This document provides an introduction to Six Sigma. It begins by defining Six Sigma as a measurement that indicates how a process is performing, with six standard deviations from the mean indicating a process capable of producing 3.4 defects per million opportunities. It then discusses the philosophy, tools, methodology, and metrics of Six Sigma. The document outlines the history and development of Six Sigma. It discusses the relationship between sigma levels and defects per million opportunities (DPMO) as well as cost of poor quality. The five phases of the DMAIC methodology are introduced. Finally, the document discusses establishing customer focus through tools like critical to quality matrices and voice of the customer to identify critical characteristics.
“Lean” is a management philosophy based on the Toyota Production System (TPS). With Lean Manufacturing, you will be able to enhance value for your customers by improving and smoothing the process flow and eliminating waste. Simply put, with Lean, you will be able to increase productivity and create greater customer value with less resources.
By teaching this presentation, managers and employees will have a better understanding of the Lean principles and approach to eliminating waste, and will be more forthcoming to lead and participate in the Lean implementation process.
LEARNING OBJECTIVES
1. Acquire knowledge on the key concepts and principles of Lean
2. Describe the common Lean methods and tools for waste elimination and value creation
3. Describe the key roles in Lean deployment
4. Define the success factors for sustaining a Lean culture
CONTENTS
1. Introduction to Lean Manufacturing
2. Key Concepts of Lean
3. Lean Methods & Tools
4. Lean Roles
5. Sustaining a Lean Culture
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
Recorded webinar: http://bit.ly/1uVqMJC
Subscribe: http://www.ksmartin.com/subscribe
Purchase the book: http://www.bit.ly/VSM
These are slides from a webinar done with APICS Heartland on the topic of Value Stream Mapping.
This webinar covers:
• How to use value stream mapping as an organizational transformation & leadership alignment tool
• How to plan for a value stream mapping activity
• The mechanics of mapping, including key metrics
for office/service/knowledge work
• How to create an actionable Value Stream Transformation Plan
Performance Measures of Manufacturing System, Manufacturing lead time, Work in process, Machine utilization, Throughput, Capacity, Flexibility, Performability, Quality
This says about the basic concepts pertaining to Process Mapping and Value Stream Mapping , as an initiative towards Lean implemntation in Industrial environment.
“Lean” is a management philosophy based on the Toyota Production System (TPS). With Lean Manufacturing, you will be able to enhance value for your customers by improving and smoothing the process flow and eliminating waste. Simply put, with Lean, you will be able to increase productivity and create greater customer value with less resources.
By teaching this presentation, managers and employees will have a better understanding of the Lean principles and approach to eliminating waste, and will be more forthcoming to lead and participate in the Lean implementation process.
LEARNING OBJECTIVES
1. Acquire knowledge on the key concepts and principles of Lean
2. Describe the common Lean methods and tools for waste elimination and value creation
3. Describe the key roles in Lean deployment
4. Define the success factors for sustaining a Lean culture
CONTENTS
1. Introduction to Lean Manufacturing
2. Key Concepts of Lean
3. Lean Methods & Tools
4. Lean Roles
5. Sustaining a Lean Culture
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
Recorded webinar: http://bit.ly/1uVqMJC
Subscribe: http://www.ksmartin.com/subscribe
Purchase the book: http://www.bit.ly/VSM
These are slides from a webinar done with APICS Heartland on the topic of Value Stream Mapping.
This webinar covers:
• How to use value stream mapping as an organizational transformation & leadership alignment tool
• How to plan for a value stream mapping activity
• The mechanics of mapping, including key metrics
for office/service/knowledge work
• How to create an actionable Value Stream Transformation Plan
Performance Measures of Manufacturing System, Manufacturing lead time, Work in process, Machine utilization, Throughput, Capacity, Flexibility, Performability, Quality
This says about the basic concepts pertaining to Process Mapping and Value Stream Mapping , as an initiative towards Lean implemntation in Industrial environment.
Value Stream Mapping is a key component of Value Stream Management – the process by which Lean concepts and tools are utilized to minimize waste and promote one piece flow pulled by customer demand through the entire operation.
Six Sigma DMADV DMAIC - Project CharterDavid Nichols
In this Slide Share we will examine the Project Charter. The Project Charter is the first step in the DMADV and DMAIC processes. The Project Charter will start the project or will kill it. Without this document properly executed, the project will be limited.
Value stream mapping is a practical and highly effective way to learn to see and resolve disconnects, redundancies, and gaps in how work gets done.
This VSM project template helps you and your project team to put together a "storyboard" for effective presentation to your key stakeholders. It includes four key phases:
1) Define and pick product/service family
2) Create a current state map
3) Develop a future state map
4) Develop an implementation plan
This document consists of a VSM project template in Powerpoint format and a set of Excel templates comprising VSM charter, Results table, Implementation Plan and common VSM icons.
More Information:
https://flevy.com/browse/business-document/lean-manufacturing-160
BENEFITS OF DOCUMENT
Learn how to eliminate waste to save time and make more money.
Learn how to apply simple Lean methods and tools in the workplace to improve productivity and quality.
DOCUMENT DESCRIPTION
Lean is a management philosophy based on the Toyota Production System (TPS). With Lean Manufacturing, you will be able to enhance value for your customers by improving and smoothing the process flow and eliminating waste. Simply put, with Lean, you will be able to increase productivity and create greater customer value with less resources.
By teaching this presentation, managers and employees will have a better understanding of the Lean principles and approach to eliminating waste, and will be more forthcoming to lead and participate in the Lean implementation process.
LEARNING OBJECTIVES
1. Understand the key concepts and principles of Lean
2. Acquire knowledge on the common Lean methods and tools and their applications to eliminate waste and create more value for customers
3. Identify ways to develop "Kaizen eyes" to look for improvement opportunities
4. Describe the various Lean roles
5. Define the critical success factors for sustaining a Lean culture
CONTENTS
1. Introduction to Lean Thinking
- The case for Lean Manufacturing
- Where did Lean originate?
- Toyota's philosophy
- Lean adoption in various environments
- Impact of Lean principles in industry
- Lean applications in manufacturing, process and service industries
- What is Lean?
- What Lean is not
- Traditional thinking versus Lean thinking
- Traditional culture vs. Lean culture
- Lean management framework
- Lean and six sigma
- Benefits of Lean manufacturing
Got a question about this presentation? Email us at support@flevy.com.
I've been asked to put together a basic (and therefore relatively quick) introduction to Lean Six Sigma & DMAIC. While it’s not yet finished, I thought I would put it out there for people to comment on. Since the presentation is supposed to be training material there’s more text on the slides than I would prefer, but there are a few exercises and games to get the trainees involved.
I've put the PowerPoint version on my blog:
http://alesandrab.wordpress.com/2013/06/07/introduction-to-lean-six-sigma-dmaic/
Value Stream Mapping is a key component of Value Stream Management – the process by which Lean concepts and tools are utilized to minimize waste and promote one piece flow pulled by customer demand through the entire operation.
Six Sigma DMADV DMAIC - Project CharterDavid Nichols
In this Slide Share we will examine the Project Charter. The Project Charter is the first step in the DMADV and DMAIC processes. The Project Charter will start the project or will kill it. Without this document properly executed, the project will be limited.
Value stream mapping is a practical and highly effective way to learn to see and resolve disconnects, redundancies, and gaps in how work gets done.
This VSM project template helps you and your project team to put together a "storyboard" for effective presentation to your key stakeholders. It includes four key phases:
1) Define and pick product/service family
2) Create a current state map
3) Develop a future state map
4) Develop an implementation plan
This document consists of a VSM project template in Powerpoint format and a set of Excel templates comprising VSM charter, Results table, Implementation Plan and common VSM icons.
More Information:
https://flevy.com/browse/business-document/lean-manufacturing-160
BENEFITS OF DOCUMENT
Learn how to eliminate waste to save time and make more money.
Learn how to apply simple Lean methods and tools in the workplace to improve productivity and quality.
DOCUMENT DESCRIPTION
Lean is a management philosophy based on the Toyota Production System (TPS). With Lean Manufacturing, you will be able to enhance value for your customers by improving and smoothing the process flow and eliminating waste. Simply put, with Lean, you will be able to increase productivity and create greater customer value with less resources.
By teaching this presentation, managers and employees will have a better understanding of the Lean principles and approach to eliminating waste, and will be more forthcoming to lead and participate in the Lean implementation process.
LEARNING OBJECTIVES
1. Understand the key concepts and principles of Lean
2. Acquire knowledge on the common Lean methods and tools and their applications to eliminate waste and create more value for customers
3. Identify ways to develop "Kaizen eyes" to look for improvement opportunities
4. Describe the various Lean roles
5. Define the critical success factors for sustaining a Lean culture
CONTENTS
1. Introduction to Lean Thinking
- The case for Lean Manufacturing
- Where did Lean originate?
- Toyota's philosophy
- Lean adoption in various environments
- Impact of Lean principles in industry
- Lean applications in manufacturing, process and service industries
- What is Lean?
- What Lean is not
- Traditional thinking versus Lean thinking
- Traditional culture vs. Lean culture
- Lean management framework
- Lean and six sigma
- Benefits of Lean manufacturing
Got a question about this presentation? Email us at support@flevy.com.
I've been asked to put together a basic (and therefore relatively quick) introduction to Lean Six Sigma & DMAIC. While it’s not yet finished, I thought I would put it out there for people to comment on. Since the presentation is supposed to be training material there’s more text on the slides than I would prefer, but there are a few exercises and games to get the trainees involved.
I've put the PowerPoint version on my blog:
http://alesandrab.wordpress.com/2013/06/07/introduction-to-lean-six-sigma-dmaic/
Six Sigma is a disciplined, statistical-based, data-driven approach and continuous improvement methodology for eliminating defects in a product, process or service.
By- Acropolis
Six Sigma Implementation to reduce rejection rate of Pump Casings at local Ma...IOSR Journals
Six Sigma is being Implemented all over the World as a successful Quality Improvement
Methodology. This article provides a description of Six Sigma Project implemented at Local manufacturing
Company. The Company Manufactures Pump Casings where it was receiving high nonconformance rate that
resulted in to Rejection of Product. This study deals with Six Sigma DMAIC methodology implementation and
gives a frame work of how the non-conformance rate was first monitored and then brought in to acceptance
limits. A complete Coverage of the statistical analysis performed during the study is given and results are
shown to describe that how Six Sigma helped the Project members to Improve Quality of Pump casings at
manufacturing facility.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Six Sigma is a data-driven approach to process improvement that seeks to identify and eliminate defects or variations in processes to improve efficiency and quality. It is a methodology that focuses on understanding customer needs, measuring current performance, analyzing data to identify root causes of problems, improving processes, and controlling future performance to ensure sustained improvement.
The benefits of Six Sigma are far-reaching, impacting various industries including manufacturing, healthcare, finance, and service industries. By implementing Six Sigma, organizations can expect to see improvements in customer satisfaction, cost reduction, increased efficiency, and enhanced employee engagement.
This Six Sigma Improvement Process PPT presentation is tailored for senior executives, decision-makers, and key stakeholders who are assessing and planning to launch a Six Sigma program. It is also beneficial for management and staff seeking education on key concepts, principles, and the Six Sigma DMAIC approach to process improvement. Additionally, trainers and facilitators looking to enhance the learning experience with professionally developed training materials by certified Lean Six Sigma Black Belts will find this presentation valuable.
This presentation provides a comprehensive overview of the Six Sigma Improvement Process, offering insights and strategies for organizations to achieve excellence in their operations. Whether you are just beginning your Six Sigma journey or looking to enhance your existing program, this presentation is an essential resource for driving impactful and sustainable change within your organization.
LEARNING OBJECTIVES
1. Understand key Six Sigma concepts and principles for continuous improvement.
2. Apply Six Sigma tools and DMAIC methodology to solve business problems.
3. Identify key roles and responsibilities in Six Sigma projects and understand project selection and management for maximizing benefits.
4. Identify the critical success factors for successful Six Sigma implementation.
CONTENTS
1. Overview of Six Sigma
2. Key Concepts of Six Sigma
3. Critical to Quality (CTQ)
4. Six Sigma Methodologies
5. Six Sigma Toolkit
6. Organizing for Six Sigma
7. Project Selection and Management
8. Critical Success Factors
Six Sigma Improvement Process: Transforming Processes, Elevating Performance
Six sigma
1. TÜV SÜD South Asia 1 9/14/2007
BASICS OF SIX SIGMABASICS OF SIX SIGMA
2. TÜV SÜD South Asia 2 9/14/2007
INTRODUCTION
Participants
• Names
• Roles
• Expectations from this training
3. TÜV SÜD South Asia 3 9/14/2007
What is SixWhat is Six SigmaSigma
4. TÜV SÜD South Asia 4 9/14/2007
What is Six Sigma?
• Sigma is a measurement that indicates how a process is
performing
• Six Sigma stands for Six Standard Deviations (Sigma is the
Greek letter used to represent standard deviation in statistics)
from mean. Six Sigma methodology provides the techniques
and tools to improve the capability and reduce the defects in
any process.
• Six sigma is a fact-based, data-driven philosophy of
improvement that values defect prevention over defect
detection.
5. TÜV SÜD South Asia 5 9/14/2007
What is Six Sigma?
• Philosophy: The philosophical perspective views all works as a
processes that can be defined, measured, analyzed, improved &
controlled (DMAIC). Processes require inputs & produce outputs. If
you control the inputs, you will control the outputs. This is generally
expressed as the y= f (x) concept.
• Set of Tools: Six Sigma as a set of tools includes all the
qualitative and quantitative techniques used by the six sigma expert
to drive process improvement. A few such tools include statistical
process control (SPC), Control charts, failure mode & effects
analysis, process mapping etc.
6. TÜV SÜD South Asia 6 9/14/2007
What is Six Sigma?
• Methodology: This view of Six Sigma recognizes the underlying
and rigorous approach known as DMAIC. DMAIC defines the steps a
Six Sigma practitioner is expected to follow, starting with identifying
the problem and ending with the implementation of long-lasting
solutions. While DMAIC is not only Six Sigma Methodology in use, it
is certainly the most widely adopted and recognized.
• Metrics: In simple terms, Six Sigma quality performance means
3.4 defects per million opportunities.
7. TÜV SÜD South Asia 7 9/14/2007
A little bit of History ….
• Six Sigma was developed by Bill Smith, QM at Motorola
• It’s implementation began at Motorola in 1987
• It allowed Motorola to win the first Baldrige Award in 1988
• Motorola recorded more than $16 Billion savings as a result of Six
Sigma
• Several of the major companies in the world have adopted Six Sigma
since then ….
Texas Instruments, Asea Brown Boveri, AlliedSignal, General Electric,
Bombardier, Nokia Mobile Phones, Lockheed Martin, Sony, Polaroid,
Dupont, American Express, Ford Motor,…..
The Six Sigma Breakthrough Strategy has become a Competitive Tool
8. TÜV SÜD South Asia 8 9/14/2007
Sigma as a Measure of Quality
2 308,537 69.1%
3 66,807 93.3%
4 6,210 99.4%
5 233 99.97%
6 3.4 99.99966%
σσ DPMODPMO RTYRTY
Process
Capability
Process
Capability
Defect Per
Million
Opportunities
Defect Per
Million
Opportunities
Rolled
Throughput Yield
(Long Term)
Rolled
Throughput Yield
(Long Term)
• Sigma is a statistical
unit for measuring
quality
• It is correlated to the
defect rate and the
complexity of the
process / product
• Sigma is a statistical
unit for measuring
quality
• It is correlated to the
defect rate and the
complexity of the
process / product
Six Sigma is a Standard of Excellence.
It means no more than 3.4 Defects per Million Opportunities.
9. TÜV SÜD South Asia 9 9/14/2007
Why SixWhy Six SigmaSigma
10. TÜV SÜD South Asia 10 9/14/2007
The Classical View of Performance
Practical Meaning of “99% Good”
• 20,000 lost articles of mail per hour
• Unsafe drinking water almost 15 minutes each day
• 5,000 incorrect surgical operations per week
• 2 short or long landings at major airports each day
• 200,000 wrong drug prescriptions each year
• No electricity for almost 7 hours each month
3 σ Capability Long Term Yield Historical Standard
93.32%
4 σ Capability Long Term Yield Current Standard
99.38%
6 σ Capability Long Term Yield New Standard
99.99966%
11. TÜV SÜD South Asia 11 9/14/2007
Benchmarking Chart
2 3 4 5 6 7
1,000,000
100,000
10,000
1,000
100
10
1
World Class
Average
Company
Restaurant Bills
Airline Baggage
Handling
Purchased Material
Reject Rate
Payroll Processing
Order Taking
Domestic Airline Flight
Fatality Rate – 0.43 PPM
12. TÜV SÜD South Asia 12 9/14/2007
Six Sigma Results
• Defects are eliminated
• Production and development costs are reduced
• Cycle Times and Inventory Levels are reduced
• Profit Margin and Customer Satisfaction are improved
13. TÜV SÜD South Asia 13 9/14/2007
1 Sigma Shift Improvement Yields
• 20% Margin Improvement
• 12% - 18% Capacity Increase
• 12% Workforce Reduction
• 10% - 30% Capital Reduction
14. TÜV SÜD South Asia 14 9/14/2007
SixSix Sigma & Cost of Poor Quality (COPQ)Sigma & Cost of Poor Quality (COPQ)
15. TÜV SÜD South Asia 15 9/14/2007
Cost of Poor Quality (COPQ) Correlation
• Process Control is pre-requisite for error free
Quality
• COPQ is a result of poorly controlled process
• Process Control can be measured in PPM/Yield
• PPM/Yield measurements are correlated to COPQ
• Process Control is pre-requisite for error free
Quality
• COPQ is a result of poorly controlled process
• Process Control can be measured in PPM/Yield
• PPM/Yield measurements are correlated to COPQ
Six Sigma has shown that the Highest Quality Producer is also
the Lowest Cost Producer
Six Sigma has shown that the Highest Quality Producer is also
the Lowest Cost Producer
16. TÜV SÜD South Asia 16 9/14/2007
What is the Cost Poor Quality
Internal Costs
• Scrap
• Rework/Repair
• Downtime
• Redesign
• Excess Inspection
• Excess Inventory
Internal Costs
• Scrap
• Rework/Repair
• Downtime
• Redesign
• Excess Inspection
• Excess Inventory
External Costs
• Warranty
• Retrofits
• Service Calls
• Recalls
• Lost Sales
• Long Cycle Times
External Costs
• Warranty
• Retrofits
• Service Calls
• Recalls
• Lost Sales
• Long Cycle Times
17. TÜV SÜD South Asia 17 9/14/2007
Components of Cost of Poor Quality
People (Indirect Labor)
• Rework
• Inspection
• Material Handling
• Maintenance
• Setup
• Excess Overtime
• Labor Variance off standard
People (Indirect Labor)
• Rework
• Inspection
• Material Handling
• Maintenance
• Setup
• Excess Overtime
• Labor Variance off standard
Maintenance
• Maintenance
• Repairs
• Rearrangement
Maintenance
• Maintenance
• Repairs
• Rearrangement
Defects
• Scrap
• Rework
• Defects
• Warranty & Recalls
• Returned Good Handling
Defects
• Scrap
• Rework
• Defects
• Warranty & Recalls
• Returned Good Handling
Inventory
• Raw Material Holding Cost
• WIP Holding Cost
• Finished Good Holding Cost
• Obsolescence
• Inventory Shrinkage
Inventory
• Raw Material Holding Cost
• WIP Holding Cost
• Finished Good Holding Cost
• Obsolescence
• Inventory Shrinkage
Premium Freight
• Air Freight
• Expedited Truck Freight
Premium Freight
• Air Freight
• Expedited Truck Freight
18. TÜV SÜD South Asia 18 9/14/2007
COPQ & Sigma / DPMO Relationship
COPQ Sigma DPMO
30-40% of Sales
20-30% of Sales
15-20% of Sales
10-15% of Sales
<10% of Sales
2.0
3.0
4.0
5.0
6.0
308,537
66,807
6,210
233
3.4
Non Competitive
Industry Average
World Class
19. TÜV SÜD South Asia 19 9/14/2007
COPQ & Sigma/Yield Relationship
COPQ Sigma Yield
30-40% of Sales
20-30% of Sales
15-20% of Sales
10-15% of Sales
<10% of Sales
2.0
3.0
4.0
5.0
6.0
5%
93%
99.4%
99.976%
99.999655%
Non Competitive
Industry Average
World Class
20. TÜV SÜD South Asia 20 9/14/2007
Six Sigma Improvement Strategy
Know what is Important to the Customer and to the Business
Reduce Defect Levels by:
1. Reducing the Variation
2. Centering around the Target
Know what is Important to the Customer and to the Business
Reduce Defect Levels by:
1. Reducing the Variation
2. Centering around the Target
Long Term
LSL USL
21. TÜV SÜD South Asia 21 9/14/2007
The Goals of Six Sigma
• Improved Customer Satisfaction
• Defect Reduction/Elimination
• Yield Improvement
• Reduced COPQ
• Improved Process Capability
• Stretch Goals – Target 6 Sigma standards
• Process Understanding
• Constant Measurement of Key Metrics
• Breakthrough Improvement
• Improved Customer Satisfaction
• Defect Reduction/Elimination
• Yield Improvement
• Reduced COPQ
• Improved Process Capability
• Stretch Goals – Target 6 Sigma standards
• Process Understanding
• Constant Measurement of Key Metrics
• Breakthrough Improvement
Six-Sigma Objectives Are Directly and Quantifiably
Connected to the Objective of the Business.
Six-Sigma Objectives Are Directly and Quantifiably
Connected to the Objective of the Business.
22. TÜV SÜD South Asia 22 9/14/2007
A Final Note on Philosophy
Six Sigma is a relentless, constant
Journey of Improvement
Six Sigma is a relentless, constant
Journey of Improvement
23. TÜV SÜD South Asia 23 9/14/2007
Phases of Six SigmaPhases of Six Sigma
24. TÜV SÜD South Asia 24 9/14/2007
Five Phases of Six Sigma
• Define
• Measure
• Analysis
• Improve
• Control
25. TÜV SÜD South Asia 25 9/14/2007
Define Phase Tools
• Voice of Customer (VOC)
• CT Matrix
• Business Matrix
• Pareto Analysis
• Project Charter
• Team Selection (ARMI )
• Top Level Process Map (SIPOC)
26. TÜV SÜD South Asia 26 9/14/2007
Define
Voice of Customer (VOC)Voice of Customer (VOC)
27. TÜV SÜD South Asia 27 9/14/2007
Establishing Customer Focus
• Customer – Anyone internal or external to the
organization who comes in contract with the product
or output of work
• Quality – Performance to the standard expected by
the Customer
• Customer – Anyone internal or external to the
organization who comes in contract with the product
or output of work
• Quality – Performance to the standard expected by
the Customer
28. TÜV SÜD South Asia 28 9/14/2007
The Customer Problem
Customers will not repurchase a company’s product if they are
not satisfied with the current company product.
The stronger the degree of satisfaction with a company’s current
product or service, the greater the likelihood that a customer will
repurchase from the same company.
Customers will not repurchase a company’s product if they are
not satisfied with the current company product.
The stronger the degree of satisfaction with a company’s current
product or service, the greater the likelihood that a customer will
repurchase from the same company.
29. TÜV SÜD South Asia 29 9/14/2007
Variation Is The Enemy in Achieving Customer Satisfaction
• Uncertainty
• Unknown
• Disbelief
• Risk
• Defect Rate
• Uncertainty
• Unknown
• Disbelief
• Risk
• Defect Rate
Variation
30. TÜV SÜD South Asia 30 9/14/2007
What Do You Measure Now?
What Numbers get the most attention in your area?
What Quality Measurements do you have?
Do they have a Customer Focus?
Do they have a Quality Focus?
Do they have an Input Focus?
How do you use these Measures?
What Numbers get the most attention in your area?
What Quality Measurements do you have?
Do they have a Customer Focus?
Do they have a Quality Focus?
Do they have an Input Focus?
How do you use these Measures?
Switching to a Sigma base measurement system
• Measure of Variation and Quality
• Measure of Process Capability
• Measure of Variation and Quality
• Measure of Process Capabilityσ
31. TÜV SÜD South Asia 31 9/14/2007
What Do You Measure Now?
Driving value from the Need – Do interaction
Need Do
Customer Supplier
Customers and Suppliers Exchange Value
Through the Need-Do Interaction
Customers and Suppliers Exchange Value
Through the Need-Do Interaction
32. TÜV SÜD South Asia 32 9/14/2007
Maximizing the Need/Do Interaction
Supplier
Customer
Do
Need
Defects
Quality
Cost
Price
Cycle Time
Delivery
Supplier strives for performance in Cycle Time, Cost and Defects
To Meet
Customers expectations in Delivery, Price and Quality
Supplier strives for performance in Cycle Time, Cost and Defects
To Meet
Customers expectations in Delivery, Price and Quality
33. TÜV SÜD South Asia 33 9/14/2007
Critical To
Matrix
Critical To
Matrix
CT’s
34. TÜV SÜD South Asia 34 9/14/2007
Key Questions
• What does the phrase “critical to satisfaction” mean
in terms of a customer? CTS
• What does the phrase “critical to quality” mean in
terms of a product or service? CTQ
• What does the phrase “critical to delivery” mean in
terms of a product service? CTD
• What does the phrase “critical to cost” mean in terms
of a product or service? CTC
• What does the phrase “critical to process” mean in
terms of a product or service? CTP
• What does the phrase “critical to satisfaction” mean
in terms of a customer? CTS
• What does the phrase “critical to quality” mean in
terms of a product or service? CTQ
• What does the phrase “critical to delivery” mean in
terms of a product service? CTD
• What does the phrase “critical to cost” mean in terms
of a product or service? CTC
• What does the phrase “critical to process” mean in
terms of a product or service? CTP
35. TÜV SÜD South Asia 35 9/14/2007
CT Concept
Quality Delivery PriceNeed
Defect-free Cycle time CostDo
CTQ1 -Critical to Delivery Cost-Critical to Quality -Critical to Cost
CTQ2
CTQ3
Processes
CTP1 -Critical to Process 1
CTP2
36. TÜV SÜD South Asia 36 9/14/2007
CTQ and CTP Characteristics
CTQ1 Output Y1-Critical to Quality
CTQ2
CTQ3
Processes
CTP1 - Input f1 (X)Critical to Process
CTP2
37. TÜV SÜD South Asia 37 9/14/2007
“Critical to” Characteristics
The inherent variation of any dependent variable (Y) is
determined by the variations inherent in each of the
independent variables f(x).
The inherent variation of any dependent variable (Y) is
determined by the variations inherent in each of the
independent variables f(x).
Product or Service
requirement that
impacts Quality,
Delivery or Cost
One of the “vital few”
process variable (x) that
significantly affect Y
Product
Capability
Process
Capability
Probability
of Defects
Probability
of Defects
Probability
of Defects
Critical-to-Quality
characteristic
CTQ1
Defect Opportunity Control Opportunity
Critical-to-Process
characteristic
CTP1
Y = f (X)
38. TÜV SÜD South Asia 38 9/14/2007
The Focus of Six Sigma
Y = f (X)
Y
• Dependent
• Output
• Effect
• Symptom Monitor
Y
• Dependent
• Output
• Effect
• Symptom Monitor
X1…..XN
• Independent
• Input Variables
• Cause
• Problem Control
X1…..XN
• Independent
• Input Variables
• Cause
• Problem Control
39. TÜV SÜD South Asia 39 9/14/2007
CT Matrix Components
Y = f (X1,X2……,XN)
• Translation of customer needs into product or service
requirements in terms of Quality, Delivery and Cost.
• These are the CTQ,CTD and CTC Characteristics
Y
• Breakdown of the processes required to produce the
product or service.
• Identification of projects by understanding the
relationship between product or service requirements
and the processes used.
• Identification of the process parameters f(x1,x2…….xN)
that affect the requirements.
f(X)
40. TÜV SÜD South Asia 40 9/14/2007
Business MetricsBusiness Metrics
41. TÜV SÜD South Asia 41 9/14/2007
Business Metrics
• Following Business Metrics can be used in Six Sigma Projects.
• Defect per Unit (DPU)
• Defects per Million Opportunities (DPMO)
• Throughput Yield (Yield)
• Rolled Throughput Yield (RTY)
• Parts per Million (PPM)
• Following Business Metrics can be used in Six Sigma Projects.
• Defect per Unit (DPU)
• Defects per Million Opportunities (DPMO)
• Throughput Yield (Yield)
• Rolled Throughput Yield (RTY)
• Parts per Million (PPM)
42. TÜV SÜD South Asia 42 9/14/2007
Business Metrics
• An example will illustrate the use of business metrics used in
previous slides.
• Example:
A process produces 40000 pencils. Three types of defect can
occur & number of occurrences are:
• Blurred printing – 36
• Wrong dimensions – 118
• Rolled ends - 11
• An example will illustrate the use of business metrics used in
previous slides.
• Example:
A process produces 40000 pencils. Three types of defect can
occur & number of occurrences are:
• Blurred printing – 36
• Wrong dimensions – 118
• Rolled ends - 11
43. TÜV SÜD South Asia 43 9/14/2007
Business Metrics
• Defect per Unit (DPU):
= Total number of defects / No. of units
= 165 / 40000 = 0.004125
• Throughput Yield (Yield):
= e-DPU = e-0.004125 = 0.996
• Parts per Million (PPM):
= DPU x 10,00,000
= 0.004125 x 10,00,000 = 4125
• Defect per Unit (DPU):
= Total number of defects / No. of units
= 165 / 40000 = 0.004125
• Throughput Yield (Yield):
= e-DPU = e-0.004125 = 0.996
• Parts per Million (PPM):
= DPU x 10,00,000
= 0.004125 x 10,00,000 = 4125
44. TÜV SÜD South Asia 44 9/14/2007
Business Metrics
• Defect per Million Opportunities (DPMO):
To Calculate the number of opportunities, it is necessary to find the
number of ways each defect can occur on each item. In this product,
blurred printing occurs in only one way (the pencil slips in the fixture),
so in the batch there are 40,000 opportunities for this defect to occur.
There are three independent places where dimensions are checked, so
there are 3 x 40,000 = 1,20,000 opportunities for dimensional defects.
Rolled ends can occur at the top and / or the bottom of the pencil, so
there are 40,000 x 2 = 80,000 opportunities for this defect to occur. The
total number of opportunities for defects is 40,000 + 1,20,000 + 80,000
= 2,40,000
DPMO = (Total no. of defects x 10,00,000) / (Total no. of opportunities)
= (165 x 10,00,000) / (2,40,000) = 687.5
• Defect per Million Opportunities (DPMO):
To Calculate the number of opportunities, it is necessary to find the
number of ways each defect can occur on each item. In this product,
blurred printing occurs in only one way (the pencil slips in the fixture),
so in the batch there are 40,000 opportunities for this defect to occur.
There are three independent places where dimensions are checked, so
there are 3 x 40,000 = 1,20,000 opportunities for dimensional defects.
Rolled ends can occur at the top and / or the bottom of the pencil, so
there are 40,000 x 2 = 80,000 opportunities for this defect to occur. The
total number of opportunities for defects is 40,000 + 1,20,000 + 80,000
= 2,40,000
DPMO = (Total no. of defects x 10,00,000) / (Total no. of opportunities)
= (165 x 10,00,000) / (2,40,000) = 687.5
45. TÜV SÜD South Asia 45 9/14/2007
Business Metrics
• Rolled Throughput Yield (RTY):
RTY applies to the yield from a series of processes and is found
by multiplying the individual process yields. If a product goes
through four processes whose yields are 0.994, 0.987, 0.951 &
0.990, then
RTY = 0.994 x 0.987 x 0.951 x 0.990 = 0.924
• Rolled Throughput Yield (RTY):
RTY applies to the yield from a series of processes and is found
by multiplying the individual process yields. If a product goes
through four processes whose yields are 0.994, 0.987, 0.951 &
0.990, then
RTY = 0.994 x 0.987 x 0.951 x 0.990 = 0.924
46. TÜV SÜD South Asia 46 9/14/2007
Exercise-1
• A car manufacturer produces 15000 cars per month . Three
types of defect can occur at different stage & number of
occurrences are:
Initial Assembly – 50 (No. of Opportunities – 4)
Intermediate Assembly – 95 (No. of Opportunities – 2)
Final Assembly – 35 (No. of Opportunities – 3)
Calculate the Defects per Unit (DPU), Defect per Million
Opportunities (DPMO), Throughput Yield & Parts per
Million (PPM).
• A car manufacturer produces 15000 cars per month . Three
types of defect can occur at different stage & number of
occurrences are:
Initial Assembly – 50 (No. of Opportunities – 4)
Intermediate Assembly – 95 (No. of Opportunities – 2)
Final Assembly – 35 (No. of Opportunities – 3)
Calculate the Defects per Unit (DPU), Defect per Million
Opportunities (DPMO), Throughput Yield & Parts per
Million (PPM).
47. TÜV SÜD South Asia 47 9/14/2007
Exercise-2
A B C D
Process B –
Making 100# in
– 80# out 80%
Process A –
Mixing 100# in
– 90# out 90%
Process C –
Converting 100# in
– 90# out 90%
Process D –
Inspection 100# in –
95# out 95%
Calculate the Rolled Throughput Yield (RTY) for the above
process.
Calculate the Rolled Throughput Yield (RTY) for the above
process.
48. TÜV SÜD South Asia 48 9/14/2007
Pareto ChartsPareto Charts
49. TÜV SÜD South Asia 49 9/14/2007
Pareto Charts
• Pareto Diagrams are an essential tools to help prioritize
improvement targets. Paretos usually allow us to focus on the
20% of the problems that causes 80% of the poor
performance.
• Pareto Diagrams are an essential tools to help prioritize
improvement targets. Paretos usually allow us to focus on the
20% of the problems that causes 80% of the poor
performance.
Count 4 2 1 1
Percent 50.0 25.0 12.5 12.5
Cum % 50.0 75.0 87.5 100.0
Damage DentBendChipScratch
9
8
7
6
5
4
3
2
1
0
100
80
60
40
20
0
Count
Percent
Pareto Chart of Damage Interpreting the
results:
Focus on
improvements to
scratches and
chips because
75% of the damage
is due to these
defects.
50. TÜV SÜD South Asia 50 9/14/2007
Pareto Chart (Second Level)
SmudgeOtherScratchPeel
20
15
10
5
0
SmudgeOtherScratchPeel
20
15
10
5
0
Period =Day
Flaws
Count
Period =Evening
Period =Night Period =Weekend
Peel
Scratch
Other
Smudge
Flaws
ParetoChart of Flaws by Period
Interpreting the
results:
The night shift is
producing more
flaws overall. Most of
the problems are due
to scratches and
peels. You may learn
a lot about the
problem if you
examine that part of
the process during
the night shift.
You should drill down using third level, fourth level, etc.,
as far as it makes sense in solving your problem.
51. TÜV SÜD South Asia 51 9/14/2007
Project CharterProject Charter
52. TÜV SÜD South Asia 52 9/14/2007
Project Charter
The Project should be defined through a Problem Description/
Project Objective and include:
• PPM or DPMO Baseline data
• Cost of Poor Quality (COPQ)
• Rolled Throughput Yield (RTY)
• Inventory or
• Other Appropriate Metric
The Project should be defined through a Problem Description/
Project Objective and include:
• PPM or DPMO Baseline data
• Cost of Poor Quality (COPQ)
• Rolled Throughput Yield (RTY)
• Inventory or
• Other Appropriate Metric
53. TÜV SÜD South Asia 53 9/14/2007
SIX SIGMA PROJECT STATUS
Black Belt : Project No. B 004 In Progress
Company/Plant: Product: DW tube 30.08.06
Process : Process Owner : S.H. Pathak 30.08.06
Champion: Master Black Belt:R. K. Arora 22.06.06
Process Team : 10.01.06
Problem Decsription:
Baseline Current Target 1 Improve OEE
1 28471 mtrs/shift 30442 mtrs/shift 47295 mtrs/shift 2 Increase Availability
2 3.52 Lacs 99.06 Lacs/Annum 3
3
3.52 Lacs 99.06 Lacs/Annum
Define Measure Analyze Improve Control D 13.01.06 21.01.06
1 Team MSA 1st level cause Statistical SolutionMonitoring M 03.02.06 18.02.06
2 Metrics Baseline Capability Optimum Solution Standardization A 20.03.06 01.04.06
3 Process Process Map Root Cause Implement SolutionTrain I 20.06.06
4 Charter X Shortlisting Validate Solution Maintain C 20.07.06
Project Status Summary Report
Start Date :
End Date :
S.H. Pathak, Jogesh Shah, M. Prejith
To improve the produtivity on DW Line from 28471 to 47295 mtrs./shift
Status:
Status Date:
Review Date:
Last Review Date:
Arpit Upadhyay
MileStones
1. Target Productivity calculated based on 90% Efficiency and 7.45 hrs working time(Mini clean time
reduced).
Constraints/Special Conditions Preliminary Plan
P
h
a
s
Target
Date
Actual
Date
Status SummaryProject Details
Metrics Y and Complementary Ys
Bundy India Ltd., Baroda
Double Wall tube manufacturing
Vinod Dhar, Sukhdev Narayan
Projected Savings:
Reduce Down time
Business Metric(s):
Z-Score
Critical to Delivery
Critical to Cost
54. TÜV SÜD South Asia 54 9/14/2007
Team Selection (ARMI)Team Selection (ARMI)
55. TÜV SÜD South Asia 55 9/14/2007
Team Selection (ARMI)
The Six Sigma Team shall include following members.
• A R M I
• Approver Resources Members Interested Party
• Champion Maser Black Belt Black Belt Stake Holder
• Executive Green Belt Customer
Process Owner Supplier
The Six Sigma Team shall include following members.
• A R M I
• Approver Resources Members Interested Party
• Champion Maser Black Belt Black Belt Stake Holder
• Executive Green Belt Customer
Process Owner Supplier
56. TÜV SÜD South Asia 56 9/14/2007
Top Level Process Map
(SIPOC)
Top Level Process Map
(SIPOC)
57. TÜV SÜD South Asia 57 9/14/2007
Top Level Process Map
Top Level Process Map – the basic steps or activities that will
produce the output – the essentials, without any extras. Everyone
does these steps – no argument.
– The Top Level Flow Map is the minimum level of
process flow mapping required in order to begin a
FMEA
Top Level Process Map – the basic steps or activities that will
produce the output – the essentials, without any extras. Everyone
does these steps – no argument.
– The Top Level Flow Map is the minimum level of
process flow mapping required in order to begin a
FMEA
58. TÜV SÜD South Asia 58 9/14/2007
Top Level Process Map
List General Input and major Customer Key Output VariablesList General Input and major Customer Key Output Variables
Assembly
AD-SP Air
Dryer Body
INPUTS OUTPUTS
Part to Print
Performance to Spec
Visually acceptable
Leak Free
Identified
Clean
Packaged for use
Consistent standard
Assembly Labor
Procedures
Materials
Equipment, Fixtures
Environment
Cleanliness
Rework
59. TÜV SÜD South Asia 59 9/14/2007
Top Level Process Map
Remember that processes are also affected by elements that feed into
and receive from the process
Remember that processes are also affected by elements that feed into
and receive from the process
Suppliers
Assembly
AD-SP Air
Dryer Body
INPUTS OUTPUTS
Customers
This is known as the SIPOC Model
60. TÜV SÜD South Asia 60 9/14/2007
Basic StatisticsBasic Statistics
61. TÜV SÜD South Asia 61 9/14/2007
Statistics
• The Science of:
– Collecting,
– Describing,
– Analyzing,
– Interpreting data…
And Making Decisions
62. TÜV SÜD South Asia 62 9/14/2007
Type of Data
• Attribute Data (Qualitative)
– Categories like Machine 1, Machine 2, Machine 3
– Yes, No
– Go, No Go or Pass/Fail
– Good/Defective
– On-Time/Late
– Discrete (Count) Data
• # of Maintenance Equipment Failures, # of freight
claims
• Variable of Continuous Data (Quantitative)
– Decimal subdivisions are meaningful
– Cycle Time, Pressure, Conveyor Speed
63. TÜV SÜD South Asia 63 9/14/2007
Measures of Central Tendency
• What is the Middle Value of Distribution?
– Median
• What value represents the distribution?
– Mode
• What value represents the entire distribution?
– Mean ( x )
• What is the best measures of central tendency?
64. TÜV SÜD South Asia 64 9/14/2007
Data Distributions
• Mean: Arithmetic average of a set of values
– Reflects the influence of all values
– Strongly Influenced by extreme values
• Median: Reflects the 50% rank – the center number after a set
of numbers has been sorted from low to high.
– Does not include all values in calculation
– Is “robust” to extreme scores
• Mode: The value or item occurring most frequently in a series
of observations or statistical data.
65. TÜV SÜD South Asia 65 9/14/2007
Measure of Central Tendency - Mean
• Find the value of “n” and “X” for the following 2
distribution.
1 2 3 4 5 6 7 8 9
n = X=
n = X=
Are the 2
Distributions
Same?
What is the
Difference?
66. TÜV SÜD South Asia 66 9/14/2007
Measures of Variability - Spread
• Range “R” = Max – Min is an easy measure of Spread
n = X= R=
1 2 3 4 5 6 7 8 9
n = X= R=
67. TÜV SÜD South Asia 67 9/14/2007
Is Range a good Measure of Variability?
• Find the value of “n”, “X” and “R” for the following 2
distribution.
1 2 3 4 5 6 7 8 9
n = X= R=
n = X= R=
Do the 2
distributions
have same
Variability?
How do we
measure average
variability from
the Center?
68. TÜV SÜD South Asia 68 9/14/2007
Measures of Variability (Spread)
• Calculate Variance & Standard Deviation for these 2
Distributions.
n = X= R= V= S=
1 2 3 4 5 6 7 8 9
n = X= R= V= S=
69. TÜV SÜD South Asia 69 9/14/2007
Measures of Variability
• The Range is the distance between the extreme values of data
set. (Highest – Lowest)
• The Variance(S2) is the Average Squared Deviation of each
data point from the Mean.
• The Standard Deviation (s) is the Square Root of the Variance.
• The range is more sensitive to outliers than the variance.
• The most common and useful measure of variation is the
Standard Deviation.
70. TÜV SÜD South Asia 70 9/14/2007
Sample Statistics vs. Population Parameters
EstimateStatistics Parameters
X = Sample Mean
S = Sample Standard
Deviation
= Population Mean
= Population Standard
Deviation
µ
σ
71. TÜV SÜD South Asia 71 9/14/2007
Statistical Calculations (Sample)
n
X
n
i
Xi∑=
= 1
__
Mean Variance
1
1 )(2
2
__
−
=
∑= −
n
S
n
i XXi
2
__
/ dR=σ
Standard Deviation
N d2
2 1.128
3 1.693
4 2.059
6 2.326
Standard Deviation
1
1 )( 2
__
−
=
∑= −
n
S
n
i XXi
72. TÜV SÜD South Asia 72 9/14/2007
Statistical Calculation (Population)
Mean Variance
n
n
i XXi
∑= −
= 1 )(2
2
__
σ
__
X≈µ
Standard Deviation
n
n
i XXi
∑= −
= 1 )( 2
__
σ
73. TÜV SÜD South Asia 73 9/14/2007
Probability Density Functions (Shape)
• The Shape of the distribution is shown by the probability
Density Function.
• The Y axis is Probability Density and the X axis is Data Values
• Area Under the curve Represents the probability of finding a
data point between 2 Values.
• Probability Density Function Defines the interrelation between
the center and the spread.
• The distributions with known function are called Parametric
and those with unknown functions are called Non-Parametric
74. TÜV SÜD South Asia 74 9/14/2007
Distribution for a Targeted Process
• If an Expert Marksman is Shooting, what place has the
Highest Probability of getting a hit?
75. TÜV SÜD South Asia 75 9/14/2007
Distribution for a Targeted Process
76. TÜV SÜD South Asia 76 9/14/2007
Properties of Normal Distribution
• Normal Distribution is Symmetric
– Has equal No. of Points on both Sides
– Mean Median and Mode Coincide
• Normal Distribution is Infinite
– The chance of finding a point outside tolerance is not
absolutely Zero.
– We need to define a practical Limit of the Process
77. TÜV SÜD South Asia 77 9/14/2007
Properties of Normal Distribution
• Normal Curve & Probability Areas
68 %
95 %
99.73 %
-4 -3 -2 -1 0 1 2 3 4
Output σ
78. TÜV SÜD South Asia 78 9/14/2007
Let’s Summarize…
• We need data to study, predict and improve the processes.
• Data may be Variable or Attribute.
• To understand a data distribution, we need to know its
Center, Spread and Shape.
• Normal Distribution is the most common but not the only
shape.
79. TÜV SÜD South Asia 79 9/14/2007
Exercise-3
• Calculate the Mean, Median, Range, Variance & Standard
Deviation for following data set.
2, 2, 5, 6, 7, 9, 9
• Calculate the Mean, Median, Range, Variance & Standard
Deviation for following data set.
2, 2, 5, 6, 7, 9, 9
80. TÜV SÜD South Asia 80 9/14/2007
Capability AnalysisCapability Analysis
81. TÜV SÜD South Asia 81 9/14/2007
Do we NEED Metrics and Baseline?
• If we cannot measure it, we cannot improve it.
• Metrics Help us understand where we stand
• Metrics help us move in the right direction.
• Metrics provide objectivity to peoples’ feelings and
perceptions.
• Metrics provide a common language and help us share
information without subjectivity, biases and confusions.
• Metrics help us set a common goal.
• If we cannot measure it, we cannot improve it.
• Metrics Help us understand where we stand
• Metrics help us move in the right direction.
• Metrics provide objectivity to peoples’ feelings and
perceptions.
• Metrics provide a common language and help us share
information without subjectivity, biases and confusions.
• Metrics help us set a common goal.
82. TÜV SÜD South Asia 82 9/14/2007
Baseline
• When we start a long journey, we look at the mile stones to
find out how far we have come…
• But, suppose, we did not know where we started, can we tell
how far we have come?
• Base line sets a starting point of our journey.
• It is the first measure and tells us about as-is State.
• It also helps us to set targets and scope out project.
• When we start a long journey, we look at the mile stones to
find out how far we have come…
• But, suppose, we did not know where we started, can we tell
how far we have come?
• Base line sets a starting point of our journey.
• It is the first measure and tells us about as-is State.
• It also helps us to set targets and scope out project.
83. TÜV SÜD South Asia 83 9/14/2007
What do we need to Measure?
• We need to measure whatever is important to the project.
• We need to track the following metrics
1. Y
2. Business Metrics
3. Z Score
• We need to measure whatever is important to the project.
• We need to track the following metrics
1. Y
2. Business Metrics
3. Z Score
84. TÜV SÜD South Asia 84 9/14/2007
Why we need to Measure - Y
• Y is the metric (CTQ/CTD/CTC) that we are focusing on. E.g.
– PPM, No. of mistakes in a form, Dia Variation, Power
Factor, etc.
– Cycle Time, Lead Time, Inventory Level etc.
– Maintenance cost, Utility cost etc.
• Y is the metric (CTQ/CTD/CTC) that we are focusing on. E.g.
– PPM, No. of mistakes in a form, Dia Variation, Power
Factor, etc.
– Cycle Time, Lead Time, Inventory Level etc.
– Maintenance cost, Utility cost etc.
85. TÜV SÜD South Asia 85 9/14/2007
What we need to Measure - Business
• Business metrics are the justification for taking up a six
sigma project and are required for management buy-in.
• Since Management is committing resources to the project, it
needs to know what will be the business impact.
• One or more business metrics are required to maintain
management focus on the project. Or else, it will be Six Sigma
for the sake of Six
• Business metrics are best expressed in terms of money but
could be any that give the big picture e.g.
• COPQ, Customer Satisfaction Index, RTY exc.
• Business metrics are the justification for taking up a six
sigma project and are required for management buy-in.
• Since Management is committing resources to the project, it
needs to know what will be the business impact.
• One or more business metrics are required to maintain
management focus on the project. Or else, it will be Six Sigma
for the sake of Six
• Business metrics are best expressed in terms of money but
could be any that give the big picture e.g.
• COPQ, Customer Satisfaction Index, RTY exc.
86. TÜV SÜD South Asia 86 9/14/2007
What we need to Measure – Z Score
• Z Score is the sigma level of the process.
• This is a common metric.
• It is used as common scale for measuring the extent of
improvements.
• It also helps us benchmark against world class processes.
• A world class or Six Sigma process operates at 6 Sigma
Levels or a Z Score = 6
• Z Score is the sigma level of the process.
• This is a common metric.
• It is used as common scale for measuring the extent of
improvements.
• It also helps us benchmark against world class processes.
• A world class or Six Sigma process operates at 6 Sigma
Levels or a Z Score = 6
87. TÜV SÜD South Asia 87 9/14/2007
While Setting The Metrics, Remember…
• The metrics Should be relevant to the Problem Statement.
• If both Variable and Attribute Metrics are available, prefer
Variable metric.
• If your metric is a lean metric (inventory, cycle time etc.) first
consider Lean tools.
• Sometimes counter-metrics are required to ensure proper
output.
– E.g. While Improving the metric – “Cycle Time”, Counter-
metric – “Defect rate” needs to be tracked so that the
cycle time is not reduced at the expense of Quality
• The metrics Should be relevant to the Problem Statement.
• If both Variable and Attribute Metrics are available, prefer
Variable metric.
• If your metric is a lean metric (inventory, cycle time etc.) first
consider Lean tools.
• Sometimes counter-metrics are required to ensure proper
output.
– E.g. While Improving the metric – “Cycle Time”, Counter-
metric – “Defect rate” needs to be tracked so that the
cycle time is not reduced at the expense of Quality
88. TÜV SÜD South Asia 88 9/14/2007
The Z - Transform
σ
__
XX
Z
−
=
• Z – Transform is used for a
Normally Distributed process.
• It expresses how far value X is
from the Center in terms of
σ
• E.g. for a normal distribution
with =70 and σ=10, a the
value X=30 has z=(30-70)/10=-
4
• In other words the point X=30
is 4σ away From the mean on
–ve Side
• Z – Transform is used for a
Normally Distributed process.
• It expresses how far value X is
from the Center in terms of
σ
• E.g. for a normal distribution
with =70 and σ=10, a the
value X=30 has z=(30-70)/10=-
4
• In other words the point X=30
is 4σ away From the mean on
–ve Side
__
X
__
X
σZ
X X
89. TÜV SÜD South Asia 89 9/14/2007
The Z - Score
σ
__
XSL
Z
−
=• If X was substituted by the
Tolerance Limits (LSL & USL),
Z will tell how many σs are
there between Tolerance
Limits and the center of the
process.
• This is the Sigma level or the
Z Score
• E.g. for normal distribution
with =70 and σ=10, LSL=30,
ZL=(30-70)/10=-4
• For USL=100,Z=3
• If X was substituted by the
Tolerance Limits (LSL & USL),
Z will tell how many σs are
there between Tolerance
Limits and the center of the
process.
• This is the Sigma level or the
Z Score
• E.g. for normal distribution
with =70 and σ=10, LSL=30,
ZL=(30-70)/10=-4
• For USL=100,Z=3
30 70 100
σ4 σ3
__
X
90. TÜV SÜD South Asia 90 9/14/2007
But Wait….
• Every time we make a batch, do we get the SAME amount of
Variation?
• Why does the process VARY from batch to batch?
• Can we prevent Batch to Batch variation TOTALLY?
• Data from WHICH of these batches should be taken for
calculating Z Score?
• How much data is SUFFICENT?
• If I get different Z Scores for data collected at different times
which of them is CORRECT?
• Every time we make a batch, do we get the SAME amount of
Variation?
• Why does the process VARY from batch to batch?
• Can we prevent Batch to Batch variation TOTALLY?
• Data from WHICH of these batches should be taken for
calculating Z Score?
• How much data is SUFFICENT?
• If I get different Z Scores for data collected at different times
which of them is CORRECT?
91. TÜV SÜD South Asia 91 9/14/2007
Well
• Every time we make a batch, we may NOT get the same
amount of Variation.
• The process varies from batch to batch due to MEAN SHIFT
over a period of time.
• We can MINIMIZE this but not prevent it.
• This means that process will have more variation in LONG
TERM when compared to SHORT TERM variation.
• A process is Six Sigma process when the short term Z Score
is 6
• Every time we make a batch, we may NOT get the same
amount of Variation.
• The process varies from batch to batch due to MEAN SHIFT
over a period of time.
• We can MINIMIZE this but not prevent it.
• This means that process will have more variation in LONG
TERM when compared to SHORT TERM variation.
• A process is Six Sigma process when the short term Z Score
is 6
92. TÜV SÜD South Asia 92 9/14/2007
Shot Term vs Long Term
• Mean of a process shifts over
a period of time.
• This Shift is empirically
observed to be 1.5
• So Zlt = Zst-1.5 Approx.
• And Zst =Zlt+1.5 Approx.
• A Six Sigma Process has Zst
=6
• So a Six Sigma Process has
Zlt =4.5
• Mean of a process shifts over
a period of time.
• This Shift is empirically
observed to be 1.5
• So Zlt = Zst-1.5 Approx.
• And Zst =Zlt+1.5 Approx.
• A Six Sigma Process has Zst
=6
• So a Six Sigma Process has
Zlt =4.5
Mean Shift
σ5.1=
LSL Xlt Xst USL
σ5.4=Zlt
σ6=Zlt
93. TÜV SÜD South Asia 93 9/14/2007
Capability vs Performance
• Zst represents the CAPABILITY of the process whereas Zlt
represents the PERFORMANCE over a period of time
• What is Capability?
– Inherent ability
– Due to Common Causes of Variation
• What is Performance?
– Final Output
– Due to Common as well as Special Causes of variation
• Zst represents the CAPABILITY of the process whereas Zlt
represents the PERFORMANCE over a period of time
• What is Capability?
– Inherent ability
– Due to Common Causes of Variation
• What is Performance?
– Final Output
– Due to Common as well as Special Causes of variation
94. TÜV SÜD South Asia 94 9/14/2007
Causes of Variation
• Common Cause of Variation
– Are an intrinsic part of the process
– Give consistent Variation
– Affect each data point equally
– Are reflected in Unit to Unit Variation
• Special Causes of Variation
– Are usually outside the process
– Appear some time and not at the other times
– Affect some data points more than others
– Are reflected in Time to time Variations
• Common Cause of Variation
– Are an intrinsic part of the process
– Give consistent Variation
– Affect each data point equally
– Are reflected in Unit to Unit Variation
• Special Causes of Variation
– Are usually outside the process
– Appear some time and not at the other times
– Affect some data points more than others
– Are reflected in Time to time Variations
95. TÜV SÜD South Asia 95 9/14/2007
Causes of Variation - Examples
• Common Cause of Variation
– Usual Traffic on Road
– Usual Play in the Slides of machine
– Human Attentiveness
– Variation in dimensions in a lot manufactured together.
• Special Causes of Variation
– Accident on Road
– Excess Play in Slide due to wear over time.
– Illness
– Variation due to Change in lot or supplier.
• Common Cause of Variation
– Usual Traffic on Road
– Usual Play in the Slides of machine
– Human Attentiveness
– Variation in dimensions in a lot manufactured together.
• Special Causes of Variation
– Accident on Road
– Excess Play in Slide due to wear over time.
– Illness
– Variation due to Change in lot or supplier.
96. TÜV SÜD South Asia 96 9/14/2007
Stability
• When the variation is only due to common causes, the process is said to be
Stable.
• A Stable Process has predictable variation.
• Special causes disturb the stability of the process due to which the
Variation becomes unpredictable.
• A Stable process is also called a process in “Control”
• When the variation is only due to common causes, the process is said to be
Stable.
• A Stable Process has predictable variation.
• Special causes disturb the stability of the process due to which the
Variation becomes unpredictable.
• A Stable process is also called a process in “Control”
252321191715131197531
7.5
5.0
2.5
0.0
-2.5
-5.0
Sample
SampleMean __
X=0.63
UCL=5.98
LCL=-4.73
1
1
1
Xbar Chart of Unstable
252321191715131197531
5
4
3
2
1
0
-1
-2
-3
-4
Sample
SampleMean
__
X=0.442
UCL=4.700
LCL=-3.817
Xbar Chart of Stable
97. TÜV SÜD South Asia 97 9/14/2007
Capability vs Stability
• Capability has a meaning only when a process is stable.
• If a process is out of control, first we need to stabilize the
process.
• Improvement in the inherent variation can be made only
when the process is stable.
• Control Charts are used to study stability
• The first job of Six Sigma practitioner is to Identify and
remove Special Causes of Variation.
• Once the process is made predictable, the next job is to
identify the causes of inherent variation and remove them.
• Capability has a meaning only when a process is stable.
• If a process is out of control, first we need to stabilize the
process.
• Improvement in the inherent variation can be made only
when the process is stable.
• Control Charts are used to study stability
• The first job of Six Sigma practitioner is to Identify and
remove Special Causes of Variation.
• Once the process is made predictable, the next job is to
identify the causes of inherent variation and remove them.
98. TÜV SÜD South Asia 98 9/14/2007
Calculating Capability
•Capability Can be defined as Tolerable Variation
Process Variation
σ1X +
σ3X +
σ2X +
LSL USL
σ6
LSLUSL
Cp
−
= σ6
T
Cp =
99. TÜV SÜD South Asia 99 9/14/2007
Calculating Capability
• Marginal Capability
σ1X +
LSL USL
σ3X +
σ2X +
σ6
T
Cp =
σ
σ
6
6
=Cp 1=Cp
100. TÜV SÜD South Asia 100 9/14/2007
Calculating Capability
• Six Sigma Capability
LSL USL
σ3 σ3
σ6X +
σ3X +
σ6
T
Cp =
σ
σ
6
12
=Cp 2=Cp
101. TÜV SÜD South Asia 101 9/14/2007
Calculating Capability
• Calculate Cp from Upper & Lower Side
LSLX −
___
σ3
___
LSLX
CpL
−
=
___
XUSL −
σ3
___
XUSL
CpU
−
=
0 2 4 6 8 10 12 14 16 18 20
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
σσ 3
,
3
____
XUSLLSLX
MinCp K
103. TÜV SÜD South Asia 103 9/14/2007
Capability vs Performance
σ6
LSLUSL
Cp
−
=
σ6
LSLUSL
Pp
−
=
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
σσ 3
,
3
____
XUSLLSLX
MinCpK
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
σσ 3
,
3
____
XUSLLSLX
MinPpK
• If the formula are same, what is the difference?
• The difference is in Sigma calculation!
• Sigma in Capability covers Short Term Variation.
• Sigma in Performance covers Long Term Variation.
• How is the Data collection Different?
• If the formula are same, what is the difference?
• The difference is in Sigma calculation!
• Sigma in Capability covers Short Term Variation.
• Sigma in Performance covers Long Term Variation.
• How is the Data collection Different?
104. TÜV SÜD South Asia 104 9/14/2007
Capability Calculation
• Capability covers short term variation.
• It requires data collected over short period of time.
• Small Subgroups of data (Generally 3-7 sample size) are
taken.
• Data points within a subgroup need to be of consecutive
output.
• Many subgroups are collected over a period of time.
• The average variation within a subgroup is considered to be
present the inherent Variation.
• Sigma is calculated using
• Should be used only when process is stable
• Capability covers short term variation.
• It requires data collected over short period of time.
• Small Subgroups of data (Generally 3-7 sample size) are
taken.
• Data points within a subgroup need to be of consecutive
output.
• Many subgroups are collected over a period of time.
• The average variation within a subgroup is considered to be
present the inherent Variation.
• Sigma is calculated using
• Should be used only when process is stable
2
__
d
R
=σ
105. TÜV SÜD South Asia 105 9/14/2007
Performance Calculation
• Performance covers long term variation.
• It required data collected over long period of time.
• Data should represent more than one day, if possible more
than a month of variation.
• If Data points are too many, one may randomly sample the
data to represent all days and batches.
• The Root Mean Square variation is considered to to
represent the Overall Variation.
• Sigma is calculated using
• Should be used only when data is available over a long
period of time.
• Performance covers long term variation.
• It required data collected over long period of time.
• Data should represent more than one day, if possible more
than a month of variation.
• If Data points are too many, one may randomly sample the
data to represent all days and batches.
• The Root Mean Square variation is considered to to
represent the Overall Variation.
• Sigma is calculated using
• Should be used only when data is available over a long
period of time.
1
2__
−
⎟
⎠
⎞
⎜
⎝
⎛
−
=
n
Xxi
σ
106. TÜV SÜD South Asia 106 9/14/2007
Capability, Performance and Z Score
• If the process is Stable,
Collect Short term data
using Subgroups,
Calculate Cpk and
Zst=3xCpk
• If the process is Unstable
or Stability is not known,
Collect Long term data by
random sampling,
Calculate Ppk and
Zlt=3xPpk. Convert it into
Short Term bench mark Z
by Zst=Zlt+1.5
• If the process is Stable,
Collect Short term data
using Subgroups,
Calculate Cpk and
Zst=3xCpk
• If the process is Unstable
or Stability is not known,
Collect Long term data by
random sampling,
Calculate Ppk and
Zlt=3xPpk. Convert it into
Short Term bench mark Z
by Zst=Zlt+1.5
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
−−
=
σσ
σσ
σσ
____
____
____
,
3
,
3
3
,
3
XUSLLSLX
MinZ
XUSLLSLX
MinPp
XUSLLSLX
MinCp
K
K
So
ZLT=3 X Ppk
&
ZST=3 X CpK
107. TÜV SÜD South Asia 107 9/14/2007
Z Score Calculation Road Map
Attribute Y
Calculate
DPU
Calculate
Zlt
Calculate
Zst
Un-Stable
Process/
Not Known
Select Y
Variable Y
Normal Non-Normal
Stable
Process
Non
Normal
Capability
Calculation
Zst is the baseline Z score
108. TÜV SÜD South Asia 108 9/14/2007
Exercise-4
• Calculate the Z Score for the following processes.
1. Data of Length in machining process has been collected. The
required length is 555 max. The Process has been behaving
consistently for last 6 months. The data was collected for the
first 5 pieces for each of last 35 batches. The mean of the data
is 540.26857 & Standard deviation is 10.38606.
2. Data for Cycle Time of a molding process has been collected.
The specification is 60-65 sec. The Process has been
behaving erratically for last 8 months. The data collected for
the first 5 pieces for each of last 30 shifts. The mean of the
data is 64.03827 & Standard deviation is 0.54618.
• Calculate the Z Score for the following processes.
1. Data of Length in machining process has been collected. The
required length is 555 max. The Process has been behaving
consistently for last 6 months. The data was collected for the
first 5 pieces for each of last 35 batches. The mean of the data
is 540.26857 & Standard deviation is 10.38606.
2. Data for Cycle Time of a molding process has been collected.
The specification is 60-65 sec. The Process has been
behaving erratically for last 8 months. The data collected for
the first 5 pieces for each of last 30 shifts. The mean of the
data is 64.03827 & Standard deviation is 0.54618.
109. TÜV SÜD South Asia 109 9/14/2007
Implementation of Six SigmaImplementation of Six Sigma
110. TÜV SÜD South Asia 110 9/14/2007
Phases of Breakthrough Strategy
Phase II: Process Analysis
Phase I: Process Measurement
Phase III: Process Improvement
Phase IV: Process Control
Characterization
Optimization
111. TÜV SÜD South Asia 111 9/14/2007
Phase of Breakthrough Strategy
Phase I: Process Measurement
• Identify KPIV’s and KPOV’s on Process Map/FMEA
• Establish Measurement System Capability
• Establish Process Capability Baseline
Phase I: Process Measurement
• Identify KPIV’s and KPOV’s on Process Map/FMEA
• Establish Measurement System Capability
• Establish Process Capability Baseline
Phase II: Process Analysis
• Update Process Map, FMEA, Control Plan & Capability
• Identify Critical Input Variable
• Analyze Process data using Six Sigma Tools
Phase II: Process Analysis
• Update Process Map, FMEA, Control Plan & Capability
• Identify Critical Input Variable
• Analyze Process data using Six Sigma Tools
Phase III: Process Improvement
• Verify and optimize Critical Input Variables
• Identify and Test Proposed Solutions
• Implement Solutions and Confirm Results
Phase III: Process Improvement
• Verify and optimize Critical Input Variables
• Identify and Test Proposed Solutions
• Implement Solutions and Confirm Results
Phase IV: Process Control
• Standardization / Mistake Proofing
• Implement Process Controls and Verify Effectiveness
• Monitor Process by Control Plan—HOLD the Gains
Phase IV: Process Control
• Standardization / Mistake Proofing
• Implement Process Controls and Verify Effectiveness
• Monitor Process by Control Plan—HOLD the Gains
112. TÜV SÜD South Asia 112 9/14/2007
Phase I: Process Measurement
Plan Project and Identify Key Process Metrics, Inputs and Outputs
• Project Selection Justification
• Business Metrics (RTY, COPQ, PPM)
• Process Mapping / Data Collection Process/Control Plan
• Cause & Effect Matrix / FMEA
Quantify Variation on Vital Few Variation Sources
• 3 Level Pareto charts
• Vital Few Variation Sources
• Gage Studies (GR&R)
Perform Short-term Capability Study
• Short-term and Long-term Capability
– CpK, PpK
– SPC Charts
– Sigma (Z) Calculations
113. TÜV SÜD South Asia 113 9/14/2007
Phase II: Process Analysis
Update Project Baseline and Status
• Project Status From
• Metric Graph with Goal Line
• Process Map / FMEA / Control Plan
Identify Root Causes of Variation
• Multi-Vari and Horizontal Root Cause Charts
• SPC Charts
• Fishbone Chart, Documenting Input Variables
• Hypothesis Tests to Verify Critical Input Variables
• List of Critical Input Variables
• List of Containment Actions
114. TÜV SÜD South Asia 114 9/14/2007
Phase III: Process Improvement
Update Project Baseline and Status
• Project Status From
• Metric Graph with Goal Line
• Process Map / FMEA / Control Plan
Optimize Process
• Test and Verify Critical Input Variables
• Use Statistical Tools to Optimize Process
• Identify, Plan and Test Proposed Solutions
• Select Solutions and Confirm Results
• Implement Solutions and Improvement Plans
• Document Improvement Plans and Actions
115. TÜV SÜD South Asia 115 9/14/2007
Phase IV: Process Control
Update Project Baseline and Status
• Project Status From
• Metric Graph with Goal Line
• Process Map / FMEA / Control Plan
Optimize Process
• Each Standardization and Mistake Proofing
• Implement Process Controls
• Verify Effectiveness of Process Controls and System Improvements
• Monitor Process by Control Plan
• HOLD and GAINS
116. TÜV SÜD South Asia 116 9/14/2007
Statistical Problem Solving
Physical
Problem
Physical
Solution
Statistical
Problem
Statistical
SolutionC
A
MD
I
• Define the Problem in terms of
Y and Probable Xs
• Measures the Extent of Problem
• Shortlist the Xs for analyses
• Collect Data
• Eliminate Xs that are not
important
• Finalize Xs for Optimization
• Confirm the short listed Xs
• Find Y=f(X) or Best case for the
selected Xs
• Identify Physical controls based
on constraints
• Verify and Maintain new
controls
117. TÜV SÜD South Asia 117 9/14/2007
THANK YOUTHANK YOU