Quantitative methods in process improvement – Six Sigma (6σ) Diganta Borah Sr. Engineer (P&A)
Quantitative methods in
process improvement –
Six Sigma (6σ)
Diganta Borah
Sr. Engineer (P&A)
Topics
♦Understanding Six Sigma
♦History of Six Sigma
♦Six Sigma Methodologies & Tools
♦Roles & Responsibilities
Six Sigma is. . .
♦ A performance goal, representing 3.4 defects for every million opportunities to make one.
♦ A series of tools and methods used to improve or design products, processes, and/or services.
♦ A statistical measure indicating the number of standard deviations within customer expectations.
♦ A disciplined, fact-based approach to managing a business and its processes.
μ
σ
What’s in a name?
♦ Sigma is the Greek letter representing the standard
deviation of a population of data.
♦ Sigma is a measure
of variation
(the data spread)
What does variation mean?
♦ Variation means that a
process does not produce
the same result (the “Y”)
every time.
♦ Some variation will exist in
all processes.
♦ Variation directly affects customer experiences.
Customers do Customers do notnot feel averages!feel averages!
-10
-5
0
5
10
15
20
Measuring Process PerformanceThe pizza delivery example. . .
♦ Customers want their pizza delivered fast!
♦ Guarantee = “30 minutes or less”
♦ What if we measured performance and found an average delivery time of 23.5 minutes?
– On-time performance is great, right?
– Our customers must be happy with us, right?
How often are we delivering on
time?Answer: Look at
the variation!
♦ Managing by the average doesn’t tell the whole story. The average and the variation together show what’s happening.
s
x
30 min. or less
0 10 20 30 40 50
Reduce Variation to Improve
PerformanceHow many standard
deviations can you
“fit” within
customer
expectations?
♦ Sigma level measures how often we meet (or fail to meet) the requirement(s) of our customer(s).
s
x
30 min. or less
0 10 20 30 40 50
Managing Up the Sigma Scale
3.40.00034%99.9997%6
2330.023%99.977%5
6,2100.62%99.38%4
66,8076.7%93.3%3
308,53830.9%69.1%2
691,46269.1%30.9%1
DPMO% Bad% GoodSigma
Examples of the Sigma Scale
In a world at 3 sigma. . .
♦ There are 964 U.S. flight cancellations per day.
♦ The police make 7 false arrests every 4 minutes.
♦ In one hour, 47,283 international long distance calls are accidentally disconnected.
In a world at 6 sigma. . .
♦ 1 U.S. flight is cancelled every 3 weeks.
♦ There are fewer than 4 false arrests per month.
♦ It would take more than 2 years to see the same number of dropped international calls.
Topics
♦Understanding Six Sigma
♦History of Six Sigma
♦Six Sigma Methodologies & Tools
♦Roles & Responsibilities
The Six Sigma Evolutionary Timeline
1736: French mathematician Abraham de Moivre publishes an article introducing the normal curve.
1896: Italian sociologist Vilfredo Alfredo Pareto introduces the 80/20 rule and the Pareto distribution in Cours d’Economie Politique.
1924: Walter A. Shewhart introduces the control chart and the distinction of special vs. common cause variation as contributors to process problems.
1941: Alex Osborn, head of BBDO Advertising, fathers a widely-adopted set of rules for “brainstorming”.
1949: U. S. DOD issues Military Procedure MIL-P-1629, Procedures for Performing a Failure Mode Effects and Criticality Analysis.
1960: Kaoru Ishikawa introduces his now famous cause-and-effect diagram.
1818: Gauss uses the normal curve to explore the mathematics of error analysis for measurement, probability analysis, and hypothesis testing.
1970s: Dr. Noriaki Kano introduces his two-dimensional quality model and the three types of quality.
1986: Bill Smith, a senior engineer and scientist introduces the concept of Six Sigma at Motorola
1994: Larry Bossidy launches Six Sigma at Allied Signal.
1995: Jack Welch launches Six Sigma at GE.
Six Sigma Companies
Six Sigma and Financial Services
Topics
♦ Understanding Six Sigma
♦ History of Six Sigma
♦ Six Sigma Methodologies & Tools
♦ Roles & Responsibilities
♦ How YOU can use Six Sigma
DMAIC – The Improvement
Methodology
Define Measure Analyze Improve Control
Objective:
CONTROL the
process
to sustain the gains.
Objective:
IMPROVE the
process to
eliminate root
causes
Objective:
ANALYZE the
root causes of
problems
Objective:
MEASURE current
performance
Objective:
DEFINE the
opportunity
Key Control
Tools:
• Control Charts
• Contingency
and/or Action
Plan(s)
Key Improve
Tools:
• Solution Selection
Matrix
• To-Be Process
Map(s)
Key Analyze
Tools:
• Histograms,
Boxplots, Multi-
Vari Charts, etc.
• Hypothesis Tests
• Regression
Analysis
Key Measure
Tools:
• Critical to Quality
Requirements
(CTQs)
• Sample Plan
• Capability
Analysis
• Failure Modes
and Effect
Analysis (FMEA)
Key Define Tools:
• Cost of Poor
Quality (COPQ)
• Voice of the
Stakeholder
(VOS)
• Project Charter
• As-Is Process
Map(s)
• Primary Metric
(Y)
♦ What is the problem? The “problem” is the Output (a “Y”
in a math equation Y=f(x1,x2,x3) etc).
♦ What is the cost of this problem
♦ Who are the stake holders / decision makers
♦ Align resources and expectations
Define – DMAIC ProjectWhat is the project?
Six SigmaSix Sigma
Project Project
CharterCharterVoice of the StakeholderStakeholders
$
Cost of Poor
Quality
Define – As-Is ProcessHow does our existing process work?Move-It! Courier Package HandlingProcess
Acco
un
tin
gF
ina
lizin
gD
eliv
ery
Out-Sort SupervisorOut-Sort ClerkAccounts
SupervisorAccounts
Receivable ClerkWeight Fee ClerkDistance Fee ClerkIn-Sort SupervisorIn-Sort ClerkMail ClerkCourier
Observ e packageweight (1 or 2) onback of package
Look upappropriate
Weight Fee andwrite in top middlebox on package
back
Take packagesf rom Weight FeeClerk Outbox toA/R Clerk Inbox.
Add Distance &Weight Fees
together and writein top right box on
package back
Circle Total Feeand Draw Arrow
f rom total tosender code
Take packagesf rom A/R Clerk
Outbox toAccounts
Superv isor Inbox.
Write Total Feef rom package in
appropriateSender column onAccts. Supv .’s log
Add up Total # ofPackages and
Total Fees f romlog and createclient inv oice
Deliv er inv oice toclient
Submit log toGeneral Managerat conclusion of
round.
Take packagesf rom Accounts
Superv isorOutbox to Out-
Sort Clerk Inbox.
Draw 5-point Starin upper right
corner of packagef ront
Sort packages inorder of Sender
Code bef oreplacing in outbox
Take packagesf rom Out-Sort
Clerk Outbox toOut-Sort
Superv isor Inbox.
Observ e senderand receiv er
codes and makeentry in Out-SortSuperv isor’s log
Deliv er Packagesto customers
according to N, S,E, W route
Submit log toGeneral Managerat end of round
Submit log toGeneral Managerat end of round
Does EVERYONE
agree how the current
process works?
Define the Non Value
Add steps
Define – Customer RequirementsWhat are the CTQs? What motivates the customer?
Voice of the CustomerVoice of the Customer Key Customer IssueKey Customer Issue Critical to QualityCritical to QualitySECONDARY RESEARCH
PRIMARY RESEARCH
SurveysSurveys
OTM
Market Data
Indust
ry I
nte
lLis
tenin
g P
ost
s
Industry Benchmarking
Focus Groups
Customer Service
Customer Correspondence
Obser-vations
Measure – Baselines and
CapabilityWhat is our current level of performance?
♦ Sample some data / not all data
♦ Current Process actuals measured
against the Customer expectation
♦ What is the chance that we will succeed
at this level every time?50403020100
95% Confidence Interval for Mu
26.525.524.523.522.521.520.519.5
95% Confidence Interval for Median
Variable: 2003 Output
19.7313
8.9690
21.1423
Maximum3rd QuartileMedian1st QuartileMinimum
NKurtosisSkewnessVarianceStDevMean
P-Value:A-Squared:
26.0572
11.8667
25.1961
55.290729.610023.147516.4134 0.2156
1000.2407710.238483
104.34910.215223.1692
0.8540.211
95% Confidence Interval for Median
95% Confidence Interval for Sigma
95% Confidence Interval for Mu
Anderson-Darling Normality Test
Descriptive Statistics
Others
AmountLate
41779
4.017.079.0
100.0 96.0 79.0
100
50
0
100
80
60
40
20
0
Defect
Count
PercentCum %
Pe
rce
nt
Co
unt
Pareto Chart for Txfr Defects
Measure – Failures and RisksWhere does our process fail and why? Subjective opinion mapped into an “objective” risk profile number
Failure Modes and Effects Analysis (FMEA)
Process or
Product Name:Prepared by: Page ____ of ____
Responsible: FMEA Date (Orig) ______________ (Rev) _____________
Process
Step/Part
Number Potential Failure Mode Potential Failure Effects
S
E
V Potential Causes
O
C
C Current Controls
D
E
T
R
P
N
Actions
Recommended Resp. Actions Taken
S
E
V
O
C
C
D
E
T
R
P
N
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
Process/Product
X1
X2
X4
X3
etc
Six SigmaSix Sigma
Analyze – Potential Root CausesWhat affects our process?
y = f (xy = f (x11, x, x22, x, x33 . . . x. . . xnn))
Ishikawa Diagram (Fishbone)
Analyze – Validated Root CausesWhat are the key root causes?
Other s
AmountLate
41779
4.017.079.0
100.0 96.0 79.0
100
50
0
100
80
60
40
20
0
Defect
Count
PercentCum %
Perc
ent
Count
Pareto Chart for Txfr Defects
Six SigmaSix Sigma
y = f (xy = f (x11, x, x22, x, x33 . . . x. . . xnn))
Critical Xs
Other
Clerical
Currency
2 312
11.817.670.6
100.0 88.2 70.6
15
10
5
0
100
80
60
40
20
0
Defect
Count
PercentCum %
Perc
ent
Count
Pareto Chart for Amt Defects
Process
Simulation
Data Stratification
Regression Analysis
Experimental Design
Improve – Potential SolutionsHow can we address the root causes we identified?
♦Address the causes, not the symptoms.
y = f (xy = f (x11, x, x22, x, x33 . . . x. . . xnn))
Critical Xs
Decision
Ev
aluate
Clarify
Gen
erate
Divergent | ConvergentDivergent | Convergent
Improve – Solution SelectionHow do we choose the best solution?
Time
Quality
Cost
ScoreOtherCBATimeSigmaSolution
Six SigmaSix Sigma
Solution Solution
Implementation Implementation
PlanPlan
Solution Selection Matrix
XNice
Idea
Nice
Try☺
SolutionRight Wrong
Imple
menta
tion
Bad
Good
Control – Sustainable BenefitsHow do we ”hold the gains” of our new process?
♦ Some variation is normal and OK
♦ How High and Low can an “X” go yet not materially impact the “Y”
♦ Pre-plan approach for control exceptions
0 10 20 30
15
25
35
Observation Number
Indiv
idual V
alu
e
Mean=24.35
UCL=33.48
LCL=15.21
Process Owner: Date:
Process Description: CCR:
Measuring and Monitoring
Key
Measure
ments
Specs
&/or
Targets
Measures
(Tools)
Where &
Frequency
Responsibility
(Who)
Contingency
(Quick Fix)Remarks
P1 - activity
duration,
min.
P2 - # of
incomplete
loan
applications
Process Control System (Business Process Framework)
Direct Process Customer:
Flowchart
Customer Sales Branch ManagerProcessingLoan Service
Manager
1.1
Applic
ation &
Revie
w1.2
Pro
cessin
g1.3
Cre
dit r
evi
ew
1.4
Revie
w1.5
Dis
clo
sure
Apply forloan
Reviewappliation forcompleteness
ApplicationComplete?
Completemeeting
informationNo
DFSS – The Design MethodologyDesign for Six Sigma
♦ Uses– Design new processes, products, and/or services from scratch
– Replace old processes where improvement will not suffice
♦ Differences between DFSS and DMAIC– Projects typically longer than 4-6 months
– Extensive definition of Customer Requirements (CTQs)
– Heavy emphasis on benchmarking and simulation; less emphasis on baselining
♦ Key Tools– Multi-Generational Planning (MGP)
– Quality Function Deployment (QFD)
Define Measure Analyze Develop Verify
Topics
♦Understanding Six Sigma
♦History of Six Sigma
♦Six Sigma Methodologies & Tools
♦Roles & Responsibilities
Champions
♦ Promote awareness and execution of Six Sigma within lines of business and/or functions
♦ Identify potential Six Sigma projects to be executed by Black Belts and Green Belts
♦ Identify, select, and support Black Belt and Green Belt candidates
♦ Participate in 2-3 days of workshop training
Black Belts
♦ Use Six Sigma methodologies and advanced tools
(to execute business improvement projects
♦ Are dedicated full-time (100%) to Six Sigma
♦ Serve as Six Sigma knowledge leaders within
Business Unit(s)
♦ Undergo 5 weeks of training over 5-10 months
Green Belts
♦ Use Six Sigma DMAIC methodology and basic tools to execute improvements within their existing job function(s)
♦ May lead smaller improvement projects within Business Unit(s)
♦ Bring knowledge of Six Sigma concepts & tools to their respective job function(s)
♦ Undergo 8-11 days of training over 3-6 months
♦ Subject Matter Experts
– Provide specific process knowledge to Six Sigma teams
– Ad hoc members of Six Sigma project teams
♦ Financial Controllers
– Ensure validity and reliability of financial figures used by Six Sigma project teams
– Assist in development of financial components of initial business case and final cost-benefit analysis
Other Roles
THANK YOU