Quality Journey --Six Sigma DMAIC.pdf

Quality Journey by Nilesh Jajoo
Six Sigma - Lean Six Sigma

Defining Six Sigma
Six Sigma as a methodology provides businesses with the tools to improve the capability of their
business processes. For Six Sigma, a process is the basic unit for improvement . In Six Sigma, the purpose
of process improvement is to increase performance and decrease performance variation
When people refer to Six Sigma, they refer to several things:
It is a philosophy It is based on facts & data
It is a statistical approach to problem solving It is a structured approach to solve problems or
reduce variation
It refers to 3.4 defects per million opportunities It is a relentless focus on customer satisfaction
Strong tie-in with bottom line benefits Metric, Methodology, Management System

History of Six Sigma
In the late 1970's, Dr. Mikel Harry, a senior staff engineer at Motorola's Government Electronics Group (GEG), experimented
with problem solving through statistical analysis. Using this approach, GE's products were being designed and produced at a
faster rate and at a lower cost. Subsequently, Dr. Harry began to formulate a method for applying Six Sigma throughout
Motorola. In 1987, when Bob Galvin was the Chairman, Six Sigma was started as a methodology in Motorola. Bill Smith, an
engineer, and Dr. Mikel Harry together devised a 6 step methodology with the focus on defect reduction and improvement in
yield through statistics. Bill Smith is credited as the father of Six Sigma. Subsequently, Allied Signal began implementing Six
Sigma under the leadership of Larry Bossidy. In 1995, General Electric, under the leadership of Jack Welch began the most
widespread implementation of Six Sigma.
MikelHarry Bill Smith Larry Bossidy Jack Welch
General Electric: “It is not a secret society, a slogan or a cliché. Six Sigma is a highly disciplined process that helps focus on
developing and delivering near-perfect products and services. Six Sigma has changed our DNA –it isnow theway we work.”
Honeywell: “Six Sigma refers to our overall strategy to improve growth and productivity as well as a Quality measure. As a
strategy, Six Sigma is a way for us to achieve performance breakthroughs. It applies to every function in our company and not
just to the factory floor.”

Lean Six Sigma
Lean operation principles are derived from the Lean manufacturing practices. Lean manufacturing is a very effective strategy
first developed by Toyota . The key focus of Lean is to identify and eliminate wasteful actions that do not add value to
customers . Lean operation principles can be used to greatly improve the efficiency and speed of all processes.
Simple Lean tools withextraordinary benefits
5S KAIZEN POKA -YOKE
Pareto
Analysis
5 Why’s PDCA
Benefits of Lean –Total Productive Maintenance
• Increased productivity
• Reduced breakdown
• Reduced defects
• Reduction in maintenance cost
• Reduced stock
• Zero accidents
• Improved morale
etc.

7 Waste in Lean
W O R M P I T
Waiting Over-Production Rework Motion Over-processing Inventory Transportation
The underutilization of talent and skills is sometimes called the 8th waste in Lean.
Waiting is non- productive time due to lack of material, people, or equipment e.g. 1) Waiting on part of customer or employee for a service
input 2) Delayed work due to lack of communicationfrom another internal group.
Over-Production refers to producing more than the next step needs or more than the customer buys e.g.- Preparing extra reports , Over-
ordering materials
Rework or Correction . Waste of Correction includes the waste handling and fixing mistakes e.g. Incorrect data entry, Making bad
product or materials
Motion is the unnecessary movement of people and equipment e.g. Extra steps , Extra data entry , Search for something for approval
Over-Processing refers to tasks, activities and materials that don’t add value e.g. Sign-offs , Reports that contain more information than
the customer wants or needs , Duplication of effort/reports etc.
Inventory is the liability of materials that are bought, invested in and not immediately sold or used e.g Transactions not processed
Transportation is the unnecessary movement of material and information e.g. Forwarding emails to one another

5 S’s
 Sort –Clearly distinguish needed items from unneeded
items and eliminate the latter.
 Straighten / Stabilize / Set in Order –Keep needed items in
the correct place to allow for easy and immediate retrieval
 Shine –Keep the work area clean.
 Standardize –Develop standardized work processes to
support the first three steps
 Sustain –Put processes in place to ensure that the first four
steps are rigorously followed

KAIZEN
What KAIZEN means ?
KAIZEN
Make it easier by studying and making the improvement through
elimination of waste
+
Kaizen is a Japanese word meaning continuous improvement
One of the most notable features of kaizen is that big results come from many small changes accumulated over time
Kaizen means continual improvement which is : Quick, Simple and Inexpensive
ZEN
Think, make good , make better
KAI
To modify, to change

POKA- YOKE
Poka-yoke is a structured methodology for mistake-proofing operations. It is any device or mechanism that either
prevents a mistake from being made or ensures that the mistakes don’t get translated into errors that the customers
see or experience. The goal of Poka-Yoke is both prevention and detection: “errors will not turn into defects if
feedback and action take place at the error stage
The best operation is one that both produces and inspects at the same time
There are three approaches to Poka-Yoke:
 Warning (let the user know that there is a potential problem –like door ajar
warning in a car)
 Auto-correction (automatically change the process if there is a problem –like turn
on the windshield wipers in case of rain in some advanced cars)
 Shutdown (close down the process so it does not cause damage –like deny access
to ATM machines if password entered is wrong 3 times in a row)
Poka-YokeExample –Possibilityof Parachutefailing to open
should not exist
Technique Prediction Detection
WARNING
Washing Machine will not spin the clothes till the
cover of the tub is closed
Smoke detectors provide warning that smoke has
been detected and that there is a possible fire.
CONTROL
The tank hole for unleaded gas is smaller than the
one for leaded gasoline
1. The air conditioner does not
cool beyond the adjusted temperature
2. Speed governors in buses.
SHUTDOWN
The camera will not click photograph in darkness Iron automatically switches off when a particular
(high) temperature is reached

Six Sigma Project
Full Time Project Leaders
Black Belt
Focus
Yellow Belt
Carry at least Two Years of
Experience post MBB and teach Lean
Sis Sigma
MBB
Focus on Tools usage, DMAIC and
LEAN principles application
Green Belt

Define Measure Analyze Improve Control
Define Measure Analyze Design verify
Design For SIX sigma
Six Sigma Methodology

Iterative Process
Define
Measure
Analyze
Improve
Control

12 Steps Process
Step Description Focus Deliverable Sample Tools
0 Project Selection
Identify project CTQ's, develop team charter, define high-level
process map
1 Select CTQ characteristics Y Identify and measure customer CTQ's Customer, QFD, FMEA
2 Define Performance Standards Y Define and confirm specifications for the Y Customer, blueprints
3 Measurement System Analysis
Y
Measurement system is adequate to measure Y
Continuous Gage R&R,
Test/Retest, Attribute R&R
4 Establish Process Capability Y Baseline current process; normality test Capability indices
5 Define Performance Objectives Y Statisicly define goal of project Team, benchmarking
6 Identify Variation Sources
X
List of statistically significant X's based on analysis of historical
data
Process Analysis, Graphical
analysis, hypothesis testing
7 Screen Potential Causes X Determine vital few X's that cause changes to your Y DOE-screening
8 Discover Variable Relationships
X
Determine transfer function between Y and vital few X's;
Determine optimal settings for vital few X's; Perform
confirmation runs
Factorial designs
9 Establish Operating Tolerances Y, X Specify tolerances on the vital few X's Simulation
10
Define and Validate Measurement System
on X's in actual application Y, X
Measurement system is adequate to measure X's
Test/Retest, Attribute R&R
11 Determine Process Capability Y, X Determine post improvement capability and performance Capability indices
12 Implement Process Control
X
Develop and implement process control plan
Control charts, mistake proof,
FMEA

Define Phase Overview
What is the Define phase?
The Define phase is when your team identifies:
Who your customers are and what their requirements are for your products and services
The reason for doing the project and project boundaries
The project team members and how they will work together
What process you are trying to improve and what the process map looks like
Why is the Define phase important?
This phase is important because it clearly and precisely describes the goals of the project, aligns the project with organizational
priorities and lays the groundwork that will allow the team to remain focused.
Steps involved in the Define phase
Define 1: Identify Project CTQ’s Define 2: Project Charter Define 3: Define Process Map

Identify CTQ’s (1)
What does it mean to Identify Project CTQ’s?
Critical to Quality Characteristics, CTQ’s, are the key measurable characteristics of a project or process whose
performance standards must be met in order to satisfy the customer.
Green Belt improvement projects typically focus on one or two CTQ’s of a process or product.
Why is it important to Identify Project CTQ’s?
Project CTQ’s are important because they ensure that the improvement team is solving problems that are both
critical to your customer and aligned with your business strategy.
If project CTQ’s are not identified and validated in this manner, valuable resources may be wasted on
counterproductive projects that neither increase customer satisfaction nor add value to the business
What are the project tasks for completing Define 1?
• Identify customer
• Collect Voice of the Customer data to identify customer CTQ
• Build a process / product drill-down tree to identify project CTQ’s

Useful Tools (2)
Identify
Customers
VOC
Data
Determine
CTQs
 List Customers
 Define Customer
Segments
 Narrow List
 Review Existing VOC
Data
 Decide What to
Collect
 Collect Data
 Organize Data
 Translate VOC into
specific needs
 Define CTQs for
specific needs

Identify Customers (1)
A customer is someone who
Uses your product or service
Decides to buy your product or service
Pays for your product or service
Gets impacted by your product or service
Internal & External customers
Primary & Secondary customers
Be Clear as to which customer group we are going to Impact

Identify Customers (2)
End Users
Clients
Business
Quality
Ops
HR
Admin Finance
Be Clear as to which customer group we are going to Impact

How to convert customer comments to VOC
Sr. No Who is the customer
What customer
said
(Voice of
customer)
What Customer meant ?
What is the
need ?
when is the
need felt ?
where is the
need felt ?
Why is the need
felt
How is the
situation handled
now ?
1
2
3
4
5
• Often customer requirement are hazy
• Customer requirement must be understood clearly
• VOC table is technique to organize , analyze , & profile the customer requirements
VOC
Table
Sr. No Who is the customer
What customer said
(Voice of customer)
What Customer meant ?
What is the
need ?
when is the
need felt ?
where is the
need felt ?
Why is the need felt
How is the situation
handled now ?
1 Household member AC should be silent Sound Sleep At Night Bedroom
Remain fresh next
morning
Uses a ceiling fan
that makes a lot of
noise
Analyzing Customer comments using 5W & 1H leads to CTQ Identification
Note :- We can use “KANO”
Diagram to identify and
analyze customer VOC

Project Charter
What are the project tasks for completing Project Charter ?
1. Define the Business case
2. Develop Problem Statement
3. Develop Goal Statement
4. Assess Project Scope
5. Select Project Team and Define Roles
6. Set Milestones
7. Get sign-off for Project Charter

Project Charter
Business Case :-
High level brief of process / project
WHY is it IMPORTANT to do this project?
Why is it important to do this project NOW?
What would happen if this project is not done?
What will be the impact of this project in case of a successful closure?
Problem Statement :-
WHAT is the problem?
How big is the problem? (use real data or leave blanks to fill in when
you get the data
When was the problem evident? (dates that the data represents or
was collected)>
What is the impact of the problem (time, $, customer satisfaction,
etc.)
Goal Statement :-
The Goal statement should be S*M*A*R*T*
(“ Specific, Measurable, Attainable, Relevant, Time bound)
Always start with a verb..”Increase, Reduce, Improve”
Scope :-
What processes, systems, products, services, channels, etc. will you
consider / exclude in this project?
In Scope
Out Scope
Start and Stop Points :-
Project boundaries
Supporting Data for Project Charter :-
Current Defect /Defect %
Define Opportunity
Unit of Measure
DPU
DPMO
Current Sigma Level

Team Activity
Develop a Project Charter for the following scenarios. Leave blanks where you do not have numbers available
Case A: Current Resolution TAT for the process is 2.2 days as against a target of 1 day
Case B: Cycle Time of the Full and Final Settlement is 30 days as against the industry average of 14 days
Case C: The C-Sat scores for the process are at 50% as against a target of 70%
Case D: The current Attrition percentage is at 10% (monthly) as against the industry average of 4%

Process Map(1)
Why is it important to Define a Process Map?
A high-level (SIPOC/COPIS) map will help you understand the process and validate your project scope. It is a bridge between the problem
and scope statements in your charter and the more detailed maps you will develop to help you improve the process.
A high level map provides focus for the team and helps you identify areas that are within (as well as beyond) your control.
In addition, process mapping serves as a communication tool that helps you to clarify the process to others, both internally and
externally to the business.
S
Supplier
I P O C
Customer
Output
Process
Input

Process Map (2)
 Supplier: The provider of inputs to your process
 Input: Materials, resources or data required to execute your process
 Process: A collection of activities that takes one or more kinds of input and creates output that is of value
to the customer
 Output: The products or services that result from the process
 Customer: The recipient of the process output – may be internal or external
 CTQs: Critical-to-quality characteristics; A specific attribute or quality of the output that is a key
requirement for customer satisfaction
 Boundary: The limits of a particular process, that define the start and stop points of the process

Process Map (3)
When to Use a Flowchart
• Todevelop understanding of how a
process is done.
• Tostudy a process for improvement.
• Tocommunicate to others how a process
is done.
• When better communication is needed
between people involved with the same
process.
• Todocument a process.
• When planning a project
Start /End
Preparation Display
Y
N
Process Decision Predefine Process
Data storage
Documents
Delay
Commonly used symbols
Manual Input
Extract
• Testingthe Flow
• Arethe processstepsidentifiedcorrectly?
• Isevery feedbackloopclosed?
• Does every arrowhaveabeginningandendingpoint?
• Isthere morethanonearrow from anyactivitybox? Perhapsit couldbea diamond.
• Areallthe stepscovered?
Important
Points
Please refer 7QC tool
learning model

Process Map (4)
The Benefits Of Process Mapping Include:
 A structure for thinking through a complex process in a simplified, visible manner
 An ability to “see” the entire process as a team
 An ability to “see” that changes are not made in a vacuum and will carry through, affecting the
entire process down the line
 The magnification of non value-added areas or steps
 The ability to identify cycle times for each step in the process
Activity :- Process Flow Creation

Measure Phase Overview
What is the Measure phase?
This phase is concerned with selecting one or more product characteristics to measure, defining how the characteristics will be
measured, planning data collection, and collecting data.
Why is the Measure phase important?
This phase is important because it ensures that accurate and reliable data is collected to measure current process performance
related to the customer CTQ.
Steps involved in the Measure phase
Measure 1: CTQ Characteristic
Measure 2: Define Performance
Standards
Measure 3: Data collection Plan , Validated
Measurement system & Collect data

Select CTQ Characteristics
Two tools are commonly used to determine CTQs
CTQ Drill Down Tree
Quality Function Deployment (QFD)
Why use it?
A CTQ Drill-Down Tree is a tool which can help you reduce the scope of your project.
It accomplishes this by taking a high-level CTQ or process (also called a Big Y) to a low-level CTQ or process (also called a Small y).
This process helps to ensure that your project remains focused on what is important to the customer.

CTQ Drilldown Tree
Gross Profit & Loss
(BIG Y)
Infrastructure
Cost
IT Connectivity
Recruitment
Cost
Shared Services
Cost
Depreciation
Direct Employee
Cost
IT Services
Transport Cost
Facility Cost
Cost of Transport of
Approved Contractual
Employee
Cost of Transport for Band
3-6
SMS Blaster
Shift Cell Charges
All women employees
working during night
window
Salary of THD contractual
employee
Project Y
Project
X’s
Sample
Template

Define Performance Standards
What does it mean to Define Performance Standards?
A performance standard defines the process to be measured, how it will be measured, and how much variance will be tolerated.
This measurement will later be compared to the measurement of your current process in order to see how well you’re meeting the
customer’s need.
Why is it important to Define Performance Standards?
The performance standard translates the customer need into a clearly defined measure for which performance data can be collected.
Once you know what constitutes acceptable and unacceptable performance for your process, you can define a defect. What you define as a
defect becomes the basis for determining performance capability and improvement goals for the project.
What are the project tasks for completing Measure ?
Develop operational definition
for process to be measured
Identify target performance Set specification limit(s)
Define unit, defect and defect
opportunity

Unit, Opportunity and Defect
A Unit is the number of parts, sub-assemblies, assemblies or systems inspected or tested
An Opportunity is a characteristic you inspect or test
A Defect is anything that results in customer dissatisfaction / any non conformance
In the example below:
The Customer ordered for squares with 5 white circles etched on the surface
Therefore:
Each square is a UNIT
Each circle is an OPPORTUNITY
Each black circle is a DEFECT
Therefore we have:
4 Units
5 Opportunities per Unit
9 Defects
3 Defectives

Type of Data
Data can be broadly
classified in 2 types
Discrete Data
Continuous Data
Binary
Count
Discrete Data
Binary (Yes/No, Defect/No Defect)
Count Data (Number of PC breakdowns in a
week, Number of days present in week)
Continuous Data
Can be broken down into increments infinite
number of possible value
Refined e.g. 2.746 tells you the exact
dimension
Before moving on to Data Collection Plan, it is important to understand the characteristics of data.
• Continuous data provides more information compared to a discrete data
• Large sample sizes are required to measure higher Sigma multiples for discrete data
• Discrete data does not allow to understand the process variation
The more Continuous we can make the Data, the More it will tell us about our process Variance

Measurement Example
Speed
Miles per hour/centimeters
per second
10, 20, 30, etc. Fast/slow N/A
Continuous
Discrete
Ordinal Binary Nominal
Defects N/A N/A Good /Bad, CE/NCE
Cracked
/Burned/Missing
Time Hours, minutes, seconds 1,2,3 etc. a.m/p.m N/A
Date N/A Jan . Feb etc. Before/After N/A
AHT/Cycle Time
Hours, minutes, seconds,
month, date, year
10,20,30 etc.
Before/After, Greater
/Lower
N/A
Temperature Degrees C or F 10,20,30 etc. Hold /Cold N/A
Scores Percent, number correct A,B,C,D etc. Pass/Fail N/A

Data collection plan
Sample Template for Data collection plan

Audit Sampling Process
https://www.slideshare.net/NileshJajoo1/quality-journey-sampling-
process
Please refer session on Sampling Process :-

Measurement system analysis
Observed Process Variation
Actual Process
Variation
Measurement
Variation
Variation
due to
Operators
Variation
due to
Gage
Reproducibility
Bias Stability Linearity Repeatability
To address actual Process Variability , the variation due to the Measurement System must first be identified & separated from that of the
Process
Tools To be used for MSA
Test/Retest,
Attribute R&R

Measurement System Analysis–Objectives
• Recognize that observed variation of a product/process includes the true variation of the product/process & the variation due to the
measurement system
• Identify & describe possible sources of variation in a measurement process
• Describe the importance of a validated measurement system
• Describe the terms precision, accuracy & resolution in relation to MSA
• Use appropriate tools to validate measurement system, analyze, and interpret results
--- Gage R&R for continuous data
--- Attribute R&R for discrete data
Why is MSA important?
• Data is only as good as the process that MSA identifies how much variation is present in the measurement process. Understanding
measurement variation is necessary for identifying “true” process variation and maximizing true Y improvements.
• Without MSA, you run the risk of making decisions based on an inaccurate picture of your MSA helps direct efforts aimed at decreasing
measurement variation.
• Excessive measurement variation distorts our understanding of what the customer feels

Accuracy and Precision
Measurement System Error
Accuracy Precision
Bias Stability Linearity Repeatability Reproducibility
Good measurement systems have the
following characteristics…
Accuracy:
The average of multiple
measurements of an event are
equal to the true value
Stability:
Linearity:
Precision:
The measurement system
maintains its performance over
time
The measurement system
maintains its performance over a
range of events
There is little variation in
repeated measurements of the
same event

Prevision v/s Accuracy

Gage Reproducibility
Gage reproducibility is a measure of how consistently several operators or measurement systems measure the same
event over time. To find this value, we have several people or systems repeatedly measure the same event. We then look
for differences in the results between the people or systems.
Transaction
• Repeatability is also called Equipment Variation
• Reproducibility is also called Appraiser Variation
• Gage ‘Repeatability’ & ‘Reproducibility studies are
collectively referred as GRR studies
• GRR studies should be performed over the range of expected
observations
• Actual equipment should be used for the GRR studies
• Actual equipment should be used for the GRR studies
• It should be business as usual
When you setup your Gage R&R, make sure you follow these
guidelines
• You should have at least 30 different data points (Events or
transactions) per Operator
• You need 3 different operators randomly selected.
• When you run the second trial, randomize your data points
(events) before having the operators judge them.
• The data points you select should have at least 5 good and 5 bad

Gage R & R for Continuous Data
X Bar R Method
–Typically used in automobile industry
–Extreme values affect the method
–Short & Long Method
• Short Method does not measure operator and equipment variability separately
• Long method measures operator and equipment variability separately
ANOVA Method
• Measures operator & equipment variability separately as well as combined effect of operator & parts
• More effective when extreme value are present
• Most tedious to perform manual calculations

Gage R and R ANOVA Method: Example

Gage R and R ANOVA Method: Example
Two-Way ANOVA Table With Interaction
Source DF SS MS F P
Call Number 2 592.667 296.333 205.154 0.000
Operator Num 2 6.889 3.444 2.385 0.208
Call Number * Operator Num 4 5.778 1.444 7.800 0.001
Repeatability 18 3.333 0.185
Total 26 608.667
Gage R&R
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 0.8272 2.46
Repeatability 0.1852 0.55
Reproducibility 0.6420 1.91
Operator Num 0.2222 0.66
Operator Num*Call Number 0.4198 1.25
Part-To-Part 32.7654 97.54
Total Variation 33.5926 100.00
Study Var %Study Var
Source StdDev (SD) (6 * SD) (%SV)
Total Gage R&R 0.90948 5.4569 15.69
Repeatability 0.43033 2.5820 7.42
Reproducibility 0.80123 4.8074 13.82
Operator Num 0.47140 2.8284 8.13
Operator Num*Call Number 0.64788 3.8873 11.18
Part-To-Part 5.72411 34.3447 98.76
Total Variation 5.79591 34.7755 100.00
Number of Distinct Categories = 8
The Total Gage R&R value under %
contribution shows the measurement
system error for this test, in this case 2.46%
of the variation in the data comes from the
measurement system. We like it to be less
than 10%, so this measurement system is
acceptable.
The remaining variation comes from Part-to-
Part variation. In this study, 97.54% of the
variation was due to variation in
performance of the actual call cycle time –
true process variation.
Rules of Thumb–Acceptable Ranges
Analyzing Gage R&R Results
• R&R less than 10%–Measurement System
“acceptable
• R&R 10% to 30%–May be acceptable–make
decision based on classification of Characteristic ,
Application, Customer Input, etc.
• R&R over 30%–Not acceptable. Find problem, re-
visit the Fishbone Diagram, remove Root Causes

Analyze
In the Analyze phase, the question to be answered is "What is wrong?“ .In this phase the team determines the root
causes of the problems of the process , with key deliverable from this phase is validated root causes .
Steps involved in Analyze Phase :-
Analyze 1: List all probable X’s Analyze 2: Identify Critical X’s Analyze 3: Verify sufficiency of critical X’s for the project
Project team should have already identified the process outputs - CTQ's and CTP's, or the little Y's - in the Define phase. The X's are process
and input variables that affect the CTQ's and CTP's. The first consideration in the Measure phase is to identify the ‘x’ data to collect while
base lining these ‘y’ variables. The ‘y’ data are needed to establish a baseline of the performance of the process. The ‘x’ data are collected
concurrently with the Y's in this phase so that the relationships between the X's and Y's can be studied in the Analyze phase will impact the
Big Y's

Fish Bone (Cause and Effect)..1
Process Policy
People
Plant
Effect
Y’s
Cause X’s
Cause X’s
• EFFECT is “WHAT?”Happens
• CAUSE is “WHY?” it Happens
• EFFECT = RESULT OR OUTCOME
• CAUSE = REASON(S) OR FACTOR(S) CONTRIBUTING TO
THE EFFECT
5 WHY’s is the additional process aligned
People Policy Procedure Plant Environment
ISHIKAWA DIAGRAM or FISH BONE
DIAGRAM
The cause and effect diagram was developed by
Dr. K. ISHIKAWA to represent the relationship
between EFFECT or PROBLEM and all the
possible CAUSES influencing it. For every EFFECT
there are likely to be several CAUSES.
The major causes can be summarized generally
under four categories known as 4M’s
—MAN,MACHINE,MATERIAL & METHOD, OR
4P’s – PLANT,POLICY,PEOPLE,PROCEDURE

Fish Bone (Cause and Effect).. 2
• The first step in constructing a Fishbone diagram is to define clearly the effect being analyzed
• The second step consists of gathering all the data about the key process input variables (KPIV), the potential causes (in
the case of a problem), or requirements (in the case of the design of a production process) that can affect the outcome
• The third step consists of categorizing the causes or requirements according to their level of importance or areas of
pertinence. The most frequently used categories are:
Manpower, Machine, Method, Measurement, Mother-nature, Manufacturing
• The last step is the actual drawing of the diagram. The diagram is immensely helpful to draw a mind map of the cause
and effect relationship
Brain Storming is the strongest tool to identify the variable causes X’s
Brainstorming is used at the initial steps and during the Analyze phase of a Project to identify potential factors that affect the output. It is a
group discussion session that consists of encouraging a voluntary generation of a large volume of creative, new, and not necessarily
traditional ideas by all the participants. It is very beneficial because it helps prevent narrowing the scope of the issue being addressed to the
limited vision of a small dominant group of managers. Since the participants come from different disciplines, the ideas that they bring forth
are very unlikely to be uniform in structure. They can be organized for the purpose of finding root causes of a problem and suggest
palliatives. If the brainstorming session is unstructured, the participants can give any idea that comes to their minds, but this might lead the
session to stray from its objectives.

Fish Bone (Cause and Effect)..3

Process Mapping
Many business processes are poorly defined or totally lacking in description. Many procedures are simply described by word of
mouth or may reside in documents that are obsolete. In process management, often by simply trying to define and map the process,
we provide a means for both understanding and communicating operational details to those involved in the process.
 It also provides a baseline, or standard, for evaluating the improvement. In many cases, merely
defining and charting the process as it is can reveal many deficiencies such as redundant and needless steps and other non-
value-added activities.
 Process mapping allows the team to represent the process associated with their problem in a way that others find easy to
understand, making the job of defining the current process easier
 It also allows people to easily understand where waste exists in the process and where the process has been poorly defined
Process maps can be analyzed for:
Time-per-event(reducing cycle time ) Process Repeat (preventing rework)
Duplication of effort (identifying and
eliminating duplicated task)
Unnecessary task (eliminating tasks that are in
the process for no apparent reason)
Identifying and segregating Value-added and
non-value-added tasks
The Process Map should contain enough detail to enable effective analysis
 It should illustrate both the workflow and the organizational interaction
 It should use a common language (symbology) which is understood by everyone
 It should capture all multiple paths, decisions, and rework loops
 It should contain adequate detail
o Too much detail is incomprehensible
o Too little detail has no analytical value

Process Flow
When to Use a Flowchart
• Todevelop understanding of how a
process is done.
• Tostudy a process for improvement.
• Tocommunicate to others how a process
is done.
• When better communication is needed
between people involved with the same
process.
• Todocument a process.
• When planning a project
Start /End
Preparation Display
Y
N
Process Decision Predefine Process
Data storage
Documents
Delay
Commonly used symbols
Manual Input
Extract
• Testingthe Flow
• Arethe processstepsidentifiedcorrectly?
• Isevery feedbackloopclosed?
• Does every arrowhaveabeginningandendingpoint?
• Isthere morethanonearrow from anyactivitybox? Perhapsit couldbea diamond.
• Areallthe stepscovered?
Important
Points

Steps for functional Deployment Flowchart
• Step 1: List the major steps of the process in the order in which they
occur. This might be the output of your work with a top-down
flowchart or you might use some other technique to create this list.
• Step 2: Across the top of your board, flip chart or paper write the
names of the people or organizations involved in the process.
• Step 3: Under the name of the person or organization responsible for
the first step in the process, draw a box and write that step in the
box. If more than one person or group is responsible for a step,
extend the box so it is also under the name of that person or group.
• Step 4: If any of the other people or groups help or advise the ones
with primary responsibility for that step, draw an oval under the
names of those people or groups.
• Step 5: Connect the ovals to the box with the process step in it.
• Step 6: After the first step is complete, put the second step under the
people responsible for it.
• Step 7: Connect the first step to the second step, and then add ovals
for any helpers or advisors in the second process step. Keep going
this way with all the steps in the process

VA/NVA Analysis
The objective of non-value added analysis is to:
 Eliminate the hidden costs that do not add value to the customer
 Reduce unnecessary process complexity, and thus errors
 Reduce the process cycle time
 Reduce cost and increase capacity through better utilization of resources
 Reduce inventory
 Increase revenue (e.g., reduce development process cycle time to introduce new products to market faster)
VA • Customers are willing to pay
for it
• It transforms the product/
service
• It’s done right the first time.
NVA • Is not essential to produce
output.
• Does not add value to the
output.
• Includes:
• Defects, errors, omissions
• Preparation/setup, control/inspection
• Over-production, processing, inventory
• Transporting, motion, waiting, delays
Non Value Added Steps can be
further classified ,Required NVA
• Business necessity (e.g.
accounting)
• Employee necessity (e.g. payroll)
• Process necessity (e.g.
inspection)

FMEA | Failure Modes and Effects Analysis
What is Risk?
Risk can be defined as the likelihood of occurrence of an undesirable event combined with the magnitude of its impact
What is RiskAssessment?
Risk assessment is the determination of quantitative and qualitative value of risk related to a concrete situation and a recognized threat
(also called hazard).
What does Risk Analysisinclude?
Risk analysisincludes
 Identification of risks
 Estimation of their likelihood of occurrence
 Estimation of their causes and the magnitudeof their potential impact
 Risk evaluation and Development of risk mitigation plan
Failure modes and effect analysis is a structured method to identify failure modes, determine the severity of the failure, cause of the
failure, frequency of the failure, current controls in place and efficiency of the controls. This enables us to evaluate current risks in the
process and thereafter developing an action plan to mitigate risks.

FMEA Helps In
 Identifying the areas and ways in which a process or system can fail (failure mode)
 Estimating risk associated with specificcauses
 Identifying and prioritizing the actions that should be taken to reduce those risks
 Evaluating and documenting proposed process plans or current control plans
What is FailureMode?
A Failure Modeis:
The way in which the product, service, input, or process could:
1) Fail to meet requirements of the end user 2) Cause downstream operations to fail
Things that’s could go wrong :
1) Total Failure 2) Partial failure (too much, too little, too fast, or too slow) 3) Unintended result
Risk in the process can be defined and prioritized basis the RPN number (Risk Priority Number )
RPN = Severity * Occurrence Detection
*

Severity
Effect
Criteria :
Rank Effect
Criteria :
Severity of effect on Product (Customer Effect)
Severity of effect on Process (Manufacturing /Assembly
Effect)
Failure to
meet safety
and or/
regulatory
requirements
Potential failure affects safe vehicle operation and/ or involves noncompliance with
government regulation without warning
10
Failure to
meet safety
and or/
regulatory
requirements
May endanger the operator (machine or assembly)
without warning
Potential failure affects safe vehicle operation and/ or involves noncompliance with
government regulation with a warning
9
May endanger the operator (machine or assembly) with a
warning
Loss or
Degradation
of Primary
Function
Loss of primary function (vehicle inoperable , does not effect safe vehicle operation) 8
Major
Disruption
100% of the product may have to be scrapped. Line shut
down or stop the ship.
Degradation of primary function (vehicle operable, but at reduced level of performance) 7
Significant
Disruption
A portion of production run may have to be scrapped.
Deviation from
primary process including decreased line speed or added
manpower.
Loss or
Degradation
of Secondary
Function
Loss of Secondary Function (vehicle operable , but comfort/ convenience functions
inoperable)
6
Moderate
Disruption
100% of production run may have to be reworked off line
and accepted.
Degradation of Secondary Function (vehicle operable, but comfort/convenience
functions at reduced level of performance)
5
A portion of production run may have to be reworked off
line and accepted.
Annoyance
Appearance or Audible Noise, Vehicle operable, item does not conform and noticed by
most customers (>75%)
4
Moderate
Disruption
100% of production run may have to be reworked in
station before it is processed.
Appearance or Audible Noise, Vehicle operable, item does not conform and noticed
3
A portion of production run may have to be reworked in
station before it is
by many customers (50%) processed.
Appearance or Audible Noise, Vehicle operable, item does not conform and noticed by
discriminating customers (< 25%)
2
Minor
Disruption
Slight inconvenience to process, operation or operator.
No Effect No discernible effect 1 No Effect No discernible effect

Occurrence
Occurrence: A measure of probabilitythat a particular failure will actually happen.
The degree of occurrence is measured on a scale of 1 to 10, where 10 signifies the highest probability of occurrence
Likelihood of Failure Criteria: Occurrence of Cause – PFMEA (Incidents per items/vehicles) Rank
Very High
≥ 100 per thousand
10
≥ 1 in 10
High
50 per thousand
9
1 in 20
20 per thousand
8
1 in 50
10 per thousand
7
1 in 100
Moderate
2 per thousand
6
1 in 500
.5 per thousand
5
1 in 2,000
.1 per thousand
4
1 in 10,000
Low
.01 per thousand
3
1 in 100,000
≤ .001 per thousand
2
1 in 1,000,000
Very Low Failure is eliminated through preventive control 1

Detection
Opportunity for Detection
Criteria:
Rank
Likelihood of
Detection
Likelihood of Detection by Process Control
No detection Opportunity No process control; cannot detect or is not analyzed 10 Almost Impossible
Not likely to detect at any
stage
Failure Mode and or/ Error (Cause) is not easily detected (e.g. Random Audits). 9 Very Remote
Problem Detection Post
Processing
Failure Mode Detection Post Processing by operator through visual/tactile/audible means. 8 Remote
Problem Detection at
Source
Failure Mode detection in station by the operator through visual/tactile/audible means or post processing through the use
of attribute gauging (go/no-go, manual torque check/clicker wrench etc.).
7 Very Low
Processing
Failure Mode post processing by the operator through the use of variable gauging or in station by the operator through the
use of attribute gauging (go/no-go, manual torque check/clicker wrench, etc.).
6 Low
Source
Failure Mode or Error (Cause) detection in -station by the operator through the use of variable gauging or by automated
controls in-station that will detect discrepant part and notify the operator (light, buzzer, etc.). Gauging performed on setup
and first-piece check (for set-up causes only).
5 Moderate
Processing
Failure Mode detection post-processing by automated controls that will detect discrepant part and lock parts to prevent
further processing.
4 Moderately High
Source
Failure Mode Detection in station by automated controls that will detect discrepant part and automatically lock parts in
station to prevent further processing.
3 High
Error Detection and/or
Problem Prevention
Error (Cause) detection in-station by automated controls that will detect the error and prevent the discrepant part from
being made.
2 Very High
Detection not applicable; Error
Prevention
Error (Cause) prevention as a result of fixture design, machine design or part design. Discrepant parts cannot be made
because the item has been error proofed by process/product Design.
1 Almost Certain
A measure of probability that a particular failure or the cause in our operation shall be detected in current operation and shall not
pass on to the next operation. (Would not affect the internal/ external customer

FMEA Template

Pareto (80/20 principle)
The Pareto analysis is also known as the 80/20 rule because it is based on the idea that 80 percent of a project's benefit can
come from doing 20 percent of the work. Conversely, 80 percent of a situation's problems can be traced to 20 percent of the
causes.
When to Use a Pareto Chart
When analyzing data about the frequency of problems or causes in a process.
When there are many problems or causes and you want to focus on the most significant.
When analyzing broad causes by looking at their specific components.
When communicating with others about your data.
Pareto Chart Procedure
Pareto analysis begins by ranking problems from highest to lowest in order to fix
priority
The cumulative number of problems is plotted on the vertical axis of the graph against
the cause/phenomenon
 Pareto by Causes e.g. Man, Machine, Method etc.
Pareto by Phenomenon e.g. Quality ,Cost, Delivery
Tells about the relative sizes of problems indicates an important message about
biggest few problems, if corrected, a large % of total problems will be solved

Correlation /Regression
Correlation is a measure of the relation between two or more continuous variables. The Pearson correlation
coefficient is a statistic that measures the linear relationship between the X and Y . The symbol used is r. The
correlation value ranges from -1 to 1. The closer the value is to 1 in magnitude, the stronger the relationship
between the two.
 A value of zero, or close to zero, indicates no linear relationship between the x and y.
 A positive value indicates that as x increases, y increases.
 A negative value indicates that as x increases, y decreases.

Correlation /Regression
Regression analysis is a set of statistical processes for estimating the relationships between a ”dependent” variable and one
or more “independent” variable .
A natural extension of correlation is regression. Is the technique of determining a mathematical equation that relates the X’s to
the Y’s . Regression analysis is also used with historical data - data where the business already collects the y and associated x's.
The regression equation can be used as a prediction model for making process improvements.
 Input Variable (X’s): These are also called predictor variables or independent variables.
It is best if the variables are continuous
 Output Variable (Y’s):These are also called response variables or dependent variables (what we’re trying to predict).
It is best if the variables are continuous.

Hypothesis Testing
Hypothesis testing is a statistical analysis where a hypothesis is stated, sample data are collected, and a decision is made
based on the sample data and related probability value. This testing can be used to detect differences such as differences
between a process mean and the target for the process, differences between two suppliers, or differences between multiple
employees.
Two hypothesis statements are written :-
The first statement is the “null hypothesis”, Ho --- This is a statement of what is to be disproved.
The second statement is the “alternative hypothesis”, Ha---This is a statement of what is to be proved
• A statement of ‘Nodifference’
• It is a statement you are testing in order to determine
whether or not that statement is true
• In other words, observations are the result purely of
chance
• An Example expression is H0: A = B
Null Hypothesis
• A statement of ‘difference’
• It is that there is a real effect and the observations
are affected by the effect and some pure chance
variation
• It depends on the direction of the effect we are
looking for
Ha: A (B or Ha: A>B or Ha: A<B
Alternative Hypothesis

Steps for Hypothesis Testing
Hypothesis testing using the p-value approach
 State the null hypothesis H0, and the alternative hypothesis Ha.
 Choose the level of significance (α) and the sample size, n.
 Determine the appropriate test statistic and sampling distribution.
 Collect the data and compute the sample value of the appropriate test statistic.
 Calculate the p-value based on the test statistic and compare the p-value to α.
 Make the statistical decision. If the p-value is greater than or equal to α, we fail to reject the null hypothesis.
If the p-value is less than α, we reject the null hypothesis.
 Express the statistical decision in the context of the problem.
F-test
Parametric Hypothesis tests
Bartlett/Levene
test 2-sample t test
ANOVA-One
Way
2 proportion
test
Chi-Square test
of association

Non Parametric Test
Non-parametric tests while not an assumption-free, make no assumption of a specific distribution of the population. The
qualifiers (assuming) for non-parametric tests are always much less restrictive than for their parametric counterparts. For
example, classical ANOVA requires the assumptions of mutually independent random samples drawn from normal
distributions that have equal variances, while the non-parametric counterparts require only the assumption that the samples
come from any identical continuous distributions.
The most commonly used statistical tests (t-tests, Z-tests, ANOVA, etc.) are based on a number of assumptions
Classical statistical methods are strictly valid only for data measured on an interval or ratio scales
Non-parametric statistics apply to frequency or count data and to data measured in nominal or ordinal scales
Note :- Ordinal and nominal data are very common in Six Sigma work. Nearly all customer and employee surveys, product
quality ratings, and many other activities produce ordinal and nominal data.

Non Parametric v/s Parametric
If non-parametric methods are so great, why do we ever use parametric methods?
When the assumptions hold, parametric tests will provide greater power than non-parametric tests. That is, the
probability of rejecting H0 when it is false is higher with parametric tests than with a non-parametric test using the same
sample size. However, if the assumptions do not hold, then non-parametric tests may have considerably greater power
than their parametric counterparts.
Note :- It should be noted that non-parametric tests perform comparisons using medians rather than means, ranks
rather than measurements, and signs of difference rather than measured differences. In addition to not requiring any
distributional assumptions, these statistics are also more robust to outliers and extreme values.

Non Parametric Test
Minitab Non-
Parametric Test
What It Does Parametric Analogs
1 sample sign Performs a one-sample sign test of the median and calculates the corresponding point estimates and confidence interval.
·1-sample Z-test
·1-sample t-test
1-sample Wilcoxon
Performs a one-sample Wilcoxon signed rank test of the median and calculates the corresponding point estimate and confidence
interval
·1-sample Z-test
·1-sample t-test
Mann-Whitney
Performs a hypothesis test of the equality of two population medians and calculates the corresponding point estimate and
confidence interval.
·2-sample t-test
Kruskal-Wallis
Kruskal-Wallis performs a hypothesis test of the equality of population medians for a one-way design (two or more populations).
This test is the generalization of the procedure used by the Man-Whitney test. ·One-Way ANOVA
See also: Mood’s median test.
Mood’s Median test
Performs a hypothesis test of the equality of population medians in a one way design. Sometimes called a median test or sign
scores test. Mood’s median test is more robust against outliers than the Kruskal-Wallis test, but is less powerful (confidence
interval is wider, on the average) for analysing data from many distributions, including data from the normal distribution.
·One-way ANOVA
See also: Kruskal-Wallis test.
Friedman
Performs a non-parametric analysis of a randomized block experiment. Randomized block experiments are a ·Two-way ANOVA
generalization of paired experiments. The Friedman test is a ·Paired sign test
generalization of the paired sign test with a null hypothesis of treatments having no effect. This test requires exactly one
observation per treatment-block combination.
Runs tests Test whether or not the data order is random. Use Minitab’s stat > Quality Tools > Run Chart to generate a run chart ·None
Levene’s test
Test for equal variances. This method considers the distances of the observations from their sample median rather than their
sample mean. Using the sample median rather than the sample mean makes the test more robust for smaller samples.
·Bartlett’s test

Improve
In the Improve phase, the team has validated the causes of the problems in the process and is ready to generate a list of
solutions for consideration. They will answer the question "What needs to be done?"
Steps involved in Analyze Phase :-
Improve 1: Generate and Evaluate
Alternative Solutions
Improve 2: Select and Optimize
best solution
Improve 3: Pilot, Implement and Validate the Solution
As the we moves into this phase, the emphasis goes from analytical to creative. To create a major difference in the outputs, a new way to
handle the inputs must be considered
When the we has decided on a solution to present to management, the team must also consider the cost/benefit analysis of the solutions as
well as the best way to sell their ideas to others in the business.
• Proposed solution(s)
• Cost/benefitanalysis
• Presentation to management
• Pilot plan

Generate and evaluate Alternative Solutions
Brain Storming Session :-
Most project executions require a cross-functional team effort because different creative ideas at different levels of management are
needed in the definition and the shaping of a project. These ideas are better generated through brainstorming sessions
Brainstorming is a tool also used at the initial steps or during the Analyze phase of a project (Fish Bone analysis )
It is a group discussion session that consists of encouraging a voluntary generation of a large volume of creative, new, and not necessarily
traditional ideas by all the participants. It is very beneficial because it helps prevent narrowing the scope of the issue being addressed to
the limited vision of a small dominant group of managers. Since the participants come from different disciplines, the ideas that they bring
forth are very unlikely to be uniform in structure
Technique recommended :- De-Bono Six Thinking Hats
The White Hat thinking requires team members to consider only the data and information at hand.
The Red Hat gives team members the opportunity to present their feelings or intuition about the subject without explanation or need for
justification
The Black Hat thinking calls for caution and critical judgment. Using this hat helps teams avoid “groupthink” andproposing unrealistic
solutions
The Blue Hat is used for control of the brainstorming process. The blue hat helps teams evaluate the thinking style and determine if it is
appropriate
The Green Hat makes time and space available for creative thinking
The Yellow Hat is for optimism and a positive view of things. When this hat is in use, teams look at the logical benefits of the proposal

Impact Matrix/Pugh Concept
• No Major Process change e.g. Process
correction
• Minimum people involved in driving
change
• Less people dependent process
Easy to Work – High Impact on project Y Difficult to work -- High Impact on project Y
• Major Process change – Where FMEA is
required to evaluate the Risk of change
e.g. Automation, Application change
• People dependent
• Large team required to drive change
Difficult to work -- Low Impact on project Y
Easy to work -- Low Impact on project Y

Template to capture details for Impact Matrix
Sr. No Idea Operator Team Impact Implementation
Process
Correction
Governance
Failure
1 Script for Hold process A Quality Low Easy N Y
2 Script for Hold process B Operation High Easy N Y
3 Script for Hold process C Training Medium Difficult
Automation
Required
Y
4
5
Sample
Before Making Change in Process /Governance structure or Automation Risk Analysis is mandate
Refer Risk Analysis :-
FMEA | Failure Modes and Effects Analysis

Select & Implementation – Pilot
Pilot :-
A pilot is a test of a proposed solution . This type of test has the following properties:
 Performed on a small scale, usually on a subset of the target population
 Used to evaluate both the solution and the implementation of the solution
 Purpose is to make the full scale implementation more effective
 Provides data about expected results and exposes issues/ challenges in the implementation plan
Pilot Study helps to :-
 Identify previously unknown performance problems, improve and understand the risks of the solution
 Validate expected results and facilitate buy-in from stakeholders, cross-functional team.
 Smooth implementation with limited or no teething issues

Select & Implementation – Full Scale
The team first develops a plan to implement the one or more solution selected in the Improve phase.
It is important to create a solution implementation plan based on the results from the pilot plan and pilot implementation. A
big piece of the solution implementation plan is to leave tools to help the owner manage the process after the team has
gone on to other projects. A large-scale project may require dealing with multiple processes and sub-processes, multiple
implementation locations, a large number of implementation teams and several different disciplines and methodologies.
Full Scale Implementation should be treated as a project in itself, and project management practices should not be ignored.
That plan should include but not limited to:
 Potential Risk analysis – Failure Modes and Effect Analysis
 Solution Implementation Schedule
 Training Plan and Communication Plan
 Cost and Benefit Analysis

Implementation Plan
Activity Wk 1 Wk 2 Wk 3 Wk 4 Wk 5 Wk 6 Wk 7
Product Training
Communication Camp
Chat Handling
Chat Evalauation
Goverance Review
Since this phase requires several activities and monitoring, another valuable tool to use is the Gantt chart
Sample
Improvement Validation :-
Once full scale implementation has been successfully completed, Green Belt/Black Belt should
 Revalidate the measurement system to ensure that data collected post improvement is reliable
 Collect data for Output (Y) to evaluate performance post full scale implementation
o Sigma level - Sigma level computed during the Measure phase acts as a baseline and can be compared with Sigma level computed in Improve phase
o Cp, Cpk, Pp, Ppk - Similarly process capability indices can also be compared post improvement versus baseline
o Hypothesis tests - If sample data are collected post improvement, Hypothesis test should be carried to ascertain whether the improvement is
observed for the population process performance
o FMEA - Process FMEA may also be revised to cover the new changes in the process. It will help in ascertaining whether the solution and changes
induced by solution have affected the risk parameters of the process.
The main deliverable of Improve phase is Selected Solution.

Control
In the Control phase, the emphasis is on maintaining the gains achieved. The question the team is trying to answer is, "How
can we guarantee performance?". In the Improve phase, the team had a successful pilot and also got an opportunity to
tweak the solution. They used this information to plan the solution implementation and carried out full scale
implementation. It is time now to ensure that, when they finish the project, the success that they have observed will be
sustained. This involves transferring the responsibility to the process owner.
The deliverables in the Control phase are:
 Process Control Plan
 Solution documentation and Validation of Benefits
 Successful transfer to Process Owner
Steps involved in Control Phase :-
Control 1: Implement ControlSystem
for CriticalX’s
Control 2: Document Solution and
Benefits
Control 3: Transfer to Process Owner,
Project Closure

Implement Control System for CriticalX’s
Control System is the complete strategy for maintaining the improved process performance over time. It identifies the specific actions and tools required for
sustaining the process improvements or gains.
The objective is
 To ensure sure that the process stays in control after the solution has been implemented.
 To quickly detect the out of control state and determine the associated special causes so that actions can be taken to correct the problem before non-
conformances are produced.
 Green Belt/Black Belt will develop a control plan which the process owner will use as a guideline for sustaining the gains. Control plan provides a written
summary description of the systems used in minimizing process and service variation
 Control plans do not replace the information contained in detailed instructions
 In a grand sense the control plan describes the actions that are required at each phase of the process including receiving, in-process, outgoing, and
periodic requirements to assure that all process outputs will be in a state of control
Ultimately, the control plan is a living document reflecting current methods of control and measurement systems used
 What is the process that is being controlled?
 What measures (numbers) are we monitoring?
 Foreachmeasure,what are the “trigger point” valueswhere actionshould be taken?
 What action should be taken when a“trigger point” is reached?Who is responsible for taking action?
Control Plan
Process Documentation CommunicationPlan
Data Collection Plan Audit/Inspection Plan
Mistake Proofing System Risk Mitigation System
Response/ReactionPlan StatisticalProcess Control

Statistical Process/ Quality Control (1)
Variable Control Charts:
Many characteristics can be measured and expressed as numbers on some
continuous scale of measurement. In such cases, it is convenient to
describe the quality characteristic with a measure of central tendency and
a measure of variability. Control charts for central tendency and variability
are collectively called variables control charts. The chart is the most widely
used chart for monitoring central tendency, whereas charts based on
either the sample range or the sample standard deviation are used to
control process variability
o Charts based on individual measurements for subgroups of n = 1 –
Individual and moving range chart
o Charts based on subgroups of n>=2:
 Subgroupsof 2≤ n ≤10: Mean andrangechart
 Subgroups of n> 10: Mean and standard deviation chart
Computing control limits
Process mean of the statistic ± 3 standard deviations of the statistic so that
o Upper control limit (UCL) = process mean of the statistic + 3 standard deviations of the statistic
o Lower control limit (LCL) = process mean of the statistic –3 standard deviations of the statistic

Statistical Process/ Quality Control (2)
There is a close connection between control charts and hypothesis testing. Essentially, the control chart is a test of the hypothesis that the process is in a
state of statistical control. A point plotting within the control limits is equivalent to failing to reject the hypothesis of statistical control, and a point plotting
outside the control limits is equivalent to rejecting the hypothesis of statistical control.
The most important use of a control chart is to improve the process. We have found that, generally
 Most processes do not operate in a state of statistical control.
 Consequently, the routine and attentive use of control charts will identify assignable causes. If these causes can be eliminated from the process,
variability will be reduced and the process will be improved.
 The control chart will only detect assignable causes. Management, operator, and engineering action will usually be necessary to eliminate the
assignable cause. An action plan for responding to control chart signals is vital.
In identifying and eliminating assignable causes, it is important to find the underlying root cause of the problem and to attack it. A cosmetic solution will not
result in any real, long-term process improvement. Developing an effective system for corrective action is an essential component of an effective SPC
implementation.

Document Solution and Benefits ..(1)
Solutions should be documented for review and replication in other processes in the organization. It also acts a lessons learnt document for
other Green Belts and Black Belts.
Standardization and Solution Replication
One of the powerful aspects of Six Sigma is to take successful implementations and expand them across the organization. This is
accomplished with replication and standardization.
 Replication is taking the solution from the team and applying it to the same type or a similar type of
process.
 Standardization is taking the lessons/solutions from the team and applying those good ideas to processes that may be dissimilar to
the original process improved.
The team should consider standardization and replication opportunities to significantly increase the impact on the sigma performance of
processes to far exceed the anticipated results of the pilot and solution implementation.
As the implementation expands to other areas, four implementation approaches can be combined or used independently. The appropriate
approach will depend on the resources available, the culture of the organization and the requirements for a fast implementation. The four
approaches are:
 A sequenced approach is when a solution is fully implemented in one process or location;
implementation begins at a second location.
 A parallel approach is when the solution is implemented at two or more locations or processes simultaneously.
 A phased approach is when a pre-determined milestone is achieved at one location; the implementation at a second location begins.
 A flat approach is when an implementation is done at all target locations, companywide.

Document Solution and Benefits ..(2)
Project Benefits
The results of the improvement and financial benefits need to be monitored (generally) for one year.
The project leader should prepare a Project Closure Document. A Project Closure document displays the results of the project, control
activities, status of incomplete tasks, approval of key stakeholders (for example, the process owner, finance, quality systems, and
environmental) to confirm that the project is complete.
A Project Closure document should examine the following:
 Record all pertinent performance and financial data.
 Reference controls (or the control plan).
 Review and resolve any incomplete tasks.
 Obtain signatures (varies by project and organization).
 Finance –Are financial benefits valid?
 Process owners –Do they accept the controls and do they agree the project is complete?
 Environmental, health, and safety –Do they agree that all procedures and policies have been followed?
 Quality systems –Have sufficient verifiable controls been instituted to ensure project success? Have all procedures and policies been
followed?
 Management (for example, Champion) –Does management agree that the project is completed?
 Financial benefits may be soft, which can be difficult to measure (for example, improved product lets us keep a key customer, reduced
order delivery time, reduced environmental

Quality Journey --Six Sigma DMAIC.pdf

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