mean
3σxxx
xxxx
2σxxx
xxxx
Process Capability & Control
☺6σx xxxxxx
DPM
308,538
66,807
3.4
Yield
69%
93%
99.9996549%
σcapability
Control Plan
• Have the new operating procedures and standards been documented ?
• What Statistical Process Control (SPC) tools will be used to monitor the process performance ?
• Who will review the performance of the output variable and significant factors on closure of the project and how frequently ?
• What is the corrective action or reaction plan if any of the factors were to be out of control ?
Control – Sustainance Plan
Process Capability & Control
A method for centering or targeting the process output
independent of the size of the target (width of specification
limits)
Process Control
A measure of the natural spread of the process compared to
the size of the target (width of specification limits)
Determines whether a process, given its natural variation, is
capable of meeting established customer requirements or
specifications
Process Capability
Process Capability & Control
Yes NoYe
sN
oControl
Cap
able
Histogram of Car Speed in Highway (Km/h)
0
20
40
60
80
100
36.0
to <=
38.0
38.0
to <=
40.0
42.0
to <= 4
4.0
44.0
to <= 4
6.0
46.0
to <= 4
8.0
48.0
to <=
50.0
50.0
to <=
52.0
52.0
to <=
54.0
54.0
to <=
56.0
56.0
to <=
58.0
58.0
to <=
60.0
60.0
to <=
62.0
62.0
to <=
64.0
64.0
to <=
66.0
66.0
to <=
68.0
68.0
to <= 7
0.0
70.0
to <= 7
2.0
72.0
to <= 7
4.0
74.0
to <=
76.0
76.0
to <=
78.0
78.0
to <=
80.0
80.0
to <=
82.0
82.0
to <=
84.0
84.0
to <=
86.0
86.0
to <=
88.0
88.0
to <=
90.0
90.0
to <=
92.0
92.0
to <=
94.0
94.0
to <= 9
6.0
96.0
to <= 9
8.010
0.0 to
<= 102
.0
Class
# O
bser
vatio
nsHistogram dan Normal Distribution
s=10 Km/h
Mean=70 km/h
68%
95%
99%
Histogram of Car Speed in Highway (Km/h)
0
20
40
60
80
100
36.0
to <=
38.0
38.0
to <=
40.0
42.0
to <= 4
4.0
44.0
to <= 4
6.0
46.0
to <= 4
8.0
48.0
to <=
50.0
50.0
to <=
52.0
52.0
to <=
54.0
54.0
to <=
56.0
56.0
to <=
58.0
58.0
to <=
60.0
60.0
to <=
62.0
62.0
to <=
64.0
64.0
to <=
66.0
66.0
to <=
68.0
68.0
to <= 7
0.0
70.0
to <= 7
2.0
72.0
to <= 7
4.0
74.0
to <=
76.0
76.0
to <=
78.0
78.0
to <=
80.0
80.0
to <=
82.0
82.0
to <=
84.0
84.0
to <=
86.0
86.0
to <=
88.0
88.0
to <=
90.0
90.0
to <=
92.0
92.0
to <=
94.0
94.0
to <= 9
6.0
96.0
to <= 9
8.010
0.0 to
<= 102
.0
Class
# O
bser
vatio
nsSigma Level
s=10 Km/h
Mean=70 km/h USL
105
LSL
30
Sigma Level Lower=(Mean-LSL)/s=
(70-30/10=40/10=
4 Sigma
Sigma Level Upper=(USL-Mean)/s=
(105-70)/10=35/10=
3.5 Sigma
Process Capability: Precise & Accurate
AccurateYes No
Prec
ise
Yes
No
Target
Mean
Target
Mean
Target
Mean
Target
Mean
3σxxx
xxxx
2σxxx
xxxx
Process Capability & Control
☺6σx xxxxxx
DPM
308,538
66,807
3.4
Yield
69%
93%
99.9996549%
σcapability
Supplier/Input/Process/Output/Customer Diagram (SIPOC)
A visual representation of a process or activity which lists
supplier input variables, output characteristics and customer
What is it?
Clearly states a process and recognizes the relationships
between input variables and output responses
What does it do?
To better understand a process and how its inputs
relate to its outputs
Why do I use it?
Six Sigma Tools
SIPOC Diagram
Hi LevelProcess Map
S I P O CSuppliers Inputs Process Outputs Customers
Process Map
FlowThinking
Input Measures
Process Measures
Output Measures
SIPOC= Process Flow Direction COPIS= Thinking Direction
Starting Point
End Point
PROCESS
(ACTIVITY)
A blending of inputs to achieve
the desired outputs
Perform a service
Produce a product
Complete a task
SIPOC Diagram
People
Material
Policies
Equipment
Procedures
Methods
Environment
(Sources of Variability) (Measures of Performance) (Customer Wants)
I wants:
1………2………3………………..………..………..
S I P O CSuppliers Inputs Process Outputs Customers
I supply you:
1………2………3………………..………..………..
Process Mapping (PF)
A tool which helps analyze a process by breaking it down into
component steps
What is it?
Helps to identify the expected and unexpected areas of
complexity, problem areas, redundancy, unnecessary loops,
and where simplification and standardization may be possible
What does it do?
To identify the actual flow or sequence of events in a
process that a product or service follows
Why do I use it?
Process Mapping
This Symbol… Represents… Some Examples are…
Start/Stop Receive purchase requisitionReceipt of purchased part
Decision Point Approve/DisapproveAccept/Reject
Yes/NoPass/Fail
Activity Drop Off Travel VoucherOpen Access Panel
Connector (to another page or part of the diagram)
A
B
Process Mapping (Hospital Appointment)
Is an open line
availablePatient told to hold
for 1st available operator
Patient describes type of care
required
No
Yes
Acute Minor Illness Clinic Optometry
Family Practice
transfers patient to appropriate
office
Patient calls hospital
main number
Appointment made Appointment
madeAppointment
made
Process Mapping
Core
COPIS/SIPOC
Detailed Subprocess
Map
Acquire New Business
Obtain Request toBuy Service
ConductUnderwriting
PrepareContract
InitializeCustomer Service
Establish Terms
PrepareDocs
NegotiateContract
CloseDeal
Underwriters
S C
Tasks Procedures
Customer/Customer Service
Process Level Process MappingA Graphical Representation of Steps, Events, Operations, and Relationships of Resources Within a Process
Cause & Effect Diagram (CE)
A pictorial diagram, commonly in the shape of a fishbone,
showing all possible variables that could affect a given process
output
What is it?
Creates a snapshot of the collective knowledge and consensus
of a team around a problem and focuses the team around
causes, not symptoms
What does it do?
To identify and explore in detail all possible causes related to a problem to discover its root cause(s)
Why do I use it?
Cause & Effect Diagram (Fishbone Diagram)
Poor GasMileage
Method
(C) Carburetor
(C) Tire Pressure
(N) Weight
(C) Front or Rear Drive
(N) Air Conditioner
Machine
Transmission (C)
Tire Type (C)
Radio (C)
(C) Tire RotationTune-Ups (C)
(C) Engine Warm-Up Time
(C) Ride Brakes
Measurement
(C) Fast Start
(C) Gage for TirePressure
(C) Estimate of FullTank
(C) SpeedometerType
Manpower Materials Mother Nature
(N) Highway or City
(N) Terrain Weather Conditions (N)
(X) Gas Type
(X) Oil Type
(C) Fuel Additive
(C) Driver Training
(N) # of Passengers
(N) Driver
(C) Maint. Schedule
C = Constant - SOPsN = NoiseX = Experimental
Standard Operating Procedure (SOP)
A set of established actions or methods that are followed in
order to control variability in a process
What is it?
Defines the steps in a process
What does it do?
To ensure standardization of best practice and to reduce variation
Why do I use it?
Histogram
A bar chart that depicts frequencies of numerical data
What is it?
Identifies the distribution, central tendency, and variability of
data
What does it do?
To summarize graphically how data is distributed
Why do I use it?
F o r s ig n a l te s te r:M e a s u re m e n t S y s te m C a p a b i l i tie sNu m b e r o f O p e ra to rs 3Nu m b e r o f T ria ls 3Nu m b e r o f P a rts 1 0S ig m a M e a s u re m e n t 0 .0 4 7S ig m a T o ta l 0 .2 3 6G R &R 0 .1 9 9
Mengevaluasi variance dalam system pengukuran.
Untuk berhasil dalam perbaikan, pertamaanda harus mempunyai sistem pengukuranyang tepat.
Five Components Of An MSA:
1. Accuracy–the differences between observed average measurement and a standard
2. Repeatability–variation when one person repeatedly measures the same unit with the same measuring equipment
3. Reproducibility–variation when two or more people measure the same unit with the same measuring equipment
4. Stability–variation obtained when the same person measures the same unit with the same equipment over an extended period of time
5. Linearity–the consistency of the accuracy across the entire range of the measurement system
Measurement System Analysis (MSA)
Run Chart
A graphical tool that charts a process over time recording either
individual readings, averages, ranges, or standard deviations
What is it?
Monitors a system or process to detect meaningful changes
What does it do?
To study observed data for trends or patternsover a specified period of time
Why do I use it?
Run Chart
Historical Stock Prices
$27
$65
$51$48
$9
$5
$-
$10
$20
$30
$40
$50
$60
$70F
eb-9
9
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-99
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-99
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PKI Beckman Waters
Control Chart
A special kind of run chart that includes statistically determined
upper and lower control limits as well as a centerline
What is it?
Focuses attention on detecting significant trends, cycles and
outlying points
What does it do?
To monitor, control, and improve process performance over time by studying variation
Why do I use it?
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Centerline
Day
s o
f In
ven
tory Upper Control Limit
Lower Control Limit
Control Chart
Out of Control point
Scatter Diagram
A chart in which one variable is plotted against another to
determine if there is a correlation
What is it?
Visually identifies the relationship between two variables
What does it do?
To study and identify the possible relationship between the changes observed in two different sets of variables
Why do I use it?
Scatter Diagram
Scatter Chart
y = 0.8484x - 0.1299R 2 = 0.9346
00.10.20.30.40.50.60.70.80.9
1
0.76 0.86 0.96 1.06 1.16
Vp
Vof
fRegression Modelling
•Mengembangkan model yang menggambar bagaimana input padaproses mempengaruhi outputnya.
•Dapat meramalkan respon output yang akan muncul hanya dengan menggunakandata yang telah dikumpulkan.
•Menilai kekuatan model.
•Identifikasi data liar.
Pareto Chart
A bar chart for non-numerical categories that displays attribute
data from highest to lowest frequency (based on “Pareto
Principle” which states that 80% of the effects are due to 20% of
the causes)
What is it?
Identifies the causes that will have the greatest impact on
solving the problem
What does it do?
To focus our efforts on the problems that offer the
greatest potential for improvement
Why do I use it?
Pareto Chart
05
101520253035
L K A F B C G R D0%
20%
40%
60%
80%
100%
Frequency Cumulative Frequency
Failure Mode & Effect Analysis (FMEA)
A procedure used to identify and assess risks associated with
potential product or process failure modes
What is it?
Identifies and evaluates potential failure modes
What does it do?
To prioritize and “fool proof” the critical failure modes
Why do I use it?
Building an FMEA
Product orProcess
Failure Mode Failure Effects SEV
Causes OCC
CurrentControls
DET
RiskProfile
NumberGo to store Car won’t start Have to walk 2 Out of gas 3 Check gas
gauge1 6
2 Battery dead 2 None 5 20
Get lost No food 5 Forgetful 1 None 5 25
Buy bread Out of favoritebrand
Buy alternate 1 Sold out 2 None 5 10
Out of all bread Eat salad 4 Too late 2 Planning 2 16
Buy meat Out of favoritemeat
Buy alternate 1 Sold out 3 None 5 15
Out of all meat Eat bread 4 Poor planning 1 Storepersonnel
2 8
Makesandwich
Cut self withknife
Delay mealwhile visithospital
3 Clumsy 4 Be careful 3 36
Forget recipe Give up 5 Forgetful 1 None 5 25
RPN = SEV x OCC x DETRPN: Risk Priority Number; SEV:Severity; OCC: Occurance; DET: Detectibility
# Replications 5 repsResponse E3 varianceBonding Method 1st bond on PCB
# Replications 5 repsResponse E3 varianceBonding Method 1st bond on PCB
Factor Low Medium High1st Bond Force 35 47.5 601st Bond Time 50 62.5 75Bond Power 2 2.5 3
Factor Low Medium High1st Bond Force 35 47.5 601st Bond Time 50 62.5 75Bond Power 2 2.5 3
DESIGN
S-hat ModelE3
Factor Name Coeff P(2 Tail) Tol ActiveConst 0.00932 0.4343A Bond Force -0.01385 0.0942 1 XB Bond Power -0.01261 0.1192 1 XC Bond Time 0.00934 0.2229 1AB -0.01650 0.1429 1AC 0.01398 0.2011 1BC 0.01240 0.2484 1AA 0.03704 0.0133 0.9890 XBB 0.03547 0.0157 0.9890 XCC -0.01526 0.1832 0.9890
R2 0.9018Adj R2 0.7251
S-hat ModelE3
Factor Name Coeff P(2 Tail) Tol ActiveConst 0.00932 0.4343A Bond Force -0.01385 0.0942 1 XB Bond Power -0.01261 0.1192 1 XC Bond Time 0.00934 0.2229 1AB -0.01650 0.1429 1AC 0.01398 0.2011 1BC 0.01240 0.2484 1AA 0.03704 0.0133 0.9890 XBB 0.03547 0.0157 0.9890 XCC -0.01526 0.1832 0.9890
R2 0.9018Adj R2 0.7251
Name ExperBond Force 56.34Bond Power 2.71Bond Time 56.87
Name ExperBond Force 56.34Bond Power 2.71Bond Time 56.87
PART: 16-2 QTY= 30 PCSWire Pull Test 6.08 grfVisual Defect 0%E3 defect 0%
CONFIRMATION RUN
PART: 16-2 QTY= 30 PCSWire Pull Test 6.08 grfVisual Defect 0%E3 defect 0%
CONFIRMATION RUN
RESULT
RELIABILITY TEST RESULTPART 16-2
Quantity: 18 pcsDefect New method Old method
E3 0% 0%Visual 0% 0%
Old and new Method Comparison
LOT Old Method New Method1 0.075 0.0252 0.075 0.053 0.05 0.0254 0.125 0.025
Average 0.08 0.03Range 0.075 0.025
Wire pull strength 6.18 grf 6.08 grf
Yield E3 Defect
F Test Analysis (Std Dev)t Test Analysis (Mean) 0.286
F Test & t-Test of E3 defect P-value0.036
VERIFICATION > Cara yang paling sistematis dan efisien dalam pengumpulan data
> Digunakan untuk mengidentifikasifactor-factor penting yang Berpengaruh pada proses
> Mengidentifikasi interaksi pentingantara variable-variable proses
> Dapat digunakan untuk mengoptimalkan proses
> Digunakan untuk membangunModel yang berhubungan/Interaksidengan bagaimana input berpengaruh pada output
Design Of Experiment (DOE)
ANALYSIS OF SUPPORTING FACTORS IN SIX SIGMA IMPLEMENTATION
Case Study: PT. General Electric Lighting Indonesia
(1) Komitmen pimpinan pada setiap tahap proses implementasi,
(2) Pembelajaran pada tahap adaptasi dan tahap implementasi,
(3) Proses pelatihan pada tahap pengenalan,
(4) Dukungan agen Six Sigma yang kuat
(5) Dukungan fasilitas komunikasi pada tahap adaptasi, dan pada tahap
implementasi faktor penting yang mendukung adalah
(6) Struktur organisasi Six Sigma yang kuat,
(7) Kebijakan perusahaan,
(8) Keterlibatan anggota perusahaan dalam Six Sigma,
(9) Konsistensi DMAIC serta
(10) Kerja sama dalam pengelolaan proses,
(11) Pengelolaan sumber daya yang baik dan
(12) Qualitas awareness.
Wrap Up - What is Six Sigma?
Having a BETTER, FASTER, and at LOWER COST products and services
Defect Rate = 3.4 defects per million
A method focusing on reducing variation in all processes
Happy Customers ☺Happy Business Owner ☺
Happy Employees ☺Happy Supplier ☺
HAPPY YOU ☺
End
