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DMAIC
The One Methodology for
Improvement Projects/Problem
Solving Within NCE
Introduction to DMAIC
2
MH'97
Target
2004+
Operation
EXCELLENCE
2007
CI
Time
Performance
2008200520011997
Consumer and cus...
Introduction to DMAIC
3
Leadership Development
Nestlé management & leadership principles, business principles, Nestlé on t...
Introduction to DMAIC
4
DMAIC Introduction in the Foundation Modules
Nestlé Operating Model (NOM):Nestlé Operating Model (...
Introduction to DMAIC
5
Typical DMAIC Project Goals
• Reduce costs, reduce consumer complaints
• Improve productivity
• In...
Introduction to DMAIC
6
Ongoing Projects Within Nestlé
Business Product Title
Confectionary Smarties Reduce consumer compl...
Introduction to DMAIC
7
DMAIC: Methodology to Tackle Problems Identified by the Operation
Feedback
Inputs
Outputs
Measures...
DMAIC Success Factors
Introduction to DMAIC
9
Key Success Factors
• Top management actively participates and leads
• The portfolio of projects i...
Introduction to DMAIC
10
Key Success Factors, cont.
• There is a careful selection of:
• Projects
• Project sponsors
• Gre...
DMAIC Roles
Introduction to DMAIC
12
DMAIC Roles
Role Description Nestlé
Executive steering
committee
Sets direction NCE steering comm...
Introduction to DMAIC
13
DMAIC Structure Within a Factory
1 Focused Improvement Leader
• Either Black or Green Belt
• Work...
Introduction to DMAIC
14
Competence Alignment with Project Scope and Complexity of Causes
Scope of Project Complexity of
C...
Introduction to DMAIC
15
Different Levels of DMAIC Application Within a Factory
Top
Management
Top
Management
Middle
Manag...
DMAIC Building Strategy
Introduction to DMAIC
17
Coaching Models
• Green Belts will be coached through the DMAIC phases
• Two models of coaching: ...
Introduction to DMAIC
18
Coaching Model
10-12w
DEFINE MEASURE ANALYZE IMPROVE CONTROL
Green Belt coaching should take appr...
Introduction to DMAIC
20
Summary
• DMAIC will be the one improvement method used
within NCE
• DMAIC will be used across th...
Introduction to DMAIC
21
The essence of
Six Sigma
Introduction to DMAIC
22
Brief History of DMAIC
1979 - Motorola quality imperative “roots of Six Sigma”
1981 - Motorola ch...
Introduction to DMAIC
23
Who uses DMAIC - Six Sigma...in India
• Whirlpool
• LG Electronics
• Samsung
• GE Group
• Samtel
...
Module 1.3: Identifying the Customers
What You Can Learn: The Kano Model
Delighters
M
ore
Is
B
etter
Must Be
Delight
Neutr...
Module 1.3: Identifying the Customers
The Kano Model and VOC
• Must Be characteristics:
• Generally taken for granted
• Un...
Introduction to DMAIC
26
What is Quality?
Non conformance to customer
specification
“ …conformance to the agreed
customer ...
Introduction to DMAIC
27
Would you use this cannon to shoot a fly?
We need to use the most cost effective tool to make the...
Introduction to DMAIC
28
What is DMAIC?
• A Measurement SystemA Measurement System
• A Problem-Solving ApproachA Problem-S...
Introduction to DMAIC
29
Why 99.7% is Not Good Enough?
3 Sigma Process3 Sigma Process
Less than 38 newborn babies accident...
Introduction to DMAIC
30
What's Six Sigma?
Introduction to DMAIC
31
Average
River
Depth - 5ft
Focus on Average can turn any business “Red”Focus on Average can turn a...
What causes Defects?What causes Defects?
VVaarriiaattionion
Introduction to DMAIC
33
Count the number of times the 6th letter
of the alphabet appears in the following text:
The neces...
Introduction to DMAIC
34
What Does “Sigma” Tell Us?
Process Sigma (or σ) is a statistical term that represents how much va...
Introduction to DMAIC
36
Target
Weight
X XXX X XX XX
XX
X
X
X
XX
X
X
X
X
X
X
X
X
X
XX
X
X
X
XX X
XX
XXX
X X
X
X
X
Every Hu...
Introduction to DMAIC
37
Mean
Customer
Specification
Mean Customer
Specification
1σ
2σ
3 σ
A 3σ process because 3 standard...
Introduction to DMAIC
38
Area under the curve
Introduction to DMAIC
39
DPMO – Know your Sigma
• A product has five areas where defect can occur we produced 30 Products ...
Introduction to DMAIC
40
Consider the example of Delivery Time
of two Supplier.
• Delta Services has a mean of 5.2 Days
• ...
Introduction to DMAIC
4141
μ
USLUSL
T
μ
USLUSL
T
USLUSL
T
μ
Precise but not Accurate
Accurate but not Precise
Accurate and...
Introduction to DMAIC
42
Overview of DMAIC
1
2
3
4
5
DEFINE
MEASURE
ANALYZE
IMPROVE
CONTROL
43
Introduction to DMAIC
43
DEFINE
MEASURE
ANALYZE
CONTROL
DEFINE:
• Problem
• SIPOC
• VOC
• Root-cause investigation
• Te...
Introduction to DMAIC
DEFINE Road Map
Need
Customer
drivers CTQs
Who What When
Introduction to DMAIC
45
SIPOC
S I
P
O C
Suppliers Inputs
Process
Outputs Customers
Process Boundary
33
44
5511 22
S I
P
O...
Introduction to DMAIC
46
ScrapScrap
90%90%
Customer QualityCustomer Quality
ReworkRework
Hidden Factory
NOT
OK
Yield After...
Introduction to DMAIC
47
Why Measure?
Is it advisable to attack a problem
without measuring it?
Thus it’s advisable to:
• ...
Introduction to DMAIC
MEASURE Road Map
Introduction to DMAIC
49
Operational Definition
An operational definition is a precise description that
tells you how to g...
Introduction to DMAIC
50
Sampling
Introduction to DMAIC
51
Types of Sampling
Introduction to DMAIC
52
Sampling
• Develop data collection plan and collect data…
Introduction to DMAIC
53
Example: On-Time Delivery
• This company was having
trouble delivering products due
to delays in ...
Introduction to DMAIC
54
• Now look at the time plot of the same data shown previously
on the frequency plots
• What is yo...
Introduction to DMAIC
55
Analyze – with proper tools
Support different situations by specific tools
Introduction to DMAIC
ANALYZE Road Map
Introduction to DMAIC
57
Identify Causes of Variation
Tools for Identification of causes of Variation :
• Process MapProce...
Introduction to DMAIC
58
Focus of Six Sigma
x
Introduction to DMAIC
59
Process Map Analysis
• Steps That Are Essential Because They Physically Change The Product/Servic...
Introduction to DMAIC
60
Fish Bone Analysis
• Also called Cause & Effect Diagram or Ishikawa Diagram
• Used to identify Po...
Module 2.3: Data Analysis II: Looking for Patterns Not Related to Time
The Pareto Principle
• The Pareto principle is ofte...
Module 2.3: Data Analysis II: Looking for Patterns Not Related to Time
Examples of Pareto Charts
0
10
20
30
40
50
60
70
Sc...
Introduction to DMAIC
IMPROVE Road Map
Introduction to DMAIC
64
Once the Root Causes have been identified, it becomes easy to build solutions around
these causes...
Introduction to DMAIC
65
Mistake Proofing
The Problem:
Automobiles are crossing the
train tracks and getting hit by
a trai...
Introduction to DMAIC
66
The “ B ” Fix:
Place cross gates at crossing to
further deter crossing of vehicles.
Dilemma: Vehi...
Introduction to DMAIC
67
Fail-safing Connection to the FMEA
Process
Step/Input
Potential Failure Mode Potential Failure Ef...
Introduction to DMAIC
68
Fail-safing Connection to the FMEA
Function
Part/Process
Failure Mode
Effects
Causes
Controls
Sev...
Introduction to DMAIC
CONTROL Road Map
Introduction to DMAIC
70
Control Phase
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
Average
Lower Control Limit (LCL)
Uppe...
Introduction to DMAIC
71
Now count the number of times the 6th letter
of the alphabet appears in the following text:
The n...
Thank You!!!
DMAIC is a journey
Not a destination….
Introduction to DMAIC
73
Introduction to DMAIC
74
Mistake Proofing
PREDICTION/PREVENTION
Some cameras will
not function when
there is not enough
li...
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Six sigma presentation

  1. 1. DMAIC The One Methodology for Improvement Projects/Problem Solving Within NCE
  2. 2. Introduction to DMAIC 2 MH'97 Target 2004+ Operation EXCELLENCE 2007 CI Time Performance 2008200520011997 Consumer and customer focus Business and operations goal alignment Excellence in leadership and competence development One model for improving performance Using world-class tools and best practices Engaging everybody’s heart and mind ... to sustain ongoing savings to support business growth NCE, Our Way Forward to Improve Performance
  3. 3. Introduction to DMAIC 3 Leadership Development Nestlé management & leadership principles, business principles, Nestlé on the move ... Nestlé Integrated Management System (NIMS) Quality, safety, environment, standards, business excellence ... Goal Alignment Examples: mission-directed work teams, mini business units, DMAIC problem solving ... ... Measure, Monitor, Organize Customer Distribution Packaging Raw Material LEAN Supply Chain Manufacturing Total Performance Management TPM Consumer Audits, Self-Assessment Tools ... The “One Model”: A Common Language and Way of Doing Things
  4. 4. Introduction to DMAIC 4 DMAIC Introduction in the Foundation Modules Nestlé Operating Model (NOM):Nestlé Operating Model (NOM): Operational master planning and three foundation modules… …are part of the goal alignment dimension Operational master planning and three foundation modules… …are part of the goal alignment dimension Three Foundation Modules:Three Foundation Modules: Measures Operation Reviews Problem Solving TPM Pillars:TPM Pillars: The TPMN problem- solving model and tools are aligned with the foundations problem- solving module The TPMN problem- solving model and tools are aligned with the foundations problem- solving module Operational Master Planning
  5. 5. Introduction to DMAIC 5 Typical DMAIC Project Goals • Reduce costs, reduce consumer complaints • Improve productivity • Increase capacity, utilization, availability, flexibility • Inventory—lower costs, faster delivery, reduced scrap • Scheduling, forecast accuracy, availability • Supply chain—cost, inventory, cycle time, quality, availability • Speed—new products to market, service, approvals, delivery • Facilities—design, layout, space utilization, flow • Order processing—improve accuracy, customer satisfaction • Improve quality of services • HR—staffing, benefit administration, employee services • Data management, accuracy, timeliness, access, cost • Transactions—reduce errors and handoffs, increase accountability • Billing—speed of collections, reduce errors and delinquencies
  6. 6. Introduction to DMAIC 6 Ongoing Projects Within Nestlé Business Product Title Confectionary Smarties Reduce consumer complaints related to insufficient amount of orange and blue smarties in selling unit Coffee and beverages Nescafé Reduce rework due to visual quality deviation ("bubble" or black particle) Roasted and ground coffee Nespresso Reduce downtime due to sleeve maker machine from 70 min to 25 min Roasted and ground coffee Nespresso Increase the service level in Italy from 95% to 99% GLOBE Fitgap Increase service level of Fitgap (Fitgap approved within the agreed delay) from 80% to 90% Nutrition Infant formula Increase line efficiency of optima lines from 50% to the targeted value of 70% Nutrition Infant formula Reduce the turnaround time from 10 days to 5 days Purina Dry dog food Increase the average moisture content from 8% to 9% while reducing the variability from 0.8% to 0.5% Purina Dry cat food Increase the blending quality delivered by automated blending machine Chilled culinary Liquid batter Reduce overfilling from 0.5% to 0.2% Purina Wet dog food Reduce the variability of the ratio chunk/gravy DMAIC Projects SAR Projects
  7. 7. Introduction to DMAIC 7 DMAIC: Methodology to Tackle Problems Identified by the Operation Feedback Inputs Outputs Measures Ideas Problems Information Request for Support Issue/Action Go See Think Do IncreasinglyDifficulttoSolve Formal Problem Solving
  8. 8. DMAIC Success Factors
  9. 9. Introduction to DMAIC 9 Key Success Factors • Top management actively participates and leads • The portfolio of projects is balanced • DMAIC leadership is not left solely to Green Belts • The finance department is involved in measuring and validating the financial benefits • Do not use DMAIC to cut jobs • Remember that it takes time to implement DMAIC on an organizationwide basis • Break down existing barriers in the organization
  10. 10. Introduction to DMAIC 10 Key Success Factors, cont. • There is a careful selection of: • Projects • Project sponsors • Green Belts and Yellow Belts • The project scope is well defined and feasible • Able to be accomplished in a reasonable time • Appropriate for Belt level • A good “project review” process is employed on a: • Plant basis • Regional basis • Global basis
  11. 11. DMAIC Roles
  12. 12. Introduction to DMAIC 12 DMAIC Roles Role Description Nestlé Executive steering committee Sets direction NCE steering committee Champions Prioritize and deploy teams TM, market IP manager, factory manager Sponsors Assist teams on an ongoing basis Factory management (factory manager, then dept. heads) Master Black Belts Serve as experts/ consultants/coaches Market expert coordinating improvement projects Green/Black Belts Run medium/big project/serve as coaches of White and Yellow Belts Can be factory IP manager White/Yellow Belts Run small projects Line supervisor/shift leader Improvement teams Deliver and implement results Factory employee Notes: • "Belts" are the DMAIC practitioners
  13. 13. Introduction to DMAIC 13 DMAIC Structure Within a Factory 1 Focused Improvement Leader • Either Black or Green Belt • Works on DMAIC full time • Oversees up to 15–20 Belts 3 Green Belts • Serve as project leader and coach • Devote ~25% time to DMAIC 1–7 Yellow Belts/White Belts • Serve as team members or project leaders • Devote ~10–20% time to DMAIC Notes: • "Belts" are the DMAIC practitioners. • Factories are the first targeted community; the supply chain can have a similar structure. Example: Average factory of 300 employees Factory Manager Focused Improvement leader Green Belt Green Belt Green Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Functional Report Hierarchical Report Factory Manager Focused Improvement leader Green Belt Green Belt Green Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Yellow/White Belt Functional Report Hierarchical Report Area Area 1 Area 2 Area n
  14. 14. Introduction to DMAIC 14 Competence Alignment with Project Scope and Complexity of Causes Scope of Project Complexity of Causes Competence Dedicated Time (recommended) Focus in chain High Black Belt Advanced DMAIC 50% – 100% Focus in factory Medium Green Belt Intermediate DMAIC 30% – 40% Focus in area Medium Yellow Belt Basic 2 DMAIC 20% – 30% Focus in line Low White Belt Basic 1 DMAIC 10% – 20%
  15. 15. Introduction to DMAIC 15 Different Levels of DMAIC Application Within a Factory Top Management Top Management Middle Management — Functional Specialists Workforce – Front Line and Staff Scope BigProjectsBigProjectsSmallProjectsSmallProjectsDaytoDayDaytoDay MethodsProject Responsibility # of Concurrent Projects Duration Problem- Solving Module More Formal Basic Green/Black Belt Mind- set Less Formal Go-See- Think-Do 8 3 100 0–1 month 2 weeks–3 months 2–6 months
  16. 16. DMAIC Building Strategy
  17. 17. Introduction to DMAIC 17 Coaching Models • Green Belts will be coached through the DMAIC phases • Two models of coaching: remote coaching and joint coaching • Goal of coaching is to enable Green Belts to succeed with their projects and earn a financial gain of at least €20,000 for their project sponsors Remote Coaching Joint Coaching How it works • There is a predetermined time for each phase of the training • The coach and Green Belt are connected by electronic means; they need to be physically together in the same place • Other Green Belts do not assist in the coaching sessions • There is a predetermined time for each phase of the training • The coach and Green Belt conduct their training sessions together in the same place • Another Green Belt can assist the coaching session, if feasible When appropriate • When the Green Belt and his/her coach cannot meet at the same site because they are working at geographically separate locations • When several Green Belts can meet at one site at the same time • When a project requires the coach’s physical presence
  18. 18. Introduction to DMAIC 18 Coaching Model 10-12w DEFINE MEASURE ANALYZE IMPROVE CONTROL Green Belt coaching should take approximately 14 hours per project: • Three hours for the project setup and DEFINE phase • Three hours for the MEASURE phase • Two hours for the ANALYZE phase • Two hours for the IMPROVE phase • Two hours for the CONTROL phase • Two hours for project presentation, wrap-up, and project certification (part of the total certification process) Note: With joint coaching, another Green Belt can help out with the coaching sessions as well as the sponsor. 3h 3h 2h 2h 2h 2h DMAIC Schedule
  19. 19. Introduction to DMAIC 20 Summary • DMAIC will be the one improvement method used within NCE • DMAIC will be used across the value chain, first focusing on manufacturing (focused improvement pillar) • DMAIC brings benefits to the whole organization • DMAIC requires a variety of new roles across the organization (from practitioners to sponsors) • Nestlé will progressively build DMAIC capability before becoming self-sufficient
  20. 20. Introduction to DMAIC 21 The essence of Six Sigma
  21. 21. Introduction to DMAIC 22 Brief History of DMAIC 1979 - Motorola quality imperative “roots of Six Sigma” 1981 - Motorola challenge to improve 10 fold in 5 years 1988 - Motorola wins Malcolm Baldrige Quality Award 1991 - Motorola Six Sigma Research Institute established 1992 - Motorola, Texas Instruments, IBM, Kodak, and others initiated efforts to develop the 6σ Black Belt program 1995 - GE mandates Six Sigma rollout; estimates current performance at 3.0 Sigma 1997 - GE invests $250M to train 4,000 Black Belts and 60,000 Green Belts out of workforce of 222,000; recoups $300M same year 1998 - GE calculates Six Sigma payoff at $1.25B • Mikel J. Harry is called the father of Six Sigma
  22. 22. Introduction to DMAIC 23 Who uses DMAIC - Six Sigma...in India • Whirlpool • LG Electronics • Samsung • GE Group • Samtel • Phillips • Maruti • TVS Group • Delphi • TATA Steel • Wipro • Escotel • Crompton Greaves • Motorola • DHL • Asian Paints • Honeywell • VIP Industries • Escorts Hospital • Jubliant • Agilent Tech • Citibank • AMEX • ICICI • Hindustan Times • Accenture • HCL • Daksh • Vertex • Patni • Infosys • Airtel …. Now it is Nestle too !!
  23. 23. Module 1.3: Identifying the Customers What You Can Learn: The Kano Model Delighters M ore Is B etter Must Be Delight Neutral Dissatisfaction CustomerSatisfaction Degree of Achievement FulfilledAbsent ΤΙΜ Ε “Hygiene Factors” Taken for granted Basic Spoken Measurable Range of Fulfillment Unexpected Unknown
  24. 24. Module 1.3: Identifying the Customers The Kano Model and VOC • Must Be characteristics: • Generally taken for granted • Unless they are absent; fix these first • More Is Better: • Additional features customers would appreciate • Delighters: • Generally not mentioned, since customers are not dissatisfied with their absence • The primary objective of the Kano model is to capture the most important customer requirements from the customer’s perspective • By working on the critical requirements, you will keep your project focused and increase your chances of success • Anything below customer specification is defect and above is quality Delighters M ore Is Better Must Be Delight Neutral Dissatisfaction CustomerSatisfaction Degree of Achievement FulfilledAbsent Resigned to Reality Pleased Not Pleased Taken for Granted
  25. 25. Introduction to DMAIC 26 What is Quality? Non conformance to customer specification “ …conformance to the agreed customer specifications and requirements...” Quality & Defect What is Defect?
  26. 26. Introduction to DMAIC 27 Would you use this cannon to shoot a fly? We need to use the most cost effective tool to make the a sustainable impact…. No…
  27. 27. Introduction to DMAIC 28 What is DMAIC? • A Measurement SystemA Measurement System • A Problem-Solving ApproachA Problem-Solving Approach • A Disciplined Change ProcessA Disciplined Change Process ““THE SIX SIGMA BREAKTHROUGH STRATEGY”THE SIX SIGMA BREAKTHROUGH STRATEGY” MMeasureeasure AAnalyzenalyze IImprovemprove CControlontrolDDefineefine
  28. 28. Introduction to DMAIC 29 Why 99.7% is Not Good Enough? 3 Sigma Process3 Sigma Process Less than 38 newborn babies accidentally dropped by doctors and nurses each year No electricity for 9 minutes in 5 years One short or long landing every two years 2 railway accidents per year 1.4 minutes of unsafe water every 5 years 3.4 Defects per Million Products Less than 38 newborn babies accidentally dropped by doctors and nurses each year No electricity for 9 minutes in 5 years One short or long landing every two years 2 railway accidents per year 1.4 minutes of unsafe water every 5 years 3.4 Defects per Million Products 6 Sigma Process6 Sigma Process More than 110,000 newborn babies accidentally dropped by doctors and nurses each year No electricity for 85 hours each year Four short or long landings per day 16 railway accidents per day 16 minutes per week of unsafe water supply 66807 Defects per Million Products More than 110,000 newborn babies accidentally dropped by doctors and nurses each year No electricity for 85 hours each year Four short or long landings per day 16 railway accidents per day 16 minutes per week of unsafe water supply 66807 Defects per Million Products
  29. 29. Introduction to DMAIC 30 What's Six Sigma?
  30. 30. Introduction to DMAIC 31 Average River Depth - 5ft Focus on Average can turn any business “Red”Focus on Average can turn any business “Red” Mean 12 Feet 6 Feet
  31. 31. What causes Defects?What causes Defects? VVaarriiaattionion
  32. 32. Introduction to DMAIC 33 Count the number of times the 6th letter of the alphabet appears in the following text: The necessity of training farm hands for the first class farms in the fatherly handling of farm live stock is foremost in the eyes of the farm owners. Since the forefathers of the farm owners trained the farm hands for first class farms in the fatherly handling of farm live stock, the farm owners felt they should carry on with the family tradition of training farm hands of the first class farmers in the fatherly handling of farm live stock because they believe it is the basis of good fundamental farm management. How Variation Occurs
  33. 33. Introduction to DMAIC 34 What Does “Sigma” Tell Us? Process Sigma (or σ) is a statistical term that represents how much variation there is in a process relative to customer specifications Sony Automation – Paper Blow
  34. 34. Introduction to DMAIC 36 Target Weight X XXX X XX XX XX X X X XX X X X X X X X X X XX X X X XX X XX XXX X X X X X Every Human Activity Has Variability... Customer Specification defectsdefects Understanding Variability & Customer specification Is The Essence of Six Sigma Concept of Variability USL Customer Specification LSL
  35. 35. Introduction to DMAIC 37 Mean Customer Specification Mean Customer Specification 1σ 2σ 3 σ A 3σ process because 3 standard deviations fit between target and spec 3σ 6.6% Defects Before 1σ 2σ 3σ 4σ 5σ 6σ After 6σ ! No Defects! Reducing Variability Is The Key To Six Sigma What is Six Sigma
  36. 36. Introduction to DMAIC 38 Area under the curve
  37. 37. Introduction to DMAIC 39 DPMO – Know your Sigma • A product has five areas where defect can occur we produced 30 Products with a total of 15 defects. What is the DPMO? Sigma DPMO YIELD Sigma DPMO YIELD 6 3.4 99.99966% 2.9 80,757 91.9% 5.9 5.4 99.99946% 2.8 96,801 90.3% 5.8 8.5 99.99915% 2.7 115,070 88.5% 5.7 13 99.99866% 2.6 135,666 86.4% 5.6 21 99.9979% 2.5 158,655 84.1% 5.5 32 99.9968% 2.4 184,060 81.6% 5.4 48 99.9952% 2.3 211,855 78.8% 5.3 72 99.9928% 2.2 241,964 75.8% 5.2 108 99.9892% 2.1 274,253 72.6% 5.1 159 99.984% 2 308,538 69.1% 5 233 99.977% 1.9 344,578 65.5% 4.9 337 99.966% 1.8 382,089 61.8% 4.8 483 99.952% 1.7 420,740 57.9% 4.7 687 99.931% 1.6 460,172 54.0% 4.6 968 99.90% 1.5 500,000 50.0% 4.5 1,350 99.87% 1.4 539,828 46.0% 4.4 1,866 99.81% 1.3 579,260 42.1% 4.3 2,555 99.74% 1.2 617,911 38.2% 4.2 3,467 99.65% 1.1 655,422 34.5% 4.1 4,661 99.53% 1 691,462 30.9% • DPU = 15/(30*5) = 0.1 • DPMO = 0.1*1000000 = 100000 • Sigma from table = 2.75 • Also Yield = 90.0%
  38. 38. Introduction to DMAIC 40 Consider the example of Delivery Time of two Supplier. • Delta Services has a mean of 5.2 Days • Omega has a mean of 5.7 Days • Target Mean is 5.5 days S.No Delta Services Omega Services 1 2 4 2 9 6 3 2 3 4 9 6 5 2 6 6 4 8 7 11 5 8 3 7 9 2 5 10 8 7 Average 5.2 5.7 Delivery time of two supplier in days Which one is Better ???? and Why ???? SD 3.61 1.49 Six Sigma focuses on reducing Variations in Processes Customer Feels the Variation and Omega is Consistent. Variation
  39. 39. Introduction to DMAIC 4141 μ USLUSL T μ USLUSL T USLUSL T μ Precise but not Accurate Accurate but not Precise Accurate and PreciseShift towards Target Reduce Variation • Shift towards Target • Reduce variation 6 3.4 5 233 4 6,210 3 66,807 2 308,537 σ PPM DMAIC Objective Objective of DMAIC
  40. 40. Introduction to DMAIC 42 Overview of DMAIC 1 2 3 4 5 DEFINE MEASURE ANALYZE IMPROVE CONTROL
  41. 41. 43 Introduction to DMAIC 43 DEFINE MEASURE ANALYZE CONTROL DEFINE: • Problem • SIPOC • VOC • Root-cause investigation • Test (verify) causes • Analyze map • Standardize process • Train personnel • Monitor performance Solutions: • Set criteria • Develop • Select • Anticipate failure mode IMPROVE Data: • Collect • Plot • Analyze • Map process Implementation: • Plan • Implement • Human side The DMAIC Process
  42. 42. Introduction to DMAIC DEFINE Road Map Need Customer drivers CTQs Who What When
  43. 43. Introduction to DMAIC 45 SIPOC S I P O C Suppliers Inputs Process Outputs Customers Process Boundary 33 44 5511 22 S I P O C Suppliers Inputs Process Outputs Customers Process Boundary 33 44 5511 22  High Level Process map from Customer Perspective
  44. 44. Introduction to DMAIC 46 ScrapScrap 90%90% Customer QualityCustomer Quality ReworkRework Hidden Factory NOT OK Yield After Inspection or Test OperationOperationInputsInputs InspectInspect First TimeFirst Time YieldYield = OK RTY is 66%RTY is 66% Process 1 2 3 Rolled Yield 81 % 73 % 4 66 % Final Test = 90%90% YieldYield 90%90% YieldYield 90%90% YieldYield 90%90% YieldYield 90%90% YieldYield Rolled Yield Versus First Time Yield
  45. 45. Introduction to DMAIC 47 Why Measure? Is it advisable to attack a problem without measuring it? Thus it’s advisable to: • Develop Data Collection plan • Validate Measurement System • Data Collection What gets measured gets done …
  46. 46. Introduction to DMAIC MEASURE Road Map
  47. 47. Introduction to DMAIC 49 Operational Definition An operational definition is a precise description that tells you how to get A value for the characteristic you are trying to measure. It includes what something is and how to measure it. To remove ambiguity • Everyone has the same understanding To provide a clear way to measure the characteristics • Identifies what to measure • Identifies how to measure • Makes sure that no matter who does the measuring, the results are essentially the same Definition Purpose
  48. 48. Introduction to DMAIC 50 Sampling
  49. 49. Introduction to DMAIC 51 Types of Sampling
  50. 50. Introduction to DMAIC 52 Sampling • Develop data collection plan and collect data…
  51. 51. Introduction to DMAIC 53 Example: On-Time Delivery • This company was having trouble delivering products due to delays in receiving materials from their suppliers • Data from the past 40 weeks on delivery dates from their two main suppliers is on the right • Based on this frequency plot, which supplier would you recommend? Note: A negative number indicates that the delivery was early Supplier A 40 Deliveries ­0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Supplier B 40 Deliveries Days from Target
  52. 52. Introduction to DMAIC 54 • Now look at the time plot of the same data shown previously on the frequency plots • What is your interpretation now that you’ve seen time and frequency plots? Which supplier would you recommend using? Time Plot of Suppliers A and B — Late Deliveries (40 weekly deliveries each) ­0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 = Supplier A = Supplier B Example: On-Time Delivery, cont.
  53. 53. Introduction to DMAIC 55 Analyze – with proper tools Support different situations by specific tools
  54. 54. Introduction to DMAIC ANALYZE Road Map
  55. 55. Introduction to DMAIC 57 Identify Causes of Variation Tools for Identification of causes of Variation : • Process MapProcess Map • Fish Bone AnalysisFish Bone Analysis • ParetoPareto • 5 Why5 Why • Control/ImpactControl/Impact
  56. 56. Introduction to DMAIC 58 Focus of Six Sigma x
  57. 57. Introduction to DMAIC 59 Process Map Analysis • Steps That Are Essential Because They Physically Change The Product/Service. • The Customer Is Willing To Pay For Them And Are Done Right The First Time. • Steps That Are Considered Non-Essential To Produce And Deliver The Product Or Service To Meet The Customer’s Needs And Requirements. • Customer Is Not Willing To Pay For Step. VA NVA Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Stage 6 Stage 7 Reduce or Eliminate Analyzing Process Map helps in identification of steps Value Adding Non-Value adding
  58. 58. Introduction to DMAIC 60 Fish Bone Analysis • Also called Cause & Effect Diagram or Ishikawa Diagram • Used to identify Possible Causes • Uses the concept of Brainstorming to generate ideas Effect MachineMan Material Method
  59. 59. Module 2.3: Data Analysis II: Looking for Patterns Not Related to Time The Pareto Principle • The Pareto principle is often described by the “80/20 rule,” which says that, in many situations, roughly 80% of the problems are caused by only 20% of the contributors • The Pareto principle implies that we can frequently solve a problem by identifying and attacking its “vital few” sources
  60. 60. Module 2.3: Data Analysis II: Looking for Patterns Not Related to Time Examples of Pareto Charts 0 10 20 30 40 50 60 70 SchedMntnc HardwareFailure Upgrades SoftwareBugs PowerOutages Unexplained Reason Computer Downtime August 1–31 0 10 20 30 40 50 60 70 80 90 100 PercentofTotal Count Percent Reasons Count 32.8 17.1 13.0 12.9 10.7 10.3 3.1 Cum % 32.8 49.9 76.10 62.9 75.8 86.6 96.9 100.0 39.70 30.20 30.00 24.90 24.00 7.18 Percent O ther SPLICE M ISSING M /C START & STOP DE LAM INATE PHOTOCELL AUTO TUNE OVERLAP ROLL CHANGING 250 200 150 100 50 0 100 80 60 40 20 0 Pareto Chart For Laminate Losses Laminate loss reduction on TOPACK line Y= f(x1,x2,x3…)
  61. 61. Introduction to DMAIC IMPROVE Road Map
  62. 62. Introduction to DMAIC 64 Once the Root Causes have been identified, it becomes easy to build solutions around these causes. The project team should get together to build self sustaining solutions. Improve • Automations – Elimination of Human intervention • Mistake Proofing – Prevent Errors from happening Home Automated thermostat controls Iron shutoff switches Ground fault circuit breakers in bathroom Tamper proof packaging on consumer products Plastic covers for the electrical outlets Office Lock-out / tag-out maintenance procedures Barcoding- Dual palm button machinery
  63. 63. Introduction to DMAIC 65 Mistake Proofing The Problem: Automobiles are crossing the train tracks and getting hit by a train. The “ C ” Fix: Place flashing cross signs at the crossing to alert vehicles. Dilemma: Vehicles are alerted of oncoming trains but can still cross. Problem not solved.
  64. 64. Introduction to DMAIC 66 The “ B ” Fix: Place cross gates at crossing to further deter crossing of vehicles. Dilemma: Vehicles are alerted and have limited crossing ability; however does not prevent those who arbitrarily want to cross. Problem detered but not solved. The “ A ” Fix: Build overpass for vehicles to cross train tracks without incident. Dilemma: None. Problem solved. Mistake Proofing
  65. 65. Introduction to DMAIC 67 Fail-safing Connection to the FMEA 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 What is the process step/ Input under investigation? In what ways does the Key Input go wrong? What is the impact on the Key Output Variables (Customer Requirements) or internal requirements? HowSevereisthe effecttothe cusotmer? What causes the Key Input to go wrong? Howoftendoescause orFMoccur? What are the existing controls and procedures (inspection and test) that prevent eith the cause or the Failure Mode? Should include an SOP number. Howwellcanyou detectcauseorFM? What are the actions for reducing the occurrance of the Cause, or improving detection? Should have actions only on high RPN's or easy fixes. 0 0 0 Good Failsafing devices drive down occurrence and detection rankings
  66. 66. Introduction to DMAIC 68 Fail-safing Connection to the FMEA Function Part/Process Failure Mode Effects Causes Controls Severity (1-10) Occurrence (1-10) Detectability (1-10) RPN Risk Priority Number RPN = S x O x D = 1 to 1000 RPN Risk Priority Number RPN = S x O x D = 1 to 1000 How it Works
  67. 67. Introduction to DMAIC CONTROL Road Map
  68. 68. Introduction to DMAIC 70 Control Phase 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 Average Lower Control Limit (LCL) Upper Control Limit (UCL) Day1 Day2 Day3 Day4 Day5 Day6 Day7 Day9 Day10 Day11 Day8 Measurement, # of Defectives, etc.. A Control Chart is simply a Run Chart with a statistically determined upper control limit (UCL) and lower control limit (LCL) drawn on either side of the process average. The normal variation in the process is used to calculate the control limits. Process Noise (Common Cause) Process Signal (Special Cause) Process Noise (Common Cause) Process Signal (Special Cause) A process is said to be in statistical control when only common causes of variation are present. Control Charts
  69. 69. Introduction to DMAIC 71 Now count the number of times the 6th letter of the alphabet appears in the following text: The necessity in training hired hands in the strange handling of valuable live stock in premier operations is a priority in the eyes of the operations owners. Since the ancestors of the owners trained the hired hands in premier operations in the strange handling of valuable live stock, the operations owners thought they should carry on with the happy tradition of training hired hands in the premier operations in the strange handling of valuable live stock because they believe it is the basis of good basic operations management. The Inspection Exercise
  70. 70. Thank You!!! DMAIC is a journey Not a destination….
  71. 71. Introduction to DMAIC 73
  72. 72. Introduction to DMAIC 74 Mistake Proofing PREDICTION/PREVENTION Some cameras will not function when there is not enough light to take a picture. DETECTION Some laundry dryers have a device that shuts them down when overheating is detected.

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