Lean Six Sigma Yellow Belt - IASSC
Course Book
INDEX
• Module 1 – Evolution & Introduction to Lean Six Sigma
• Module 2 – Define Phase
• Module 3 – Measure Phase
•Module 3 – Improve Phase
• Module 4 – Analyze Phase
• Module 6 – Control Phase & Project Closure
•
2
Module
1
Evolution & Introduction to Lean Six Sigma
3
What is Sigma?
• Sigma is a letter in the Greek Alphabet
• Sigma is a Symbol which shows the degree of variation in a process (standard deviation)
• As an upper case letter (∑), it is used as a symbol for sums and series in which each term is
computed from the previous one by adding (or subtracting) a constant. Sigma is used to add all
parts, in sequence, to give a total made up of every number in the sequence.
How close are you
to meet your
target?
4
What is Six Sigma?
5
Six Sigma - A Breakthrough Strategy
A Business Management Strategy developed by Bill Smith (Father of Six Sigma)Motorola,USA,1981
It is a methodology for continuous improvement
It is a set of statistical and other quality tools arranged in a unique way
A Problem Solving technique, Statistically Approached, A Quality Philosophy, Out of Box thinking
Applied to existing processes and products
Improves the quality of process outputs by identifying and removing the causes of defects (errors)
and minimizing variability in manufacturing and business processes
Accuracy: 99.9997% free of defects(3.4 defects per 1 million)
We gain a competitive edge in Quality, Cost, Customer Satisfaction
6
Fundamental Definition
The fundamental definition of Six Sigma capability refers to a process where "the center of the
process is away from the nearest specification limit by six standard deviations of the process".
It is a set of statistical and other quality tools arranged in a unique way.
It is a way of knowing where you are and where you could be!
7
Origin of Six Sigma
MOTOROLA
The company that invented Six Sigma
The term “Six Sigma” was coined by Bill Smith, an engineer from Motorola
Late 1970s- Motorola started experimenting with problem solving statistical analysis
1987- Motorola officially launched its Six Sigma program
8
The Growth of Six Sigma
GE
The company that perfected Six Sigma
Jack Welch launched Six Sigma at GE in Jan, 1996.
1998/99- Green Belt exam certification became the criterion for management promotions
2002/03- Green Belt certification became the criterion for promotion to management roles
9
Business Cost Model
Old Model
New Model
Cost + Profit = Sales Price
Price - Cost = Profit
Price set by adding profit margin
on top of cost
Few choices for customer
Value is customer perception
Ongoing cost reduction activities
More choices for customer
Increase profits
Possibly lower sales price
10
Cost of Poor Quality
11
Six Sigma Organizations
GE … All 300,000+ GE employees must be Six Sigma
certified
3M … New CEO (from GE) requires all 3M
employees to become Six Sigma certified
DuPont
CSC
AlliedSignal
LG
Sun Microsystems
EXL
Raytheon
IBM
Motorola
Boeing
Lockheed-Martin
Bank-of-America
American Express
HSBC
SAS Institute
Rapidly Increasing Areas of Application:
Healthcare – GE Healthcare
Financial
Military – NSWC, Pentagon, etc.
Fueled by:
Notorious bottom-line orientation & results
Process orientation: rigorous and systematic
approaches to innovation and design
Focus on the customer
Successful track record elsewhere
“Industry Buzz”
More than 75% companies of Fortune 500
companies use Six Sigma in some or other way.
12
Where can Six Sigma be applied?
Service
Management
Design
Purchase
Administration
Six Sigma
Methods
Production
IT
Quality
Depart
HRM
M&S
13
The Villain
Cost of Poorly Performing Processes
s level
DPMO
CP3
2
3
4
5
6
308,537
66,807
6,210
233
3.4
Not Applicable
25%-40% of sales
15%-25% of sales
5%-15% of sales
< 1% of sales
Each sigma shift provides a 10% net income improvement
Sigma (s) is a measure of “perfection” relating to process
performance capability … the “bigger the better.”
A process operating at a “Six Sigma” level produces only
3.4 defects per million opportunities (DPMO) for a defect.
Cost of Poorly Performing
Processes (CP3)
Why is Six Sigma Important?
14
The Hero
What Does Six Sigma Tell Us?
•
•
•
•
•
We don’t know what we don’t know.
We can’t do what we don’t know.
We won’t know until we measure.
We don’t measure what we don’t value.
We don’t value what we don’t measure.
• Typical Results: Companies that properly implement Six Sigma have seen
profit margins grow 20% year after year for each sigma shift (up to about 4.8s
to 5.0s). Since most companies start at about 3s, virtually each employee
trained in Six Sigma will return on average $230,000 per project to the
bottom line until the company reaches 4.7s.
• However, improved profit margins allow companies to create products &
services with added features and functions that result in greater market
shares.
15
Six Sigma Results
Company
Annual Savings
General Electric
$2.0+ billion
JP Morgan Chase
*$1.5 billion (*since inception in 1998)
Motorola
$ 16 billion (*since inception in 1980s)
Johnson & Johnson
$500 million
Honeywell
$600 million
Six Sigma Savings as % of revenue vary from 1.2 to 4.5 %
For $ 30 million/year sales – Savings potential $ 360,000 to $ 1.35 million.
16
What is Sigma?
Sigma is nothing but standard deviation.
The Standard Deviation is a measure of how
spread out numbers are. Its symbol is σ (the greek
letter sigma) The formula is easy: it is the square
root of the Variance.
With 6 sigma process, we have 99.9997% data
within -6 to +6 s.d or sigma This equals to 3.4
defects per 1000000 opportunities.
17
Variation
True Six Sigma process
18
Six Sigma Methodology
Two methodologies for acquiring, assessing, and applying customer, competitor, and
enterprise intelligence for the purposes of product, system or enterprise innovation and
design:
Iterative Process
Innovation Algorithm
DMAIC
Define
Measure
Steps A,B,C
Analyze
Improve
Control
Steps
10,11,12
Design for Six Sigma Algorithm
DMADV
Define
Measure
3
Analyze
Design
Steps 1,2,3
Verify
Steps 7,8,9
Steps 4,5,6
19
DMAIC-Phases
20
The Approach
21
The Six Sigma Initiative integrates these efforts
Knowledge
Management
22
Path for Six Sigma
Master Black Belt
Black Belt
Green Belt
Yellow Belt
Role
Roles and Responsibilities
Span
Champion
1. Identify strategic impact projects
2. Scope projects
1 - 1000
Master Black Belt
1. Provide technical guidance to projects
2. Communicate with C- Level Executives
3. Drive training needs
1 - 500
Black Belt
1. Lead enterprise wide projects
2. Handle obstacles in projects
3. Provide Green Belt training programs
1 – 250
Green Belt
Complete projects by devoting < 50% business time
1-50
23
Six Sigma: Challenges and Misconception
Here is a close look at some misconceptions about Six Sigma:
It is just for manufacturing.
Proper implementation needs a statistical genius.
Six Sigma needs heavy investment on resources and systems.
It can be used only to handle big projects.
It can be done part time.
It needs only a clear understanding of statistical packages.
It can be used to solve day-to-day problems in processes.
24
Overview of Six Sigma: Challenges and Misconception
Here is a close look at some misconceptions about Six Sigma, and some challenges to Six Sigma
deployments:
1.Stakeholder support
Six Sigma initiatives are top-down initiatives. It needs to be driven by the top leadership. Employees in a
company can talk about Six Sigma deployments only when the top leadership supports it.
Yet, in a lot of instances, such support has waned over a period of time. Reasons for stakeholder support
declining are as below:
• Lack of identification of strategic projects
• Lack of continued training programs
• Lack of completion of strategic projects
• Lack of involvement during project execution
Points a-d leading to poor ROI from the Six Sigma deployment strategy.
25
Overview of Six Sigma: Challenges and Misconception
Here is a close look at some challenges to Six Sigma deployments:
2. Measurement systems
Six Sigma deployments are fed on regular doses of data. An incapable measurement system leads
to bad data.
Bad data often leads to bad decisions.
Every project should include a complete Measurement Systems Analysis activity to ensure
credibility of the measurement system.
3. Analysis Paralysis
Analyzing a piece of data is good. But spending hours and hours and using variety of tools to extract
some piece of information will lead to the “Analysis Paralysis” syndrome.
26
Overview of Six Sigma: Challenges and Misconception
Here is a close look at some challenges to Six Sigma deployments:
4. Communication
Agreed that Six Sigma is a top-down strategic deployment but it will be the process resources
who would decide the fate of the deployment.
Resistance from Level 1 and Level 2 employees arises only when the purpose of a Six Sigma
deployment is not communicated well.
Top Level Leadership must communicate right down to levels 1 and 2 on the need for doing Six Sigma
deployments. This will take care of all possible challenges like:
Not enough strategic impact projects
Delayed timelines for project execution
Waning support from workforce
27
Six Sigma: Summary
• Six Sigma is an amalgamation of Lean (Waste elimination) and Six Sigma (Variation reduction).
• Six Sigma approaches are deployed through projects supported by top leadership.
• Enough investment needs to be made on the PPT model before companies adopt Six Sigma
deployments approach.
• Six Sigma is not for the weak hearted.
• Successful Six Sigma implementations need good measurement systems.
• Six Sigma can be applied to most disciplines with an industry and most business units within an
organization.
• Financial results are the only way how a project’s success is measured.
• Stakeholder Support, Measurement Systems, Excess Analysis and Poor communication are challenges to
successful Sigma implementations.
28
Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Measure
Analyze
Improve
Control
Activities
Review Project Charter
Validate Problem Statement
and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Value Stream Map for Deeper
Understanding and Focus
Identify Key Input, Process and
Output Metrics
Develop Operational Definitions
Develop Data Collection Plan
Collect Baseline Data
Determine Process Capability
Complete Measure Gate
Develop Potential Solutions
Evaluate, Select, and Optimize
Best Solutions
Develop ‘To-Be’ Value Stream
Map(s)
Develop and Implement Pilot
Solution
Confirm Attainment of Project
Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Implement Mistake Proofing
Develop SOP’s, Training Plan
& Process Controls
Identify Project Replication
Opportunities
Complete Control Gate
Transition Project to Process
Owner
Identify and Implement Quick Improvements
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Effective Meeting Tools
Time Lines, Milestones,
and Gantt Charting
Identify Potential Root
Causes
Reduce List of Potential
Root Causes
Confirm Root Cause to
Output Relationship
Prioritize Root Causes
Complete Analyze Gate
Value Stream Mapping
Value of Speed (Process Cycle
Efficiency / Little’s Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control Tools
Team Feedback Session
29
Module
2
Introduction to Define
30
Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Measure
Analyze
Improve
Control
Activities
Review Project Charter
Validate Problem
Statement
and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication
Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Time Lines, Milestones,
and Gantt Charting
Value Stream Map for Deeper
Understanding and Focus
Identify Key Input, Process and
Output Metrics
Develop Operational
Definitions
Develop Data Collection Plan
Collect Baseline Data
Determine Process Capability
Complete Measure Gate
Identify Potential
Root Causes
Reduce List of
Potential Root Causes
Confirm Root Cause
to Output
Relationship
Prioritize Root Causes
Complete Analyze
Gate
Develop Potential Solutions
Evaluate, Select, and
Optimize Best Solutions
Develop ‘To-Be’ Value
Stream Map(s)
Develop and Implement
Pilot Solution
Confirm Attainment of
Project Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Implement Mistake
Proofing
Develop SOP’s, Training
Plan & Process Controls
Identify Project
Replication Opportunities
Complete Control Gate
Transition Project to
Process Owner
Identify and Implement Quick Improvements
Value Stream Mapping
Value of Speed (Process
Cycle Efficiency / Little’s
Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control
Tools
Team Feedback Session
31
Define Phase
Key Objective: Define the Project
Key Deliverables: Completed Project Charter & High Level Process Map
Roadmap of the Define Phase:
1. Alignment: Make sure that project leader & project sponsor are in alignment with the
business strategic imperatives, scope, improvement goals, timeline and estimated benefits.
All these details should be put in the project charter
2. Team launch: A project team should be chosen & launched formally.
3. SIPOC: High Level Process Map should be prepared with all team members
4. Toll Gate Review: Toll gate review to be conducted with Sponsor, Black Belt & Project leader
32
Define Phase – Y is a function of X’s (multiple inputs impacting output)
Y=f(X) : In this equation X represents the input of the process and Y the output of the process
and f the function of the variable X.
Y is the dependent output variable of a process. It is used to monitor a process to see if it is
out of control, or if symptoms are developing within a process. It is a function of the Xs that
contribute to the process. Once quantified through Design of Experiment, a transfer function
Y=f(X) can be developed to define the relationship of elements and help control a process.
Y is the output measure, such as process cycle time or customer satisfaction. f is the letter
representing “function” (what the value(s) of X(s) does/do for Y (the output). X(s) is/are any
process input(s) (variables) having assigned or inherent values(s) that is/are involved in
producing the output.
For example, if you call your major department store to ask a question, the ability to have your
question answered (Y) is a function (f) of the wait time, the number of people answering the
phones, the time it takes to talk with the representative, the representative‟s knowledge, etc.
All of these X‟s can be defined, measured and improved.
The mathematical term Y = f(x), which translates as simply “Y is a function of x,” illustrates
the idea that the important process outcomes (Ys) are a result of the drivers (x„s) within
processes. The goal of DMAIC is to identify which few process and input variables mainly
influence the process output measures. Each DMAIC phase can therefore be described by
how it contributes to this goal:
•Define: Understand the project Y and how to measure it.
•Measure: Prioritize potential x„s and measure x„s and Y.
•Analyze: Test x–Y relationships and verify/quantify important x„s.
•Improve: Implement solutions to improve Y and address important x„s.
•Control: Monitor important x„s and the Y over time.
33
Develop Project Charter
Business Case
Why is the project worth doing?
Consequence of not doing the project.
Problem Statement
Description of pain
What does not meet the customer’s needs
Goal Statement
Improvement that the team is seeking to accomplish
Scope
What will the team work with on and what is out-of-bounds
Milestone
Project plan with dates
Project team
Project team members
34
Project Charter Sample
35
Project Charter
Project charter is dynamic.
It continues to evolve throughout the project.
It sets a direction and objectives.
It explains why the project is an important investment of time & resources.
After appointment of the champion, members are listed and their roles are defined.
A Black Belt is chosen who clarifies the project rationale with the champion.
It is crucial to describe the project title.
Project title should allow others to understand the purpose of the project at a glance.
36
Project Charter
Major Issues & Objectives of the Project
The actual project
Mention the purpose of the project
Explain why your team would select this project as the problem area
Define the parameters determining the success of the project
37
Project Charter
Major Issues & Objectives of the Project
Stakeholders
Mention the beneficiaries and final outcome
Explain the different goals and objective of various stakeholders
The expected result of the project will influence whom and how
Describe the different sources of resources
Requisite skills and knowledge for the project
Skills Required
1. Analytics
2. Leadership
3. Communication
Potential Team Members
1. Mr. X
2. Ms. Y
3. Mr. Z
38
Project Team
Formation of the team begins with the Black Belt who will lead the team. The leader must have
sufficient training in Six Sigma.
Six Sigma teams must have leadership from two people:
1.The champion or
2.Black/Green Belt, tactical team leader
The team leader selects or helps the champion select other members of the project team.
Team should be cross-functional and familiar with Six Sigma
39
Project Team
A BB is required to be on a project
full time
Team working with the BB should
be small
4, 5 or 6 members
In larger teams, coordination is
difficult
A BB educates team members to
ensure awareness.
The team should include Green
Belts
They should devote at least 25%
of their time to a project.
40
RACI Model
Why Use It
Helpful for team when deciding what their resources needs are
How they will utilize these resources throughout the life-cycle of the project
What Does It do
Provides an overview of all the key stakeholders
Determine which stakeholders are essential for the success during different stages of the project
Identifies the role of each stakeholder
41
RACI Model
Project Phase
Key
Stakeholders
Define
Resource 1
A
Resource 2
R
Resource 3
Measure
Analyze
Improve
Control
I
A,I
I
R
R
R
C
C
C
C
R Responsibility – People who are expected to actively participate as much as possible
A Accountability– Person who is ultimately responsible for the results
C Consultation – People who are to be consulted, experts
I Inform
– People whom the decision will affect
42
Identifying Customers
Who are the customers?
This question is the vital first step in any Six Sigma Project.
Team should begin the project by identifying all customers.
External
• Suppliers
• Distributors
• Retailer
Internal
• Manager
• Finance Department Head
• Sr. Executive
43
Identifying VOC
Description:
The Voice of the Customer (VOC) are the customer specifications. This can include variable data such as
the:
Lower Specification Limit (LSL)Upper Specification Limit (USL)Target Value (or Nominal Value)
The customer may specify only one specification limit and the target value is not necessarily the
midpoint of the specifications. Don't assume this value, ask the customer for the target value if one
exists.
The VOC may also involve attribute specifications such as a "number of ...", color type, or PPM rating.
IMPORTANT:
The VOC provides specification limits (LSL. USL). This is NOT the same as the VOP which provides the
control limits (LCL, UCL). The VOP describes the width of the data and can change with every new data
point, in other words the LCL and UCL are formulae whose values are changing to describe the process
behavior. The specification limits (VOC) are constants, unless the customer informs of a change.
The VOC will be referenced and verified throughout the project and ultimately at the closing of the
project and hand-off to the Process Owner.
44
Identifying VOC
Sources of the Voice of the Customer are:
Surveys
Past complaints
Service issues
Quality issues
Delivery issues
Customer scorecards
Marketing research
Data studies of patterns and trends
Audits
Past decision behavior and tendencies
Technology research
Focus Groups
Interviews
Customer needs, wishes, desires, mandates, attitudes are dynamic. Keeping up with trends and
predicting behaviors separates the best and better products, processes, and services. Although it is
very important for any Six Sigma project, it is especially important when developing an
unprecedented product or process in a DFSS project. The more that can be obtained the better. Be
cautious on the approach and strategy, delicately balancing the team's desire to obtain all possible
information without annoying the customer, leaking a potential competitive edge, or tying up to
many resources.
45
Identify Project CTQ
Sources of Existing Customer Data
Customer
Surveys
Complaints
Executive Level
Discussions
Benchmarking
Data
Key Tool : VOC
Surveys
Focus Groups
Interviews
(+)
Low Cost, Fast
Excellent for CTQ
Definition
Can tackle complex
Issues
(-)
Low Response Rate
Difficult to Generalize
Required Trained
Resources
If we can measure it, we can develop strategies to meet customer needs
46
Identify Project CTQ
Who is the customer?
Who does he/she
think is critical to
quality?
Five Basic
Questions
Who speaks for the
customer?
Who can help define the
issues?
Who are the processes
involved?
What does the customer think is critical to quality?
47
Establishing VOC to CTQ
Description:
• The CTQ linkage is a graphical depiction to show a clear link to the needs that are critical to quality from
the perception of the customer. The chart begins with the most elementary needs and more levels are
added as needed and exact metrics are not necessary at this time.
• The CTQ breaks down customer requirements into quantified requirements. This may include targets and
upper and lower specification limits.
• The customer is also the company you work for. Including their requirements (ROI, cash, time schedule) is
also important. Below is a very basic form of a CTQ Flow-down.
Causes are “X”, Output is “Y”
48
Scope of the Project
Project scope/definition is the boundary
within which the Six Sigma team works.
Suggestions for understanding the scope of Six
Sigma Projects:
It ensures that the team focuses on the
Biggest Problem, Best Opportunity.
Check other projects affecting the project
being scoped.
Determine scope properly and achieve 70% of
benefits rather than chase after 100% of
benefits and then fail.
Clarify project expectations.
Improper scope can undermine a project and
even make it fail.
Larger scope should be divided into smaller
and realistic scope.
Focus on finances.
Keep time in mind.
Keep the project from crossing boundaries.
49
Process Mapping
Process Mapping : Step
Y= f (X1……XN)
STEP
X’s
Inputs to the process
Information
Part
Resources
Y’s
Outputs to the process
Metrics to track : (Defect Rate = DPU), Cycle Time
Key Questions that must be answered:
Why do you do this step?
How do you know it is good?
50
High Level Process Mapping
Thinking
Flow
Requirements
S
Suppliers
Requirements
I
Inputs
Measures
P
Processes
O
Outputs
C
Customers
Measures
Process
Map
51
Project Metrics
Selection of project metrics is a crucial element of the project charter.
It reflects the Voice of Customers (VOC) & Voice of Business (VOB).
Metrics are according to any of the three dimensions
Critical to
Scope/Quali
ty
(CTQ)
Critical to
Delivery
(CTD)
Critical to
Price
(CTD)
•
•
•
•
Mission
Goals
Objectives
Unstated Needs
Metrics should be simple,
straightforward,
meaningful, easily
understandable.
52
Business Case
Purpose of developing a business case is to identify:
Potential benefits of committing time & resources to project.
Types of Business Case
Directly impacts income
statement/cash flow
statement
Number
1
It avoids expense or
investment due to
expected events in future
Number
3
Number
2
Imports the balance sheet
(Working Capital)
Number
4
Risk management projects
that prevent unpredictable
events
53
Obtain Approval for the Project
The BB & the champion should present—
Project Charter
Business Case
Preliminary Project Plan
Request for Financial Support
Request for reviewing and approval
If the project is approved and resources are allocated, the team continues through Define Phase.
If not, the executive team asks the BB/champion to rework the charter.
The focus of the meeting should be to help the members of executive team learn from the findings
reported by project team.
The project team will prepare a final report on the lessons learnt when it completes a project.
54
Project Plan
The BB, MBB and the Champion develop the preliminary project plan into a
detailed project plan.
Project plan structures the project intoSteps
Schedules milestones
Deliverables
Where the
information will be
Goals for the five phases
kept for referenceFile, Intranet, Cabinet
Who will be
communicating itBB, Experts,
Champions
What is to be
communicatedMinutes of team
meetings, Project
Time Line
How it will be
communicatedMemo, E-mail, Call,
Presentation
When it will be
communicatedDates, Timings,
Frequency
To whom it will be
communicatedStakeholders, Team
Members
55
Cost of Poor Quality
Cost of poor quality (COPQ) or poor quality costs (PQC), are costs that would disappear if systems,
processes, and products were perfect. COPQ was popularized by IBMquality expert H. James Harrington in his
1987 book Poor Quality Costs.
56
Pareto Analysis
Pareto Analysis is a statistical technique in decision-making used for the selection of a limited number of tasks that
produce significant overall effect. It uses the Pareto Principle (also known as the 80/20 rule) the idea that by doing
20% of the work you can generate 80% of the benefit of doing the entire job.
57
Six Sigma Metrics
Note: Parts per Million (PPM)
PPM counts the quantity of defective parts per million parts
produced. As noted above, it does not account for the fact that
multiple defects may affect a single part. One defective part,
even with multiple defects, counts as a single defective among
other defectives in the population. As with DPMO, it uses
1,000,000 as a constant, regardless of the actual number of
parts produced. The formula is:
Example Used Above:
D = # defects (14)
TOP = total # of failure opportunities (40)
O = # defect opportunities (4)
DPU = defects per unit (1.4)
U = # units (10)
58
Six Sigma Metrics – Continued….
First Pass Yield (FPY), or Throughput Yield (TPY), and First Time Yield (FTY), Rolled Throughput Yield (RTY)
RTY= (Y1) (Y2) (Y3) (Y4) … (Yn) where Y is the yield
(proportion good) for each step
For example, a four-step process has a yield of 0.98 in step
1, 0.95 in step 2, 0.90 in step 3, and 0.80 in step 4.
RTY = (0.98)(0.95)(0.90)(0.80) = 0.67032
Example Used Above:
D = # defects (14)
TOP = total # of failure opportunities (40)
O = # defect opportunities (4)
DPU = defects per unit (1.4)
U = # units (10)
Defectives Found - 4
59
Expectations from the Define Phase
The project team has been identified, representing the key stakeholders
A project plan has been created, with some detail around the Define and Measure phases
The project team has been launched, with clear expectations for all members
All aspects of the Project Charter have been validated, including:
• The benefit types and quantities are realistic
• The Opportunity/Problem Statement clearly identifies the process performance metrics
(the Y’s) for the project
• The Goal Statement focuses on the performance metrics (the Y’s) detailed in the
Opportunity/Problem statement, and the goals are realistic
60
Expectations from the Define Phase
Requirements Gathering, to validate the Y’s, has been completed to validate the Problem
Statement and the Goal Statement
A high-level process map, a SIPOC map and possibly a value-stream map have been completed
A Stakeholder Analysis and Communication plan have been completed
Project risks have been identified and a Risk Management Plan put in place
61
DEFINE PHASE - Check List of Toll Gate Review Questions
MAIN OBJECTIVE: Define the Project
REQUIRED DELIVERABLES: Project Charter, SIPOC
TOLL GATE QUESTIONS:
Does the Problem Statement detail the problem, when and where the pain occurs?
Does a Goal Statement define the metric(s) to improve? Does the improvement target seem
achievable?
Are the Project Scope and Time Line reasonable? Have constraints and key assumptions been
identified?
Does the expected Business Impact (once the improvement target has been reached or
exceeded) still justify the project?
Have the customers been identified? What are their requirements? Are they measurable?
How were the customer requirements determined?
Who is on the team? Do they all understand the elements of the Project Charter?
62
DEFINE PHASE - Check List of Toll Gate Review Questions
Who are the key stakeholders? How will they be involved in the project? How will progress be
communicated to them?
What are the potential barriers/obstacles to success? How are they being addressed?
TOOLS AND METHODOLOGIES TYPICALLY APPLIED:
SIPOC
VOC Techniques
Stakeholder Analysis
Communication Plan
Project Plan
63
Module
3
Introduction to Measure
64
Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Activities
Review Project Charter
Validate Problem
Statement
and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication
Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Measure
Value Stream Map for
Deeper Understanding and
Focus
Identify Key Input, Process
and Output Metrics
Develop Operational
Definitions
Develop Data Collection
Plan
Collect Baseline Data
Determine Process
Capability
Complete Measure Gate
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Effective Meeting
Tools
Time Lines, Milestones,
and Gantt Charting
Analyze
Identify Potential
Root Causes
Reduce List of
Potential Root Causes
Confirm Root Cause
to Output
Relationship
Prioritize Root Causes
Complete Analyze
Gate
Improve
Develop Potential Solutions
Evaluate, Select, and
Optimize Best Solutions
Develop ‘To-Be’ Value
Stream Map(s)
Develop and Implement
Pilot Solution
Confirm Attainment of
Project Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Control
Implement Mistake
Proofing
Develop SOP’s, Training
Plan & Process Controls
Identify Project
Replication Opportunities
Complete Control Gate
Transition Project to
Process Owner
Identify and Implement Quick Improvements
Value Stream Mapping
Value of Speed (Process
Cycle Efficiency / Little’s
Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control
Tools
Team Feedback Session
65
Measure Phase
Key Objective: Process Baseline
Key Deliverables: Data Collection Plan, Process Baseline
Roadmap of the Measure Phase:
1. Data Collection Plan: Ensure accurate operational definitions of process metrics & sampling
plan
2. Measurement System Analysis: Check if the measurement system is reliable & stable
3. Process Baseline: Calculate process baseline based on historical data
4. Process Capability: Calculate process capability (Cp/Cpk, DPMO)
5. Toll Gate Review: Toll gate review to be conducted with Sponsor, Black Belt & Project leader
66
Plan For Data Collection
1
Establish
Data Collection
Goals
Clarify purpose
of data
collection
2
Develop
Operational
Definitions And
Procedures
Write and pilot
operational
definitions
3
Ensure Data
Consistency
And Stability
Through
measurement
systems
4
Collect Data
And Monitor
Consistency
Train data
collectors
Collect data
Identify what
data to collect
Develop and
pilot data
collection forms
and procedures
Check for data
accuracy and
consistency
Establish a
sampling plan
67
Types of Data
Data Classification
Discrete/Attribute
Data that can be categorized into a fixed
number of classes
That comes mostly in the form of choices
as yes / no, ok / not ok (finite)
That cannot be measured but can be
categorized (Countable)
E.g.: No of pre-release errors, Pass/Fail;
Yes/No; Performance metrics – A, B, C & D,
lines of code in a module of ‘n’ lines.
Continuous/Variable
Data that can be categorized into infinite
number of classes
That can assume any value between two
given values (Infinite)
That can be measured using some
equipment or otherwise (Measurable)
E.g.: Time taken for loading a page,
response time, memory utilization, effort
expended, delivery time, years of
experience, CPU utilization, cost of rework.
68
Types of Data
Attribute
(aka
categorized
discrete data)
Nominal
Ordinal
Interval
Continuous
(aka variable
data)
Ratio
Categorical data where the order of the categories is
arbitrary – No natural ordering
Examples
Defect types; Dept A, B, C; Labor types; Languages; design review method;
Estimation method - Usage of scientific size model like FP,CP, Test case points and
Others- 1
Nominal data with a natural ordering
Examples : Severity levels, performance levels – excellent, very good, good, bad;
Experience categories, CSAT Levels - >5 and <5, Risk associated with penalty clause High - 0, Medium/Low – 1; Engineering tools adoption level - Binary Measure: 1 Level 3 and above and 0 - Less than level 3
Continuous data that has only one continuous measure divided into equal intervals;
may have decimal values
E.g.: effort (PH), Time taken for loading a page
It is an Interval data set that is a derived measure (having one or more continuous
data set)
Examples : Defect densities, Labor rates, Productivity, Variance %’s, EDR, Teams’
Average Experience
69
Types of Data
Discrete Data (Attribute data)
 Can only take on certain fixed values (e.g. number of family
members, OK/broken, number of correct/wrong)
 Requires a large set of data to be analyzed
OK
Not Ok
70
Types of Data
Continuous Data (Variable data)
 Can take on any value (e.g. time, volume, weight,….)
 Requires a smaller set of data to be analyzed
Height
1.85 M
1.75 M
1.60 M
Weight
85 KG
70 KG
55 KG
Age
30 Years
25 Years
20 Years
71
Types of Data - Example
Measurements of dimension of a gap. The example contains 10 measurements. The upper
tolerance limit is 45mm. The measurements have to be below this limit to be ok.
Measurements 10pc (mm)
1 NOT OK out of 10 = 10% defect rate
Variable data
42.2
33.1
40.1
43.0
47.5
41.2
35.7
39.3
44.2
44.9
Attribute data
OK
OK
OK
OK
NOT OK
OK
OK
OK
OK
OK
72
Types of Data
Data : The foundation of Six Sigma methodology
Workout(Solution)
Continuous Data
Discrete Data
Problem / Issue
Continuous Data : A data which uses a measurement scale as well as
inches or time.
☞ Contains more information than discrete data.
Discrete Data : A data which is based on information such as
pass/fail.
☞ Can’t be more specific
Fire Alarm
73
Types of Data
Exercise
A Yellow Belt at Nuts & Bolts Inc. reviews the waiting time for 10 randomly chosen units that
are waiting to be processed in the next operation in the production flow.
The measurements are as follows (seconds) : 07,26,17,26,43,47,26,66,24 & 48
What type of data does this set of measurements contain?
If the tolerance limits for the waiting period is 0 – 30 Sec, what will the yield be?
What type of data is the calculated defect rate?
Time : 5 minutes
74
Types of Data
Questions on types of data :
What type of data does this set of measurements contain?
1 incorrect out of 10, 10% defect rate?
What type of data is the calculated defect rate?
Age of people at an office: 45, 23, 32, 33, 25, 61, 44, 40, 21, 30 & 33?
What type of data is this?
A list of height and weight of all boys in eight grade?
75
Data Collection
Common Cause Variation
• Common Cause Variation is the variation present in every process. Also known as
white noise.
• It is not controllable variation within the existing technology.
• Represents the best the process can be with the present technology(Inherent
process capability).
Assignable Cause Variation
• Assignable Cause Variation represents the outside influences on a process that
cause average to shift and drift. Also known as special cause.
• It is potentially controllable variation with the existing process technology.
• It represents how the process is actually performing over time(Sustained process
capability).
76
Data Collection
Example
Mixed lots of parts are currently loaded onto trailers at a supplier for shipment to the factory.
Part number and count are entered into the factory computer system manually.
Excessive variation exists between what shows in the factory computer and what is actually unloaded at
receiving because of errors in transcribing part numbers on the packing cartons. In order to reduce the
variation in this process, minimize manual processing of shipping/receiving tickers.
Example
A part is currently manufactured using a die-casting process. The internal diameter is a CTQ
dimension with a tolerance of 3±0.002.
A die casting process, by its nature, cannot accommodate this small tolerance band, and variation is
excessive(poor short-term and long-term capability).The basic technology(die casting) isn’t good
enough! The inherent capability(Z.st) isn’t sufficient. Possibly use a machining process instead...
77
Data Collection
Short Term Data
Product
Unit
Production sequence
Long Term Process
•••••••••••••••••••••••••••••••••••
Sampling size n= 5
g
n
S S
j =1i=1
2
g
2
(Xij - X) = nS (X j - X) +
Total
Total variation
j=1
Between
Assignable Cause
Variation
g
n
S S
(X ij - X j) 2
j =1i =1
Within
Common Cause
Variation
Whatever business sector, production field may be, assignable cause variation and common
cause variation are all included in the data which is obtained through the long term.
78
Data Collection- Population & Sampling
Sampling is the process of
Collecting only a portion of the data that is available or could be available, and drawing conclusions about
the total population (Statistical Inference)
Population
Sample
N = 50,000
n = 100
Population is 50,000
movie goers of New Delhi
From the sample, we infer that the average time
in the ticket queue(y) is 22mins
79
Sampling Methods
A big problem when trying to collect certain types of information (e.g. people & conditions) might be
that there are enormous quantities of information. It might be impossible to measure everything!
Imagine if all opinion polls concerning which political party is the biggest would have to ask
every citizen in the country – with the right to vote – every time.
What if the incoming inspection department had to measure the dimension of all incoming
material. How effective would that be?
In order to make such measurement situations easier it is possible to use Sampling or Random
Samples.
80
Sampling Methods/Strategies
The big pitfall in sampling is “bias” – i.e., select a sample that does NOT really represent the whole.
The sampling plan needs to guard against bias. Different methods of sampling have different
advantages and disadvantages in managing bias.
Judgment
As it sounds – selecting a sample based on someone’s knowledge of the process, assuming that it
will be “representative.” Judgment guarantees a bias, and should be avoided.
Convenience
Also just like it sounds – sampling those items or at those times when it’s easier to gather the
data. (For example, taking data from people you know, or when you go for coffee.) This is
another common (but ill-advised) approach.
81
Sampling Strategies
Best Methods for Six Sigma Data:
Random
Best approach for Population situations. Use a random number table or random function in
Excel or other software, or draw numbers from a hat.
Systematic
Most practical and unbiased in a Process situation. “Systematic” means that we select every
nth unit, or take samples at specific times of the day. The risk of bias comes when the timing of
the sample matches a pattern in the process.
82
Numerical Data Properties
Central Tendency
(Location)
Variation
(Dispersion)
Shape
83
Numerical Data Properties & Measure
Numerical Data
Properties
Central
Tendency
Variation
Mean
Range
Median
Variance
Mode
Standard Deviation
Shape
Skew
84
Numerical Data Properties & Measure
Numerical Data
Properties
Central
Tendency
Mean
Variation
Shape
Median
Range
Variance
Mode
Standard Deviation
Skew
85
Mean
Measure of Central Tendency
Most Common Measure
Acts as ‘Balance Point’
Affected by Extreme Values (‘Outliers’)
Formula (Sample Mean)
Sum of all data ( Xi )
Number of data (n)
n
X
Xi

i 1

n
X1  X2  Xn

n
86
Mean - Example
Raw Data:
X

10.3
10.3
4.9
8.9
11.7
6.3
7.7
 4.9  8.9  11.7  6.3  7.7
6
 8.30
87
Numerical Data Properties & Measures
Numerical Data
Properties
Central
Tendency
Variation
Mean
Range
Median
Variance
Mode
Standard Deviation
Shape
Skew
88
Median
Measure of Central Tendency
Middle Value In Ordered Sequence
If Odd n, Middle Value of Sequence
If Even n, Average of 2 Middle Values
Position of Median in Sequence
Not Affected by Extreme Values
Positioning Point

n 1
2
89
Median Example Odd-Sized Sample
•
Raw Data:
Position:
24.1
22.6
21.5
23.7
22.6
1
2
3
4
5
5
+1
n
+1
Positioning Point 

3
2
2
Median = 22.6
90
Numerical Data Properties & Measures
Numerical Data
Properties
Central
Tendency
Variation
Shape
Median
Range
Variance
Mode
Standard Deviation
Mean
Skew
91
Mode
Measure of Central Tendency
Value That Occurs Most Often
Not Affected by Extreme Values
May Be No Mode or Several Modes
May Be Used for Numerical & Categorical Data
92
Mode Example
No Mode
Raw Data:
10.3
4.9
8.9
11.7
6.3
7.7
One Mode
Raw Data:
6.3
4.9
8.9
6.3
4.9
4.9
More Than 1 Mode
Raw Data:
21
28
28
41
43
43
93
Thinking Challenge
You’re a financial analyst. You have collected the following closing stock prices of new stock
issues: 17, 16, 21, 18, 13, 16, 12, 11.
Describe the stock prices in terms of central tendency.
94
Central Tendency Solution
•
Mean
X 

X
1
 X
2
   X
8
8
17  16  21  18  13  16  12  11
8
 15 . 5
95
Central Tendency Solution
Median
Raw Data:
Ordered:
Position:
17
11
1
Positioning
Median
16
12
2
Point

16  16
2
21
13
3

18
16
4
n 1
2
13
16
5

16
17
6
8 1
2
12
18
7
11
21
8
 4 .5
 16
96
Central Tendency Solution
Mode
Raw Data:
Ordered:
17
11
16
12
21
13
18
16
13
16
16
17
12
18
11
21
97
Summary of Central Tendency Measures
Measure
Mean
Median
Mode
Equation
X i / n
(n+1) Position
2
none
Description
Balance Point
Middle Value
When Ordered
Most Frequent
98
Numerical Data Properties & Measures
Numerical Data
Properties
Central
Tendency
Variation
Shape
Mean
Range
Median
Variance
Mode
Standard Deviation
Skew
99
Range
Measure of Dispersion
Difference Between Largest & Smallest Observations
Ignores How Data Are Distributed
Range  X largest  X smallest
7 8 9 10
7 8 9 10
100
Range
Range :
Is a measure of spread and it is calculated by subtracting the smallest number from the largest.
Ex) 4, 5, 7, 11, 14, 14, 15
Range = max – min = 15 – 4 = 11
101
Numerical Data Properties & Measures
Numerical Data
Properties
Central
Tendency
Variation
Mean
Range
Median
Variance
Mode
Shape
Skew
Standard Deviation
102
Standard Deviation
Measures of Dispersion
Most Common Measures
Consider How Data Are Distributed
Show Variation About Mean (X or )
X = 8.3
4 6
8
10 12
103
Standard Deviation
Standard deviation :
The average of the distances between the observations and the mean…
time (sec)
8
7
6
5
4
4.4
Mean
x
3
2
1
Observation
Standard deviation has the same dimension as the measurements (e.g., mm, seconds, kg)
104
Standard Deviation
Standard deviation :
Commonly used measurements for spread represented by σ and calculated by the formula :
σ
=√
( X1 – X)2 + (X2 – X)2 + …+ ( Xn - X)2
n-1
 Where X = mean
 X1, X2 …. = the values in our group of data
 n = the number of values in our group of data
 Other denotations for the standard deviation is s and Sigma
105
Standard Deviation
Standard deviation :
Ex.
1, 2, 3, 4, 5
s=
=
√(-2)
2
√
X
( 1– 3)2 + (2 – 3)2 + (3-3)2 + (4-3)2 + (5-3)2
5-1
√
4+1+0+1+4
=
+ (-1)2 + (0)2 + (1)2 + (2)2
4
4
=
√
10 / 4
=3
=
√ 2.5
=
1.58
106
Standard Deviation
We always strive to have as low standard deviation as possible!
µ
σ
107
Case Study – Basic Statistics
A Swedish long distance runner has competed in 15 marathons in the last three years (see matrix
below)
a) Calculate the average time it took to run the five marathons in 2002, 2003 and 2004
b) Calculate the median for how long time it look to run marathon for each year
c) Calculate the range for each year
d) Calculate the standard deviation for each year
Time : 20 minutes
108
Case Study – Basic Statistics
(Minutes)
2002
2003
2004
New York
140
138
135
Stockholm
145
142
136
London
155
145
134
Boston
160
145
135
Sydney
150
240
140
Extra :
1.Calculate the average time it has taken to run all 15 marathons during 2002-2004
2.Calculate the average median for how long time it has taken to run all 15 marathons during 2002-2004
3.Calculate the range for all 15 marathons that the runner ran during 2002-2004
4.Calculate the standard deviation for the total number of marathons during 2002-2004
109
Standard Notation
Measure
Sample
Population
Mean
X

Stand. Dev.
S

Variance
S
Size
n
2

2
N
110
Calculating DPMO …
Calculate Defects per Unit (DPU) :
Total # of Defects
DPU
=
Total # of Units Produced
Calculate Defects per Opportunity (DPO) :
DPU
DPO
=
# of Opportunities for Error in One Unit
Go to a Sigma Chart and
Estimate the Sigma Level
Calculate Defects per Million Opportunities (DPMO) :
DPU x 1,000,000
DPMO =
# of Opportunities for Error in One Unit
111
Different types of Yield
100
Process A
Input
Yield 3
Yield 2
Yield 1
Process B
Process C
91
82
70
Process D
( Testing/ FI )
Loss 1
Loss 2
Loss 3
Rejects
9
9
12
5
First Time Yield YFT
Units Passed
=
Units Tested
Rolled Throughput Yield YTP
=
=
65
70
Pass
65
= 0.93
P (0) = e-DPU
Probability of Zero defects = (Yield 1) X (Yield 2) X (Yield 3) …..
= (91/100) X (82/91) X (70/82) X (65/70)
= 0.65
112
Graphical Analysis
What is Process Capability ?
A capability of a process is defined as the inherent variability of a process in the absence of any undesirable
special causes and the variability is solely due to common causes.
Short and Long-term Capability Studies
A short-term capability study covers a relatively short period of time (Hours, Days) consisting of
approximately 30 to 50 data points.
A Long-term capability study covers a relatively long period of time (Weeks, Months) consisting of
approximately 100 to 200 data points (covering all sources of variation).
113
VSM – Value Stream Map
Value stream mapping is a lean-management method for analyzing the current state and designing a
future state for the series of events that take a product or service from its beginning through to the
customer. At Toyota, it is known as "material and information flow mapping".[1] It can be applied to
nearly any value chain.
114
115
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
116
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
Measurement
A manufacturer wants to know whether a
thermometer provides accurate and consistent
202.7
measurements at five heat settings: 202°,
202.5
204°, 206°, 208°, and 210°. Six measurements
203.2
are taken at each setting. To determine
whether the thermometer is biased, subtract
203.0
the individual measurements from the reference
203.1
value. The bias values for measurements taken
203.3
at heat setting 202° are calculated in this
table.
Actual
Bias
-
202
=
0.7
-
202
=
0.5
-
202
=
1.2
-
202
=
1.0
-
202
=
1.1
-
202
=
1.3
The temperature measurements at the 202° heat
setting are positively biased. The thermometer gives
measurements that are higher than the actual
temperature.
To interpret the linearity of the thermometer data,
determine whether the bias of the thermometer
changes across the heat settings. If the data do not
form a horizontal line on a scatterplot, linearity is
present.
• Attribute & Discrete Capability
• Monitoring Techniques
Bias : Bias examines the difference between the observed average measurement and a reference value.
Bias indicates how accurate the gage is when compared to a reference value.
Linearity : Linearity examines how accurate your measurements are through the expected range of the
measurements. Linearity indicates whether the gage has the same accuracy across all reference values.
117
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
118
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
•A gage R&R study helps you investigate: Whether
your measurement system variability is small
compared with the process variability.
•How much variability in the measurement system is
caused by differences between operators.
•Whether your measurement system is capable of
discriminating between different parts.
For example, several operators measure the diameter
of screws to ensure that they meet specifications.
A gage R&R study (Stat > Quality Tools > Gage
Study) indicates whether the inspectors are
consistent in their measurements of the same part
(repeatability) and whether the variation between
inspectors is consistent (reproducibility).
• Monitoring Techniques
119
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
Should I use a crossed, nested, or expanded gage R&R study?
Use the gage R&R study that is designed for the type and number of factors that
you have.
Crossed gage R&R study
A study in which each operator measures each part. This study is
called crossed because the same parts are measured by each operator
multiple times. To perform a crossed gage R&R study in Minitab,
choose Stat >Quality Tools > Gage Study > Gage Study (Crossed).
Often, you will use a crossed gage R&R study to determine how much of your process
variation is due to measurement system variation.
Nested gage R&R study
A study in which only one operator measures each part, usually because the test
destroys the part. This study is called nested because one or more factors
is nested under another factor and, thus, not crossed with the other
factors.
To
perform
a
nested
gage
R&R
study
in
Minitab,
choose Stat > Quality Tools > Gage Study > Gage Study (Nested).
Expanded gage R&R study
A study in which one or more of the following conditions exists:
• More than two factors, usually, operator, gage, and part
• Fixed or random factors
• Both crossed and nested factors
• An unbalanced design
• Monitoring Techniques
120
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
121
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
122
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
123
MSA- Measurement System Analysis
• Precision & Accuracy
• Bias, Linearity & Stability
• Gage Repeatability & Reproducibility
• Variable & Attribute MSA
• Process Capability
• Capability Analysis
• Concept of Stability
• Attribute & Discrete Capability
• Monitoring Techniques
124
MEASURE PHASE - Check List of Toll Gate Review Questions
MAIN OBJECTIVE: Establish the current performance baseline
REQUIRED DELIVERABLES: Value-Stream Map, Data Collection Plan, Performance Baseline
TOLL GATE QUESTIONS:
Has the Project Charter been updated?
Has performance data been gathered according to a documented Collection Plan
Has an appropriate sample size and sampling frequency been established to ensure valid
representation of the process we’re measuring?
Has baseline performance been established (Process metric, Sigma level, etc…)?
How large is the gap between current performance and the customer requirements?
Are there any perceived barriers to success?
TOOLS AND METHODOLOGIES TYPICALLY APPLIED:
Data Collection Plan
Process Baseline
125
Module
4
Introduction to Analyze
126
Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Measure
Analyze
Improve
Control
Activities
Review Project Charter
Validate Problem
Statement
and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication
Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Effective Meeting
Tools
Time Lines, Milestones,
and Gantt Charting
Value Stream Map for Deeper
Understanding and Focus
Identify Key Input, Process and
Output Metrics
Develop Operational
Definitions
Develop Data Collection Plan
Collect Baseline Data
Determine Process Capability
Complete Measure Gate
Identify Potential
Root Causes
Reduce List of
Potential Root Causes
Confirm Root Cause
to Output
Relationship
Prioritize Root Causes
Complete Analyze
Gate
Develop Potential Solutions
Evaluate, Select, and
Optimize Best Solutions
Develop ‘To-Be’ Value
Stream Map(s)
Develop and Implement
Pilot Solution
Confirm Attainment of
Project Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Implement Mistake
Proofing
Develop SOP’s, Training
Plan & Process Controls
Identify Project
Replication Opportunities
Complete Control Gate
Transition Project to
Process Owner
Identify and Implement Quick Improvements
Value Stream Mapping
Value of Speed (Process
Cycle Efficiency / Little’s
Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control
Tools
Team Feedback Session
127
Optimizing the Project Plan
Once you have created the project plan, verify that it meets the project stakeholders' date, resource, and cost
requirements. If an inconsistency exists between the information in the project plan and the project requirements,
you will be able to identify the source of the problem and define a solution:
– Analyze schedule dates -Evaluate the schedule to ensure that milestone dates and project dates are achieved.
– Analyze resource allocation -Evaluate the resources to ensure that the resources are not overall located.
– Analyze cost budget -Evaluate project costs.
128
Analyze Phase
Key Objective: Validated Root Causes
Key Deliverables: List of potential root causes & validated Root Causes, Cause & Effect matrix
Roadmap of the Analyze Phase:
1.
2.
3.
4.
5.
6.
Identify Potential Root Causes (Xs):
Filter Potential Root Causes: Filter potential root causes using Impact/Control matrix.
Validate Root Causes: Validate root causes using statistical methods
Estimate impact of each ‘X’ on ‘Y’
Prioritize Root Causes: Prioritize root causes using Urgent/Important Matrix
Toll Gate Review: Toll gate review to be conducted with Sponsor, Black Belt & Project leader
129
7 QC Tools
Pareto Chart
Check sheet
Flowchart
Histogram
Scatter Chart
Control Chart
Cause and Effect Diagram
130
7 QC Tools: Pareto Charts
What is a Pareto Chart?
• This is a chart that contains bars and a line graph where the line graph represents cumulative total
of frequencies.
• The bars represent individual frequencies of items like customer complaints etc.
• It uses the 80-20 principle, as per which 80% problems happen due to 20% causes.
• The chart helps you to prioritize between a whole list of problems resulting in it being used widely
as a Prioritization tool.
131
7 QC Tools: Pareto Charts
Step 1
Find out individual % contributions of each complaint and add up cumulative totals as shown below:
132
7 QC Tools: Pareto Charts
Step 2
Hide the Indiv % column as we don’t need it to draw a Pareto Chart and select a 2-D Clustered
Column Chart (Insert  Chart  2D Clustered Column Chart). The chart would appear like the one
shown below:
120
Pareto Chart for complaints
100
80
60
40
20
Frequency
Cumulative %
0
133
7 QC Tools: Pareto Charts
Step 3
Double click on Cumulative %, and change the axis selection to Secondary Axis (Right Click  Format
Data Series  Under Plot Series on, change the radio button to Secondary Axis).
The graph will look like:
120
100
Pareto Chart for complaints
120.00%
100.00%
80
80.00%
60
60.00%
40
40.00%
20
20.00%
0
0.00%
Frequency
Cumulative %
134
7 QC Tools: Pareto Charts
Step 4
Now, right click on Cumulative %  Click on Change Series Chart Type  Select the first option under
Line Chart.
The graph changes to:
120
100
80
60
40
20
0
Pareto Chart for complaints
100.00%
90.00%
80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Frequency
Cumulative %
135
7 QC Tools: Pareto Charts
Step 5 - Interpretation
120
100
80
60
40
20
0
Pareto Chart for complaints
100.00%
90.00%
80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Frequency
Cumulative %
80% of customer complaints are due to “Wait time high”, “Service time high” and “Service
Quality Poor”.
The Operations team must look to fix these problems at the earliest with 20% being Vital Few.
136
7 QC Tools: Check Sheet
What are Check sheets?
• Check sheets are simple data collection templates used in Six Sigma projects.
• At a lot of times, companies may not have all the data needed for the project.
• In such a scenario, the project team designs a check-sheet to capture additional information
needed for the project.
• Note: Companies may design their
own check-sheets and thus,
this template shown below
can differ.
137
7 QC Tools: Flow chart
What are Flow charts?
Flow charts are considered to be basic “process mapping” tools.
Before any process is improved, one needs to know how it flows, what are its inputs etc.
Flow charts can be drawn at many levels – Macro level, Level 2 and Improvement level
A macro-level flow chart is done to showcase the process on how you see it from a bird’s eye view.
A Level 2 flow chart shows how the process actually happens. This is a bit more detailed than the Macrolevel or Level 1 Map.
The Improvement level flowchart contains all the details you need to make informed decisions of your
process and also to identify key pain-points.
The flowchart shows the way how your process is done to help converting the input to output desirable to
the customers.
138
7 QC Tools: Flow chart
139
7 QC Tools: Flow chart
The flowchart has been prepared for a real
life project scenario, where the project team
wished to improve the machine capacity of a
nail manufacturing workshop.
140
7 QC Tools: Histogram
What is a Histogram?
After collecting data, the team would like to know what the data distribution is like.
Understanding the data distribution is essential because it will help them take decisions on the
entire process performance and not just on isolated points.
A Histogram will help in giving an individual the understanding of his data distribution.
It will also tell him if there are any possible special causes acting on his data set, which he needs
to focus on and correct.
How?
We shall use the Analysis Toolpak option in Excel although this can be done fairly easily using
packages like Minitab.
141
7 QC Tools: Histogram
Data
The data for histogram is as shown. This data is collected for wait
times for a bank.
The team desiring to make an improvement to the wait times wants
to see if the wait times are significantly higher in any of the bank
branches or not.
To draw a histogram, the individual needs to know some definitions:
Quartile 1: 1st quartile (25%)
Quartile 3: 3rd quartile (75%)
142
7 QC Tools: Histogram
Step 1
Calculate Min, Max and Quartile values
Step 2
Calculate the next measure of descriptive statistics: IQR. IQR
stands for Interquartile range and is expressed as the
difference between 3rd quartile and 1st quartile. Also write
the count of the data set.
143
7 QC Tools: Histogram
Step 3
Every histogram is drawn on two important bits of
information: Bin size and Number of Bins.
To calculate Bin Size, apply the Freedman Diaconis Rule:
Bin Size = 2 * IQR * (Count) -1/3
Compute number of bins using the formula,
Number of bins = (max – min)/ Bin Size
Number of bins = 2.88 = 3
Step 4
Define the bins. Start with the minimum value as the first
bin and keep adding the bin size until you reach 3 bins.
144
7 QC Tools: Histogram
Step 5
Histogram
Use the Add-in tool provided in Microsoft Excel to draw the
Histogram. The histogram here doesn’t give an accurate
picture, so the bin size and the number of bins need be
changed to make it more granular.
Frequency
20
15
10
5
Frequency
0
10.01
10.35
10.69
More
Bin
Histogram
Step 6
Frequency
Round down the bin size and round up the number of bins,
and re-draw the histogram.
20
15
10
Frequency
5
0
10.01
10.31
10.61
10.91
More
Bin
145
7 QC Tools: Histogram
Step 7
Inference
• The data distribution doesn’t follow a normal distribution.
• The data suffers from a possible bi-modality at 10.31 and 10.91.
• It seems like the data has been collected from two sources.
• If the project team wishes to reduce the wait time, it has to understand the best practices of the
sample that delivers 10.31 and ensure they are cascaded.
146
7 QC Tools: Scatter Charts
What are Scatter Charts?
• In a project done using Six Sigma approaches, there are two kinds of variables:
KPOV (Key Process Output Variable) and KPIV (Key Process Input Variable).
• Using Scatter Charts and an associated technique, Regression Analysis, an individual
can determine the extent of statistical relationship between the two sets of
variables.
• As such, a scatter chart is known as “Relationship determination tool”.
• To draw scatter charts, you would need pairwise and continuous data.
147
7 QC Tools: Scatter Charts
Data
The data is collected for both KPIV and KPOV and
the data table is as shown:
Step 1
KPOV
Wait time
14
12
Click on Insert  Scatter Chart  Choose the first
chart, Scatter with markers. The graph would be
as below:
10
8
KPOV
Wait time
6
4
2
0
0%
5%
10%
15%
20%
148
7 QC Tools: Scatter Charts
Step 2
Click on any point in the graph  Right Click
and choose Add Trendline  Select Linear 
Select “Display R-Square value” and “Display
Equation”.
KPOV
Wait time
14
12
y = 38.444x + 4.3821
R² = 0.9862
10
8
KPOV
Wait time
6
Linear (KPOV
Wait time)
4
The R2 value and the equation mentioned on top of
the line is an auto-calculated feature from Excel. A
statistical formula will help in calculation of these
metrics manually, which will be explained in the
Green Belt or Black Belt Body of Knowledge.
2
0
0%
5%
10%
15%
20%
149
7 QC Tools: Scatter Charts
KPOV
Wait time
14
12
y = 38.444x + 4.3821
R² = 0.9862
10
KPOV
Wait time
8
6
Linear (KPOV
Wait time)
4
2
Interpretation
0
0%
5%
10%
15%
20%
R-Square value is 0.9882, i.e. Coefficient of Determination is 98.82%. This means that 98.82%
variability in Wait time is explained by absenteeism.
If the R-Square value > 64%, you can use the Regression Equation to find optimal value of
Absenteeism that would give the ideal value of Wait time.
For example, for Wait time to 8 minutes, the absenteeism rate should be 9.4%.
150
7 QC Tools: Control Charts
What are Control Charts?
Control Charts are known as Process Behavior Charts.
Project teams use control charts to know if the process is behaving under the influence of special
causes of variation.
Choice of control charts is important because a wrong selection of control charts will give you wrong
inference for the data.
Special causes of variation get highlighted when any data point crosses the 3 Sigma limits from the
mean.
The 3 Sigma limits are known as Control Limits. Every control chart would have 2 Control limits,
known as Upper Control Limit and Lower Control Limit.
The project team has the choice of fixing the control limits if they wish so. As a best practice, project
teams are instructed to let the process data decide the control limits.
151
7 QC Tools: Control Charts
What?
Data type
1. The table below shows which
control chart should be
chosen when:
Continuous
Discrete
Name of chart Conditions
I – MR
Subgroup size = 1
Xbar – R
Subgroup size < 10
Xbar – S
Subgroup size > 10
P
Defectives, varying sample size
Np
Defectives, varying sample size
U
Defects, varying sample size
C
Defects, constant sample size
152
7 QC Tools: Cause and Effect Diagram
What is a Cause and Effect Diagram?
1. A Cause and Effect Diagram is a quality tool that helps the project team understand the possible
causes to an event.
2. This tool was first popularized by Dr. Kaoro Ishikawa.
3. The causes are grouped under logical categories like 6M, 7P, 5S etc.
4. The causes to the event first need to be arrived at by brainstorming.
5. The project team then arranges these causes into the logical categories, as deemed fit.
6. The criticism about Cause and Effect Diagram is that it serves as a good visual representation to the
causes for an event. There is no statistical validation of any of the causes unless the team decides to
support the causes with data, which is outside the realms of the Cause and Effect Diagram.
153
7 QC Tools: Cause and Effect Diagram
An example of Cause and Effect Diagram
154
7 QC Tools: Summary
Pareto Charts are popularly used as a prioritization tool to identify the top 20% reasons that
contribute to 80% customer complaints.
A Check Sheet helps you to collect data in the absence of automated reporting procedures.
Flow charts help you to map the process steps.
A Histogram helps you to understand the shape and the data distribution.
Scatter Charts help in statistically validating relationships between input and output variables.
Control Charts help in identifying if the process behaves under the influence of special causes of
variation.
A Cause and Effect Diagram will logically group the causes that result in a particular event.
155
ANALYZE PHASE - Check List of Toll Gate Review Questions
MAIN OBJECTIVE: Identify and prioritize the key factors that have the biggest impact on process
performance
REQUIRED DELIVERABLE: Root Causes
TOLL GATE QUESTIONS:
Has the Project Charter been updated?
Has the team examined the process and identified potential bottlenecks, disconnects and
redundancies that could contribute to the problem statement?
Has the team identified and selected the root causes(Critical X’s) of current process
performance?
Does the team understand why the problem is being seen?
Have the root causes been validated? If so, how? If not, why?
Are there any perceived barriers to success?
156
ANALYZE PHASE - Check List of Toll Gate Review Questions
TOOLS AND METHODOLOGIES TYPICALLY APPLIED:
Graphical tools of process data: Histogram, Box Plot, Dot Plot, Pareto Chart, etc.
Data Stratification
Cause & Effect Analysis
157
Module
5
Introduction to Improve
158
Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Measure
Analyze
Improve
Control
Activities
Review Project Charter
Validate Problem
Statement
and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication
Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Effective Meeting
Tools
Time Lines, Milestones,
and Gantt Charting
Value Stream Map for Deeper
Understanding and Focus
Identify Key Input, Process and
Output Metrics
Develop Operational
Definitions
Develop Data Collection Plan
Collect Baseline Data
Determine Process Capability
Complete Measure Gate
Identify Potential
Root Causes
Reduce List of
Potential Root Causes
Confirm Root Cause
to Output
Relationship
Prioritize Root Causes
Complete Analyze
Gate
Develop Potential Solutions
Evaluate, Select, and
Optimize Best Solutions
Develop ‘To-Be’ Value
Stream Map(s)
Develop and Implement
Pilot Solution
Confirm Attainment of
Project Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Implement Mistake
Proofing
Develop SOP’s, Training
Plan & Process Controls
Identify Project
Replication Opportunities
Complete Control Gate
Transition Project to
Process Owner
Identify and Implement Quick Improvements
Value Stream Mapping
Value of Speed (Process
Cycle Efficiency / Little’s
Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control
Tools
Team Feedback Session
159
Improve Phase
Key Objective:
Validated Solutions
Key Deliverables:
Potential solutions, FMEA, Risk Assessment, Pilot Plan
Roadmap of the Improve Phase:
1. Develop Potential Solutions: Based on the validated & prioritized root causes, develop
potential solutions
2. Prioritize Best Solutions: Prepare a criteria and prioritize best solutions which works best in
business interest
3. Evaluate Risk: Assess risk in implementation of each solution
4. Pilot Plan: Prepare a pilot plan for implementation of best solutions
5. Toll Gate Review: Toll gate review to be conducted with Sponsor, Black Belt & Project leader
160
What is a Failure Mode?
The way in which the component, subassembly, product, input, or process could fail to perform its
intended function.
- Things that could go wrong.
Failure modes may be the result of upstream operations or may cause downstream operations to
fail.
161
When to Conduct an FMEA
Early in the Analyze Phase, to understand possible ‘failure modes’ of the existing process, in
the search for root causes
In the Improve Phase, to understand possible ‘failure modes’ of an improved process
162
The FMEA Form
Process or
Product Name:
Prepared by:
Process/Product
FMEA Form
Page ___ of ___
FMEA Date (Orig) _____________ (Rev) ______________
Responsible:
Process Step/
Potential
Input
Failure Mode
Potential
Failure Effects
S
Potential
O
Current Controls
E
Causes
C
V
C
What is the In what ways What is the impact E What causes U What are the existing
process step does the Key on the Key Output R the Key Input R
controls and
and input
Input go
Variables
to
go
wrong?
procedures
I
A
under
wrong?
(Customer
(inspection
and test)
T
N
investigaRequirements)? Y
that
prevent
either the
C
tion?
cause
or
the
Failure
E
Mode?
Identify failure modes
and their effects
Identify causes of the
failure modes
and controls
D
E
T
E
C
T
I
O
N
R
P
N
Actions
Recommended
What are the
actions for
reducing the
occurrence of the
cause, or
improving
detection?
Prioritize
Resp.
Actions
Taken
S
E
V
What are the
E
completed actions R
taken with the
I
recalculated RPN? T
Y
O
C
C
U
R
A
N
C
E
D
E
T
E
C
T
I
O
N
R
P
N
Determine and
assess actions
163
FMEA Procedure
1. For each process input, determine the potential failure modes.
- Start with the high value inputs
2. For each failure mode, identify effects and assign severity.
- Select a severity level for each effect.
3. Identify potential causes of each failure mode and assign score.
- Select an occurrence level for each cause.
4. List current controls for each cause and assign score.
- Select a detection level for each cause.
5. Calculate the Risk Priority Number (RPN).
6. Develop Recommended Actions and assign Responsibility.
- Give priority to high RPNs.
- MUST look at severities rated a 10.
7. Assign the Predicted Severity, Occurrence, and Detection Levels and then compare RPNs.
164
Severity, Occurrence, and Detection
Severity
- Importance of the effect on customer requirements.
Often can’t do anything about this.
Occurrence
- Frequency with which a given cause occurs and creates failure modes.
Detection
- The ability of the current control scheme to detect or prevent a given cause.
165
Rating Scales
There are a wide variety of scoring “anchors”, both quantitative or qualitative.
Two types of scales are 1-5 or 1-10.
The 1-5 scale makes it easier for the teams to decide on scores.
The 1-10 scale allows for better precision in estimates and a wider variation in scores (most
common).
166
Rating Scales (Cont.)
Severity
1 = Not Severe, 10 = Very Severe
Occurrence
1 = Not Likely, 10 = Very Likely
Detection
1 = Likely to Detect, 10 = Not Likely to Detect
167
Risk Priority Number (RPN)
RPN is the product of the severity, occurrence, and detection scores.
Severity
X
Occurrence
X
Detection
=
RPN
168
Mistake Proofing
The idea is to produce zero defects by utilizing quality tools which prevent human errors.
Combining Poka Yoke with Six Sigma helps to achieve precisely that.
What is Poka Yoke?
Poka-yoke was developed in the 1960s at Toyota by one of their industrial engineers, Shigeo
Shingo.
Shingo had also coined the idea of producing zero defective items using Poka Yoke, which are
small tools that can help prevent the defects from occurring in the first place. This helps
companies achieve zero defects in a very simple manner.
The simplicity of Poka Yoke is due to its ability of being created by any employee, may it be a
manager, sales assistant or any other employee of the organization who sees the need and has
the idea to do it.
169
Mistake Proofing
How to Mistake-Proof A Process?
Mistake proofing requires employees to be alert. Primarily, an employee actually working on a
product is in a better position to notice mistakes in the process.
If they are aware of the processes, they can come up with ways to overcome errors. This can
encourage employees to come up with timely rectifications without delay, which can bring
about greater results.
Poka Yoke is useful everywhere and anywhere where there is a chance of something going
wrong. For example, process operations is an area where there is chance of missing a step.
170
Mistake Proofing
Using Poka Yoke
• You may undertake a Pareto analysis first to identify operations where there is a high
probability of errors.
• The approach to mistake proofing can be procedural, mechanical, electrical, human or any
other form of prevention.
• Having a checklist to ensure all steps are undertaken in a sequence can help. You should test
the mistake-proofing device and ensure that the user is also aware and trained to use and review
it to achieve zero defects.
• Error elimination need not be a complicated process. There are simple solutions to small
mistakes which can otherwise mean disaster for the product. Combines with Six Sigma, mistakeproofing ensures elimination of defects in the first place.
171
Piloting Solution
It is possible to pilot all or some of every solution or new design that an organization wants to
implement. And it is almost always worth the extra effort to pilot especially if conducting a DFSS
(design for Six Sigma) project.
Defining Pilot-from a Six Sigma viewpoint a pilot can be defined as:
Testing the functional and sigma capabilities of the new process, where critical functions defined
in the current generation of the multi-generational plan are operational but on a limited scale.
Four primary advantages and/or objectives of utilizing a pilot are:
Limit capital and other resource expenditures (managing risk)
Assess true performance of design and/or solutions in a controlled but “live” environment
Identify additional improvements
Identify implementation tips and traps
172
Piloting Solution
Why Pilot?
There are numerous reasons to pilot:
Confirm expected results and relationships
Increase buy-in
Improve the implementation
Lower the risk of failure
Improve the ability to better predict
Monetary savings from a proposed solution
Increase opportunities for feedback
Quickly deliver a version of a solution to a particular segment
Validate the measurement system
Understand expected variation in the process and its possible impact to the customer
Improve on solution
173
Piloting Solution (Continued)
When to Pilot
In general, there is a way to pilot all or some part of every solution or new design that an
organization wants to implement. It is almost always worth the extra effort to pilot.
Consider doing a pilot when:
The scope of the design is large,
The new product/service could cause far-reaching, unintended consequences,
Implementing the design and/or solutions will be a costly process, and
The design and/or solutions would be difficult to reverse.
If conducting a DFSS (Design for Six Sigma) project, as opposed to a DMAIC (Define, Measure,
Analyze, Improve, Control) project, piloting is almost always a must.
174
Piloting Solution (Continued)
Pilot Key Considerations
Determining how long a pilot should run and how many samples are necessary are
important considerations to be certain enough evidence is collected. Project leaders also
need to be confident that the process is stable with regard to its performance over time. If
the process is not stable the process capability (the ability to meet your customer
requirements) cannot be assessed.
Evaluate the measurement system first since it is imperative that the data collected is
accurate and precise. Then assess the stability of the process prior to evaluating the
capability. Lastly, review the scorecards.
175
Piloting Solution (Continued)
Verify the Implementation Plan
After the pilot, verify the implementation plan. Obtain assistance from the team and the process
owners. These resources can help answer questions such as: Was your schedule met? Were the
instructions clear? Were they followed? What additional information did people need? Were
there unexpected challenges encountered?
Pilot Verification and Validation
Once the implementation plan has been verified, verify and validate the pilot itself. Analyze gaps
between predicted and test performance and pilot results. Analyze gaps between pilot results
and actual requirements. And also analyze the actual pilot project plan; how did things come
together? Did the design of the scorecards predict capability of the overall process and elements?
For the gaps identified, perform a root cause analysis to determine “why.”
176
Control Methods for 5S
177
Kanban and Poka-Yoke
Kanban
Poka-Yoke
178
Elements of Waste – Lean
•
•
•
•
•
•
•
Overproduction,
Correction,
Inventory,
Motion,
Overprocessing,
Conveyance,
Waiting
179
Expectations from the Improve Phase
The critical few KPIVs identified in the Analyze Phase have been examined with data and
designed experiments.
Significant sources of variation have been investigated and are understood.
Solutions to resolve the validated root causes (critical KPIVs) have been identified, evaluated
and selected.
The efforts and risks associated with making the process change(s) are understood,
documented, and circulated for all appropriate levels of acceptance.
The project plan now incorporates the efforts to transfer responsibility to the Process Owners
in the Control Phase.
A pilot plan has been completed, and the solution optimized based on the results.
Business impact is close to target and well founded.
Tracking mechanisms are in place to identify improvement over baseline.
180
IMPROVE PHASE - Check List of Toll Gate Review Questions
MAIN OBJECTIVE: Develop, select and implement improvement solution(s)
REQUIRED DELIVERABLES: Validated Solution(s)
TOLL GATE QUESTIONS:
Has the Project Charter been updated?
What evaluation criteria were used to select a recommended solution(s)?
Do the proposed solution(s) address all of the identified root cause(s)?
Was a pilot run to test the solution(s)? What was learned? What modifications were
made? Is there evidence that the root causes have been addressed?
Has the team considered potential problems and unintended consequences (FMEA) of the
solution(s) and developed mitigation plans?
Has the proposed solution(s) been documented?
Has the team developed an implementation plan?
Have changes been communicated to all the appropriate people?
Has the necessary training for process owners/operators been conducted?
Are there any perceived barriers to success?
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IMPROVE PHASE - Check List of Toll Gate Review Questions
TOOLS AND METHODOLOGIES TYPICALLY APPLIED:
Brainstorming
FMEA
Pilot
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Module
6
Introduction to Control & Project Closure
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Lean Six Sigma: Yellow Belt Improvement Process Road Map
Define
Measure
Analyze
Improve
Control
Activities
Review Project Charter
Validate Problem
Statement and Goals
Validate Voice of the
Customer
& Voice of the Business
Validate High-Level Value
Stream Map and Scope
Create Communication
Plan
Select and Launch Team
Develop Project Schedule
Complete Define Gate
Tools
Project Charter
Voice of the Customer
and Kano Analysis
SIPOC Map
RACI and Quad Charts
Stakeholder Analysis
Communication Plan
Effective Meeting
Tools
Time Lines, Milestones,
and Gantt Charting
Value Stream Map for
Deeper Understanding and
Focus
Identify Key Input, Process
and Output Metrics
Develop Operational
Definitions
Develop Data Collection
Plan
Collect Baseline Data
Determine Process
Capability
Complete Measure Gate
Identify Potential
Root Causes
Reduce List of
Potential Root Causes
Confirm Root Cause
to Output
Relationship
Prioritize Root Causes
Complete Analyze
Gate
Develop Potential Solutions
Evaluate, Select, and
Optimize Best Solutions
Develop ‘To-Be’ Value
Stream Map(s)
Develop and Implement
Pilot Solution
Confirm Attainment of
Project Goals
Implement Solution and
Ongoing Process
Measurements
Complete Improve Gate
Implement Mistake
Proofing
Develop SOP’s, Training
Plan & Process Controls
Identify Project
Replication Opportunities
Complete Control Gate
Transition Project to
Process Owner
Identify and Implement Quick Improvements
Value Stream Mapping
Value of Speed (Process
Cycle Efficiency / Little’s
Law)
Operational Definitions
Data Collection Plan
Histograms
Process Capability Analysis
7QC Tools
Cause & Effect Analysis
FMEA
Kaizen, 5S, NVA Analysis,
Generic Pull Systems,
Four Step Rapid Setup Method
Process Flow Improvement
Process Balancing
Solution Selection Matrix
Piloting and Simulation
Mistake-Proofing/
Zero Defects
Standard Operating
Procedures (SOP’s)
Process Control Plans
Visual Process Control
Tools
Team Feedback Session
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Control Phase
Key Objective:
Control Plan
Key Deliverables:
Control Plan, SOP, Project Sign off
Roadmap of the Control Phase:
1. Develop Control Plan: Develop control plans for process monitoring with implemented
solutions
2. Develop SOPs: Develop SOPs to train employees on new process
3. Toll Gate Review: Toll gate review to be conducted with Sponsor, Black Belt & Project
leader
4. Project Closure: Calculate the realized benefits & close the project after a formal sign off
by Sponsor
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Control Plan
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Control Plans Answer the Following Questions
1. What is the process that is being controlled?
2. What is (are) the process output(s) that are being monitored/controlled?
3. What are the inputs that are being monitored/controlled in order to keep the output at its
target level?
4. How are the inputs and outputs being measured, monitored, and controlled?
5. How does someone react when the inputs or outputs are not in control?
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Selecting What to Document
Activities critical to customer satisfaction
Processes/tasks that involve many people
- Especially changing team players, multiple functions
Complex activities
Areas where “history” is important
- Will we need to refer to what we’ve done or how we did this later?
(Examples: DMAIC project tracking and documentation)
Legal, audit requirements
- Examples: Hiring process; financial procedures
Where flexibility is essential
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Documentation Hints
Language
Write at a level appropriate to the user
Watch for jargon or techno-ese
Spell out acronyms, abbreviations and symbols the first time they are used
Be aware of multi-cultural influences
Be clear, concise, and specific
Make sure to quantify
Include process standards
Key measures, customer requirements
Provide reference sources
A name and phone number, e-mail address, etc.
Add cross references when/where applicable
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Documentation Hints
Use graphics when/where applicable
- Incorporate process maps or examples of forms
Test and validate documentation
- You may want to ask an objective party
Make it accessible and flexible
- On-line, hard copy or both
- Someone should “own” documentation
- Have an update and improvement mechanism
- Be aware of audit considerations
Use documentation to train others
Say what you do, but do what you say!
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Control Plan Sample Format
Process
Measurement
Method
Responsible Sample Size
Frequency
Barrier to
success
ANDON Cord
Rectification
ResponsibleFollow Ups
Plan
Follow Ups
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Expectations from the Control Phase
Control plans, implementation plans, SOP’s, training plans, etc. have been developed
The final solution has been implemented and the expected process performance has been
achieved
There is a clear hand-off of the project to the process owner
Business benefits have been planned and are being measured
Future opportunities for process improvement have been properly communicated
The team has celebrated and been rewarded for their efforts
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CONTROL PHASE - Check List of Toll Gate Review Questions
MAIN OBJECTIVE: Establish how to sustain and monitor new process performance
REQUIRED DELIVERABLES: Process Control Plan
TOLL GATE QUESTIONS:
Has the Project Charter been updated?
Has a Process Control Plan been prepared and reviewed with the Sponsor?
Have the key users of the process been trained?
Have the project goals/performance targets been achieved? Does the Sponsor agree?
Have the financial benefits (if any) been validated by a Finance representative?
Is the new process "in control"?
Has the new process been documented and communicated?
Does the Process Owner understand the Control Plan?
Is there an agreement between the Team leader and Sponsor as to when the new process
will be stabilized?
Are there opportunities to replicate the solutions to other processes?
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CONTROL PHASE - Check List of Toll Gate Review Questions
TOOLS AND METHODOLOGIES TYPICALLY APPLIED:
Standard Operating Procedures (SOP)
Mistake-Proofing
Auditing/Monitoring strategy (part of the Control Plan)
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Thank You and Good Luck !!!
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