Design For Six Sigma e Innovation Training for Financial Services
Event Properties
Event Date | 26-02-2018 9:30 am |
Event End Date | 30-03-2018 3:00 pm |
Registration Start Date | 01-10-2017 12:00 am |
Available place | 9 |
Cut off date | 12-03-2018 12:00 am |
Individual Price | 6250,00€ |
Location | Sheraton Diana Majestic, Milano |
Lean in Finance in partnership with SSA & Company, offer Design For Six Sigma Certification in a two-week, highly refined and innovative program that steps beyond traditional Black Belt training. Our two-week Design For Six Sigma Certification curriculum teaches participants how to learn and apply techniques related to capturing the Voice of the Customer (VOC), requirements flow-down, process capability rollup, balanced scorecards, continuous and discrete simulation, experimental design, and invention technologies.
The SSA Difference
Our two-week Design For Six Sigma Certification curriculum teaches participants how to learn and apply techniques related to capturing the Voice of the Customer (VOC), requirements flow-down, process capability rollup, balanced scorecards, continuous and discrete simulation, experimental design, and invention technologies. In addition, the Design for Six Sigma Certification offering includes 20 hours of project execution support. The two weeks of training are separated by a five- to ten-week application of Breakthrough Design for the participants’ individual projects. During the application weeks, DFSS Black Belts are supported and mentored by an assigned Project Champion, who also reviews and critiques the DFSS Black Belts results along with the instructor and classmates.
Who Should Take This Course?
DFSS Certification course participants must be certified Black Belts and are required to come to class with at least one project that will be completed over a 12- to 18-month period.
Benefits/Outcomes:
-Ability to lead teams in creating new products, processes, or services to achieve high levels of performance
-Ability to lead teams in overhauling existing products, processes, or services to achieve high levels of performance
-Ability to collect precise and detailed customer requirements, translate those requirements into design parameters, then optimize settings for those design parameters through experimentation and simulation
-Ability to lead and/or facilitate innovative projects while developing robust breakthrough designs for products, services, and processes that perform flawlessly on launch
Course Requirements:
Attendance at all 10 days of classroom training
One or more projects that can be completed within 12 to 18 months from the start of training
Black Belt Certification (attended training and completed at least two projects); proficiency in the core Lean Six Sigma tools
Windows-based laptop computer with a CD-ROM (participant must have access to the laptop throughout the training)
Minitab v.16 (loaded on laptop prior to attending training)
Design for Six Sigma Certification Price (Euro): €6,250
Registration Fee Includes:
Ten days of classroom training (two five-day sessions separated by five to ten weeks)
24 hours of project execution support, to be delivered remotely unless otherwise agreed upon; must be used within 18 months from the start of training
A set of electronic documentation covered during the training
The Design For Six Sigma Memory Jogger
Certificate of Participation for individuals who complete training
Certification for participants who meet DFSS certification requirements
Daily continental breakfast, lunch, refreshments, and snacks
DFSS Certification Requirements:
-Ten days of classroom training
-Completion of two projects
-Complete DFSS BB Test with a Score ≥ 85%
Design for Six Sigma
Program Description
Training Orientation
Topic Description
Excel Orientation - Explore the Excel software package
Statistical Software Orientation - Explore Minitab/JMP software packages
Simulator Orientation - Explore the Process Simulator
Breakthrough Vision
Topic Description
Content Overview - Understand the nature, purpose, and drivers of Six Sigma
Driving Need - Identify the needs that underlie a Six Sigma initiative
Customer Focus - Explain why focusing on the customer is essential to business success
Core Beliefs - Contrast the core beliefs of Six Sigma to conventional practices
Deterministic Reasoning - Describe a basic cause-and-effect relationship in terms of Y=f(X)
Leverage Principle - Relate the principle of leverage to an improvement project
Tool Selection - Identify the primary family of analytical tools used in Six Sigma work
Performance Breakthrough - Describe the underlying logic of the DMAIC improvement process
Business Principles
Topic Description
Quality Definition - Articulate the idea of quality in terms of value entitlement
Value Proposition - Define the primary components of value and their key elements
Metrics Reporting - Recognize the need for installing and reporting performance metrics
BOPI Goals - Recognize the need for cascading performance metrics
Underpinning Economics - Describe the relationship between quality and cost
Third Generation - Differentiate between the first, second and third generations of Six Sigma
Success Factors - Identify the primary success factors related to a Six Sigma deployment
Process Management
Topic Description
Performance Yield - Explain why final yield is often higher than first-time yield
Hidden Processes - Describe the non-value added component of a process
Measurement Power - Describe the role of measurement in an improvement initiative
Establishing Baselines - Explain why performance baselines are essential to realizing improvement
Performance Benchmarks - Explain how a benchmarking chart can be used to assess quality performance
Defect Opportunity - Understand the nature of a defect opportunity and its role in metrics reporting
Process Models - Define the key features of a Six Sigma performance model
Process Capability - Identify the primary indices of process capability
Design Complexity - Describe the impact of complexity on product and service quality
Product Reliability - Explain how process capability can impact product reliability
Installation Guidelines
Topic Description
Deployment Planning - Understand the elements of Deployment Planning
Deployment Timeline - Understand the elements of a Deployment Timeline
CXO Role - Receive insight on how key decisions are addressed
Champion Role - Define the operational role of a Six Sigma Champion and highlight key attributes
Black Belt Role - Define the operational role of a Six Sigma Black Belt and highlight key attributes
Green Belt Role - Define the operational role of a Six Sigma Green Belt and highlight key attributes
White Belt Role - Define the operational role of a Six Sigma White Belt and highlight key attributes
Application Projects - Describe the purpose of Six Sigma Application Projects and how such projects are executed
DFSS Principles - See how product design can affect yield and performance
PFSS Principles - Have an understanding of the Process For Six Sigma Criteria
MFSS Principles - Understand how Managing For Six Sigma works
Application Projects
Topic Description
Project Description - Understand how to fully define a Six Sigma application project
Project Overview - Provide an overview of the key elements that characterizes an application project
Project Guidelines - Explain how to establish project selection guidelines
Project Scope - Explain how to properly scope an application project
Project Leadership - Recognize the actions that must occur to ensure successful project leadership
Project Teams - Form a project team that is capable of supporting Six Sigma applications
Project Financials - Understand the role of project financials in supporting deployment success
Project Management - Explain how application projects are best managed to achieve maximum results
Project Payback - Understand the driving need for establishing project paybacks
Project Milestones - Identify the primary milestones associated with a successful Six Sigma deployment
Project Charters - Understand the role of project charters and how they are used to guide implementation
Value Focus
Topic Description
Value Creation - Define the idea of value and explain how it can be created
Recognize Needs - Recognize the power of need fulfillment and how it links to value creation
Define Opportunities - Understand how to define opportunities that lead to the creation of value
Measure Conditions - Identify and evaluate the conditions that underlies improvement opportunity
Analyze Forces - Explain how the underlying forces are identified and leveraged to create beneficial change
Improve Settings - Establish optimal settings for each of the key forces that underpins beneficial change
Control Variations - Discuss how unwanted variations can mask the pathway to breakthrough
Standardize Factors - Understand the role and importance of standardized success factors
Integrate Lessons - Explain how key lessons learned can be merged into a set of best practices
Application Example - Understand how the breakthrough process can be applied to everyday life
Lean Practices
Topic Description
Lean Thinking - Comprehend the underlying logic of lean thinking
Constraint Theory - Explain how constraint theory is related to value creation
Continuous Flow - Describe the operational ideas that underpins continuous flow
Pull Systems - Contrast the operation of a push system to that of a pull system
Visual Factory - Explain the role of a visual factory during improvement efforts
Kanban System - Describe how a Kanban system can improve process cycle-time
PokaYoke System - Understand how PokaYoke systems can lead to quality improvement
6S System - Explain how the 6S system can contribute to process efficiency
SMED System - Define the basic elements of an SMED system
7W Approach - Describe how the 7W approach can be used to solve problems
6M Approach - Explain how the 6M approach is used to identify sources of causation
Quality Tools
Topic Description
Variable Classifications - Define the various types of variables commonly encountered during quality improvement
Measurement Scales - Describe each of the four primary scales of measure and their relative power
Problem Definition - Characterize the nature of a sound problem statement
Focused Brainstorming - Explain how focused brainstorming is used to facilitate improvement efforts
Process Mapping - Understand how to define the flow of a process and map its operations
SIPOC Diagram - Describe the nature and purpose of an SIPOC diagram
Force-Field Analysis - Utilize force field analysis to solve problems
Matrix Analysis - Understand how matrices are created and used to facilitate problem solving
C&E Analysis - Explain how C&E matrices can be used to solve quality problems
Failure Mode Analysis - Understand how FMEA is used to realize process and design improvements
Performance Sampling - Explain how to design and implement a sampling plan
Check Sheets - Understand how check sheets can be used for purposes of data collection
Analytical Charts - Identify the general range of analytical charts that can be used to assess performance
Pareto Charts - Explain how Pareto charts can be used to isolate improvement leverage
Run Charts - Utilize run charts to assess and characterize time-based process data
Multi-Vari Charts - Define the major families of variation and how they can be graphed
Correlation Charts - Utilize a correlation chart to illustrate the association between two variables
Frequency Tables - Explain how to construct and interpret a frequency table
Performance Histograms - Construct and interpret a histogram and describe several purposes
Basic Probability - Understand basic probability theory and how it relates to process improvement
Pre-Control Charts - Describe the fundamental rules that guide the operation of a standard pre-control plan
Control Charts - Explain the purpose of statistical process control charts and the logic of their operation
Score Cards - Understand the purpose of Six Sigma score cards and how they are deployed
Search Patterns - Explain how the use of designed experiments can facilitate problem solving
Concept Integration - Understand how to sequence a given selection of quality tools to better solve problems
Quality Simulation - Employ the related quality tools to analyze data generated by the process simulator
Basic Statistics
Topic Description
Performance Variables - Identify and describe the types of variables typically encountered in field work
Statistical Notation - Recognize and interpret the conventional forms of statistical notation
Performance Variation - Explain the basic nature of variation and how it can adversely impact quality
Normal Distribution - Describe the features and properties that are characteristic of a normal distribution
Distribution Analysis - Explain how to test the assumption that a set of data is normally distributed
Location Indices - Identify, compute, and interpret the mean, median, and mode
Dispersion Indices - Identify, compute, and interpret the range, variance, and standard deviation
Quadratic Deviations - Understand the nature of a quadratic deviation and its basic purpose
Variation Coefficient - Compute and interpret the coefficient of variation
Deviation Freedom - Explain the concept of degrees-of-freedom and how it is used in statistical work
Standard Transform - Describe how to transform a set of raw data into standard normal deviates
Standard Z-Probability - Describe how to convert a standard normal deviate into its corresponding probability
Central Limit - Understand that the distribution of sampling averages follows a normal distribution
Standard Error - Recognize that the dispersion of sampling averages is described by the standard error
Student's Distribution - Understand that the T distribution applies when sampling is less than infinite
Standard T-Probability - Describe how to convert a T value into its corresponding probability
Statistics Simulation - Employ basic statistics to analyze data generated by the process simulator
Continuous Capability
Topic Description
Performance Specifications - Explain the basic nature and purpose of performance specification limits
Rational Subgrouping - Explain how to form rational subgroups and describe their purpose in Six Sigma work
Capability Study - Understand the concept of process capability and how it applies to products and services
Instantaneous Capability - Understand the concept of instantaneous capability in relation to Six Sigma work
Longitudinal Capability - Understand the concept of longitudinal capability in relation to Six Sigma work
Cp Index - Compute and interpret Cp
Cpk Index - Compute and interpret Cpk
Pp Index - Compute and interpret Pp
Ppk Index - Compute and interpret Ppk
Process Shifting - Understand the impact of process centering error on short-term capability
Process Qualification - Determine the required level of short-term capability necessary to qualify a process
ConcaP Simulation - Apply continuous indices of capability to the process simulator
Discrete Capability
Topic Description
Defect Metrics - Identify and describe the defect metrics commonly used in Six Sigma work
Defect Opportunities - Understand the nature and purpose of defect opportunities in terms of quality reporting
Binomial Distribution - Describe the features and properties that are characteristic of a binomial distribution
Poisson Distribution - Describe the features and properties that are characteristic of the Poisson distribution
Throughput Yield - Compute and interpret throughput yield in the context of Six Sigma work
Rolled Yield - Compute and interpret rolled-throughput yield in the context of Six Sigma work
Metrics Conversion - Convert yield and defect metrics to the sigma scale of measure
DiscaP Simulation - Apply discrete indices of capability to the process simulator
Hypothesis Testing
Topic Description
Statistical Inferences - Explain the concept of a statistical inference and its primary benefits
Statistical Questions - Explain the nature and purpose of a statistical question
Statistical Problems - Understand why practical problems must be translated into statistical problems
Null Hypotheses - Define the nature and role of null hypotheses when making process improvements
Alternate Hypotheses - Define the nature and role of alternate hypotheses when making process improvements
Statistical Significance - Explain the concept of statistical significance versus practical significance
Alpha Risk - Explain the concept of alpha risk in terms of the alternate hypothesis
Beta Risk - Define the meaning of beta risk and how it relates to test sensitivity
Criterion Differences - Explain the role of a criterion difference when testing hypotheses
Decision Scenarios - Develop a scenario that exemplifies the use of hypothesis testing
Sample Size - Define the statistical elements that must be considered when computing sample size
Confidence Intervals
Topic Description
Mean Distribution - Comprehend and characterize the distribution of sampling averages
Mean Interval - Compute and interpret the confidence interval of a mean
Variance Distribution - Comprehend and characterize the distribution of sampling variances
Variance Interval - Compute and interpret the confidence interval of a variance
Proportion Distribution - Comprehend and characterize the distribution of sampling proportions
Proportion Interval - Compute and interpret the confidence interval of a proportion
Frequency Interval - Describe how frequency of defects is related to confidence intervals
Control Methods
Topic Description
Statistical Control - Explain the meaning of statistical control in terms of random variation
Control Logic - Explain the logic that underpins the application of a control chart
Control Limits - Reconcile the difference between specification limits and control limits
Chart Selection - Explain how to rationally select a control chart
Chart Interpretation - Interpret an SPC chart in terms of its control limits
Zone Testing - Explain the concept of zone tests and their application to SPC charts
Variables Chart - Characterize the role and purpose of a variables chart
Attribute Chart - Characterize the role and purpose of an attribute chart
Individuals Chart - Construct and interpret an individuals control chart
IMR Chart - Construct and interpret an individual moving range control chart
Xbar Chart - Construct and interpret a control chart for subgroup averages
Range Chart - Construct and interpret a control chart for subgroup ranges
Proportion Chart - Construct and interpret a control chart for sampling proportions
Defect Chart - Construct and interpret a control chart for defect occurrences
Other Charts - Describe several other types of control charts used in Six Sigma work
Capability Studies - Explain the role of capability studies when making process improvements
Control Simulation - Apply common SPC methods to the process simulator
Parametric Methods
Topic Description
Mean Differences - Determine if two means are statistically different from each other
Variance Differences - Determine if two variances are statistically different from each other
Variation Total - Compute and interpret the total sums-of-squares
Variation Within - Compute and interpret the within-group sums-of-squares
Variation Between - Compute and interpret the between-group sums-of-squares
Variation Analysis - Explain how the analysis of variances can reveal mean differences
One-Way ANOVA - Construct and interpret a one-way analysis-of-variance table
Two-Way ANOVA - Construct and interpret a two-way analysis-of-variance table
N-Way ANOVA - Construct and interpret an N-way analysis-of-variance table
ANOVA Graphs - Construct and interpret a main effects plot as well as an interaction plot
Linear Regression - Conduct a linear regression and construct an appropriate model
Multiple Regression - Conduct a multiple regression and construct an appropriate model
Residual Analysis - Compute and analyze the residuals resulting from a simple regression
Parametric Simulation - Apply general regression methods to the process simulator
Chi-Square Methods
Topic Description
Statistical Definition - Describe how to translate a practical problem into a statistical problem
Model Fitting - Explain what is meant by the term "Model Fitting" and discuss its practical role in Six Sigma work
Testing Independence - Explain how a test of independence can be related to the idea of correlation
Contingency Coefficients - Understand how a contingency coefficient relates to a cross-tabulation table
Yates Correction - Describe the role of Yates correction in terms of the chi-square statistic
Testing Proportions - Test the significance of two proportions using the Chi-square statistic
Survey Methods
Topic Description
Research Design - Explain how the idea of research design fit with the idea of problem Solving
Information Sources - Explain how the idea of research design fit with the idea of problem Solving
Questionnaire Construction - Describe the role of survey demographics when analyzing closed-form survey data
Formulating Questions - Identify several things that should be avoided when developing survey questions
Question Quality - Explain what is meant by the term "question quality" and how this idea relates to data analysis
Sampling Plans - Describe several different types of sampling plans commonly used in survey research
Data Analysis - Explain how categorical survey data can be analyzed to establish strength of association
Nonparametric Methods
Topic Description
Nonparametric Concepts - Explain the difference between parametric and nonparametric methods
Median Test - Execute a median test on two groups and then determine if the difference is statistically significant
Runs Test - Conduct a runs test to determine if a time series pattern is random
Other Tests - Identify two nonparametric methods other than a median or runs test
Experimental Methods
Topic Description
Design Principles - Understand the principles of experiment design and analysis
Design Models - Describe the various types of designed experiments and their applications
Experimental Strategies - Outline a strategy for designing and analyzing a statistical experiment
Experimental Effects - Define the various types of experimental effects and how they impact decisions
One-Factor Two Level - Configure and analyze a one-factor two-level statistically based experiment
One-Factor Multi Level - Configure and analyze a one-factor multi-level statistically based experiment
Full Factorials - Understand the nature and underlying logic of full factorial experiments
Two-Factor Two Levels - Configure and analyze a two-factor two-level statistically based experiment
Two-Factor Multi Level - Configure and analyze a two-factor multi-level statistically based experiment
Three-Factor Two Level - Configure and analyze a three-factor two-level statistically based experiment
Planning Experiments - Understand the planning and implementation considerations related to statistical experiments
Fractional Factorials - Understand the nature and underlying logic of fractional factorial experiments
Four-Factor Half-Fraction - Configure and analyze a four-factor half-fraction statistically based experiment
Five-Factor Half-Fraction - Configure and analyze a five-factor half-fraction statistically based experiment
Screening Designs - Understand how to select, implement, and analyze a screening experiment
Robust Designs - Explain the purpose of robust design and define several practical usages
Experiment Simulation - Describe how a DOE can be employed when measurement data is not available
DFSS Methods
Topic Description
QFD Method - Explain how quality function deployment can be used to help identify design specifications
Capability Flow-Down - Describe how a capability flow-down can be used as a risk allocation and abatement tool
Capability Flow-Up - Describe how a capability flow-up can be used to analyze the reproducibility of a design
Tolerance Analysis - Demonstrate how the RSS method can be used to analyze assembly tolerances
Monte-Carlo Simulation - Explain how Monte-Carlo simulation can be used during the process of design
Measurement Analysis
Topic Description
Measurement Uncertainty - Understand the concept of measurement uncertainty
Measurement Components - Describe the components of measurement error and their consequential impact
Measurement Studies - Explain how a measurement systems analysis is designed and conducted
Training Project
Topic Description
Project Introduction - Understand the steps to deploy a Training Project
Recognize Phase - Understand the tools used during the Recognize Phase
Define Phase - Execute the steps needed during the Define Phase
Measure Phase - Understand the tools needed during the Measure Phase
Analyze Phase - Become familiar with the tools used during the Analyze Phase
Improve Phase - Become familiar with the tools needed for improvement
Control Phase - Recognize the usage of tools needed for Process Control
Survey Analysis - Execute the techniques to analyze Survey data
Risk Analysis - Understand the tools needed for a Risk Analysis
The SSA Difference
Our two-week Design For Six Sigma Certification curriculum teaches participants how to learn and apply techniques related to capturing the Voice of the Customer (VOC), requirements flow-down, process capability rollup, balanced scorecards, continuous and discrete simulation, experimental design, and invention technologies. In addition, the Design for Six Sigma Certification offering includes 20 hours of project execution support. The two weeks of training are separated by a five- to ten-week application of Breakthrough Design for the participants’ individual projects. During the application weeks, DFSS Black Belts are supported and mentored by an assigned Project Champion, who also reviews and critiques the DFSS Black Belts results along with the instructor and classmates.
Who Should Take This Course?
DFSS Certification course participants must be certified Black Belts and are required to come to class with at least one project that will be completed over a 12- to 18-month period.
Benefits/Outcomes:
-Ability to lead teams in creating new products, processes, or services to achieve high levels of performance
-Ability to lead teams in overhauling existing products, processes, or services to achieve high levels of performance
-Ability to collect precise and detailed customer requirements, translate those requirements into design parameters, then optimize settings for those design parameters through experimentation and simulation
-Ability to lead and/or facilitate innovative projects while developing robust breakthrough designs for products, services, and processes that perform flawlessly on launch
Course Requirements:
Attendance at all 10 days of classroom training
One or more projects that can be completed within 12 to 18 months from the start of training
Black Belt Certification (attended training and completed at least two projects); proficiency in the core Lean Six Sigma tools
Windows-based laptop computer with a CD-ROM (participant must have access to the laptop throughout the training)
Minitab v.16 (loaded on laptop prior to attending training)
Design for Six Sigma Certification Price (Euro): €6,250
Registration Fee Includes:
Ten days of classroom training (two five-day sessions separated by five to ten weeks)
24 hours of project execution support, to be delivered remotely unless otherwise agreed upon; must be used within 18 months from the start of training
A set of electronic documentation covered during the training
The Design For Six Sigma Memory Jogger
Certificate of Participation for individuals who complete training
Certification for participants who meet DFSS certification requirements
Daily continental breakfast, lunch, refreshments, and snacks
DFSS Certification Requirements:
-Ten days of classroom training
-Completion of two projects
-Complete DFSS BB Test with a Score ≥ 85%
Design for Six Sigma
Program Description
Training Orientation
Topic Description
Excel Orientation - Explore the Excel software package
Statistical Software Orientation - Explore Minitab/JMP software packages
Simulator Orientation - Explore the Process Simulator
Breakthrough Vision
Topic Description
Content Overview - Understand the nature, purpose, and drivers of Six Sigma
Driving Need - Identify the needs that underlie a Six Sigma initiative
Customer Focus - Explain why focusing on the customer is essential to business success
Core Beliefs - Contrast the core beliefs of Six Sigma to conventional practices
Deterministic Reasoning - Describe a basic cause-and-effect relationship in terms of Y=f(X)
Leverage Principle - Relate the principle of leverage to an improvement project
Tool Selection - Identify the primary family of analytical tools used in Six Sigma work
Performance Breakthrough - Describe the underlying logic of the DMAIC improvement process
Business Principles
Topic Description
Quality Definition - Articulate the idea of quality in terms of value entitlement
Value Proposition - Define the primary components of value and their key elements
Metrics Reporting - Recognize the need for installing and reporting performance metrics
BOPI Goals - Recognize the need for cascading performance metrics
Underpinning Economics - Describe the relationship between quality and cost
Third Generation - Differentiate between the first, second and third generations of Six Sigma
Success Factors - Identify the primary success factors related to a Six Sigma deployment
Process Management
Topic Description
Performance Yield - Explain why final yield is often higher than first-time yield
Hidden Processes - Describe the non-value added component of a process
Measurement Power - Describe the role of measurement in an improvement initiative
Establishing Baselines - Explain why performance baselines are essential to realizing improvement
Performance Benchmarks - Explain how a benchmarking chart can be used to assess quality performance
Defect Opportunity - Understand the nature of a defect opportunity and its role in metrics reporting
Process Models - Define the key features of a Six Sigma performance model
Process Capability - Identify the primary indices of process capability
Design Complexity - Describe the impact of complexity on product and service quality
Product Reliability - Explain how process capability can impact product reliability
Installation Guidelines
Topic Description
Deployment Planning - Understand the elements of Deployment Planning
Deployment Timeline - Understand the elements of a Deployment Timeline
CXO Role - Receive insight on how key decisions are addressed
Champion Role - Define the operational role of a Six Sigma Champion and highlight key attributes
Black Belt Role - Define the operational role of a Six Sigma Black Belt and highlight key attributes
Green Belt Role - Define the operational role of a Six Sigma Green Belt and highlight key attributes
White Belt Role - Define the operational role of a Six Sigma White Belt and highlight key attributes
Application Projects - Describe the purpose of Six Sigma Application Projects and how such projects are executed
DFSS Principles - See how product design can affect yield and performance
PFSS Principles - Have an understanding of the Process For Six Sigma Criteria
MFSS Principles - Understand how Managing For Six Sigma works
Application Projects
Topic Description
Project Description - Understand how to fully define a Six Sigma application project
Project Overview - Provide an overview of the key elements that characterizes an application project
Project Guidelines - Explain how to establish project selection guidelines
Project Scope - Explain how to properly scope an application project
Project Leadership - Recognize the actions that must occur to ensure successful project leadership
Project Teams - Form a project team that is capable of supporting Six Sigma applications
Project Financials - Understand the role of project financials in supporting deployment success
Project Management - Explain how application projects are best managed to achieve maximum results
Project Payback - Understand the driving need for establishing project paybacks
Project Milestones - Identify the primary milestones associated with a successful Six Sigma deployment
Project Charters - Understand the role of project charters and how they are used to guide implementation
Value Focus
Topic Description
Value Creation - Define the idea of value and explain how it can be created
Recognize Needs - Recognize the power of need fulfillment and how it links to value creation
Define Opportunities - Understand how to define opportunities that lead to the creation of value
Measure Conditions - Identify and evaluate the conditions that underlies improvement opportunity
Analyze Forces - Explain how the underlying forces are identified and leveraged to create beneficial change
Improve Settings - Establish optimal settings for each of the key forces that underpins beneficial change
Control Variations - Discuss how unwanted variations can mask the pathway to breakthrough
Standardize Factors - Understand the role and importance of standardized success factors
Integrate Lessons - Explain how key lessons learned can be merged into a set of best practices
Application Example - Understand how the breakthrough process can be applied to everyday life
Lean Practices
Topic Description
Lean Thinking - Comprehend the underlying logic of lean thinking
Constraint Theory - Explain how constraint theory is related to value creation
Continuous Flow - Describe the operational ideas that underpins continuous flow
Pull Systems - Contrast the operation of a push system to that of a pull system
Visual Factory - Explain the role of a visual factory during improvement efforts
Kanban System - Describe how a Kanban system can improve process cycle-time
PokaYoke System - Understand how PokaYoke systems can lead to quality improvement
6S System - Explain how the 6S system can contribute to process efficiency
SMED System - Define the basic elements of an SMED system
7W Approach - Describe how the 7W approach can be used to solve problems
6M Approach - Explain how the 6M approach is used to identify sources of causation
Quality Tools
Topic Description
Variable Classifications - Define the various types of variables commonly encountered during quality improvement
Measurement Scales - Describe each of the four primary scales of measure and their relative power
Problem Definition - Characterize the nature of a sound problem statement
Focused Brainstorming - Explain how focused brainstorming is used to facilitate improvement efforts
Process Mapping - Understand how to define the flow of a process and map its operations
SIPOC Diagram - Describe the nature and purpose of an SIPOC diagram
Force-Field Analysis - Utilize force field analysis to solve problems
Matrix Analysis - Understand how matrices are created and used to facilitate problem solving
C&E Analysis - Explain how C&E matrices can be used to solve quality problems
Failure Mode Analysis - Understand how FMEA is used to realize process and design improvements
Performance Sampling - Explain how to design and implement a sampling plan
Check Sheets - Understand how check sheets can be used for purposes of data collection
Analytical Charts - Identify the general range of analytical charts that can be used to assess performance
Pareto Charts - Explain how Pareto charts can be used to isolate improvement leverage
Run Charts - Utilize run charts to assess and characterize time-based process data
Multi-Vari Charts - Define the major families of variation and how they can be graphed
Correlation Charts - Utilize a correlation chart to illustrate the association between two variables
Frequency Tables - Explain how to construct and interpret a frequency table
Performance Histograms - Construct and interpret a histogram and describe several purposes
Basic Probability - Understand basic probability theory and how it relates to process improvement
Pre-Control Charts - Describe the fundamental rules that guide the operation of a standard pre-control plan
Control Charts - Explain the purpose of statistical process control charts and the logic of their operation
Score Cards - Understand the purpose of Six Sigma score cards and how they are deployed
Search Patterns - Explain how the use of designed experiments can facilitate problem solving
Concept Integration - Understand how to sequence a given selection of quality tools to better solve problems
Quality Simulation - Employ the related quality tools to analyze data generated by the process simulator
Basic Statistics
Topic Description
Performance Variables - Identify and describe the types of variables typically encountered in field work
Statistical Notation - Recognize and interpret the conventional forms of statistical notation
Performance Variation - Explain the basic nature of variation and how it can adversely impact quality
Normal Distribution - Describe the features and properties that are characteristic of a normal distribution
Distribution Analysis - Explain how to test the assumption that a set of data is normally distributed
Location Indices - Identify, compute, and interpret the mean, median, and mode
Dispersion Indices - Identify, compute, and interpret the range, variance, and standard deviation
Quadratic Deviations - Understand the nature of a quadratic deviation and its basic purpose
Variation Coefficient - Compute and interpret the coefficient of variation
Deviation Freedom - Explain the concept of degrees-of-freedom and how it is used in statistical work
Standard Transform - Describe how to transform a set of raw data into standard normal deviates
Standard Z-Probability - Describe how to convert a standard normal deviate into its corresponding probability
Central Limit - Understand that the distribution of sampling averages follows a normal distribution
Standard Error - Recognize that the dispersion of sampling averages is described by the standard error
Student's Distribution - Understand that the T distribution applies when sampling is less than infinite
Standard T-Probability - Describe how to convert a T value into its corresponding probability
Statistics Simulation - Employ basic statistics to analyze data generated by the process simulator
Continuous Capability
Topic Description
Performance Specifications - Explain the basic nature and purpose of performance specification limits
Rational Subgrouping - Explain how to form rational subgroups and describe their purpose in Six Sigma work
Capability Study - Understand the concept of process capability and how it applies to products and services
Instantaneous Capability - Understand the concept of instantaneous capability in relation to Six Sigma work
Longitudinal Capability - Understand the concept of longitudinal capability in relation to Six Sigma work
Cp Index - Compute and interpret Cp
Cpk Index - Compute and interpret Cpk
Pp Index - Compute and interpret Pp
Ppk Index - Compute and interpret Ppk
Process Shifting - Understand the impact of process centering error on short-term capability
Process Qualification - Determine the required level of short-term capability necessary to qualify a process
ConcaP Simulation - Apply continuous indices of capability to the process simulator
Discrete Capability
Topic Description
Defect Metrics - Identify and describe the defect metrics commonly used in Six Sigma work
Defect Opportunities - Understand the nature and purpose of defect opportunities in terms of quality reporting
Binomial Distribution - Describe the features and properties that are characteristic of a binomial distribution
Poisson Distribution - Describe the features and properties that are characteristic of the Poisson distribution
Throughput Yield - Compute and interpret throughput yield in the context of Six Sigma work
Rolled Yield - Compute and interpret rolled-throughput yield in the context of Six Sigma work
Metrics Conversion - Convert yield and defect metrics to the sigma scale of measure
DiscaP Simulation - Apply discrete indices of capability to the process simulator
Hypothesis Testing
Topic Description
Statistical Inferences - Explain the concept of a statistical inference and its primary benefits
Statistical Questions - Explain the nature and purpose of a statistical question
Statistical Problems - Understand why practical problems must be translated into statistical problems
Null Hypotheses - Define the nature and role of null hypotheses when making process improvements
Alternate Hypotheses - Define the nature and role of alternate hypotheses when making process improvements
Statistical Significance - Explain the concept of statistical significance versus practical significance
Alpha Risk - Explain the concept of alpha risk in terms of the alternate hypothesis
Beta Risk - Define the meaning of beta risk and how it relates to test sensitivity
Criterion Differences - Explain the role of a criterion difference when testing hypotheses
Decision Scenarios - Develop a scenario that exemplifies the use of hypothesis testing
Sample Size - Define the statistical elements that must be considered when computing sample size
Confidence Intervals
Topic Description
Mean Distribution - Comprehend and characterize the distribution of sampling averages
Mean Interval - Compute and interpret the confidence interval of a mean
Variance Distribution - Comprehend and characterize the distribution of sampling variances
Variance Interval - Compute and interpret the confidence interval of a variance
Proportion Distribution - Comprehend and characterize the distribution of sampling proportions
Proportion Interval - Compute and interpret the confidence interval of a proportion
Frequency Interval - Describe how frequency of defects is related to confidence intervals
Control Methods
Topic Description
Statistical Control - Explain the meaning of statistical control in terms of random variation
Control Logic - Explain the logic that underpins the application of a control chart
Control Limits - Reconcile the difference between specification limits and control limits
Chart Selection - Explain how to rationally select a control chart
Chart Interpretation - Interpret an SPC chart in terms of its control limits
Zone Testing - Explain the concept of zone tests and their application to SPC charts
Variables Chart - Characterize the role and purpose of a variables chart
Attribute Chart - Characterize the role and purpose of an attribute chart
Individuals Chart - Construct and interpret an individuals control chart
IMR Chart - Construct and interpret an individual moving range control chart
Xbar Chart - Construct and interpret a control chart for subgroup averages
Range Chart - Construct and interpret a control chart for subgroup ranges
Proportion Chart - Construct and interpret a control chart for sampling proportions
Defect Chart - Construct and interpret a control chart for defect occurrences
Other Charts - Describe several other types of control charts used in Six Sigma work
Capability Studies - Explain the role of capability studies when making process improvements
Control Simulation - Apply common SPC methods to the process simulator
Parametric Methods
Topic Description
Mean Differences - Determine if two means are statistically different from each other
Variance Differences - Determine if two variances are statistically different from each other
Variation Total - Compute and interpret the total sums-of-squares
Variation Within - Compute and interpret the within-group sums-of-squares
Variation Between - Compute and interpret the between-group sums-of-squares
Variation Analysis - Explain how the analysis of variances can reveal mean differences
One-Way ANOVA - Construct and interpret a one-way analysis-of-variance table
Two-Way ANOVA - Construct and interpret a two-way analysis-of-variance table
N-Way ANOVA - Construct and interpret an N-way analysis-of-variance table
ANOVA Graphs - Construct and interpret a main effects plot as well as an interaction plot
Linear Regression - Conduct a linear regression and construct an appropriate model
Multiple Regression - Conduct a multiple regression and construct an appropriate model
Residual Analysis - Compute and analyze the residuals resulting from a simple regression
Parametric Simulation - Apply general regression methods to the process simulator
Chi-Square Methods
Topic Description
Statistical Definition - Describe how to translate a practical problem into a statistical problem
Model Fitting - Explain what is meant by the term "Model Fitting" and discuss its practical role in Six Sigma work
Testing Independence - Explain how a test of independence can be related to the idea of correlation
Contingency Coefficients - Understand how a contingency coefficient relates to a cross-tabulation table
Yates Correction - Describe the role of Yates correction in terms of the chi-square statistic
Testing Proportions - Test the significance of two proportions using the Chi-square statistic
Survey Methods
Topic Description
Research Design - Explain how the idea of research design fit with the idea of problem Solving
Information Sources - Explain how the idea of research design fit with the idea of problem Solving
Questionnaire Construction - Describe the role of survey demographics when analyzing closed-form survey data
Formulating Questions - Identify several things that should be avoided when developing survey questions
Question Quality - Explain what is meant by the term "question quality" and how this idea relates to data analysis
Sampling Plans - Describe several different types of sampling plans commonly used in survey research
Data Analysis - Explain how categorical survey data can be analyzed to establish strength of association
Nonparametric Methods
Topic Description
Nonparametric Concepts - Explain the difference between parametric and nonparametric methods
Median Test - Execute a median test on two groups and then determine if the difference is statistically significant
Runs Test - Conduct a runs test to determine if a time series pattern is random
Other Tests - Identify two nonparametric methods other than a median or runs test
Experimental Methods
Topic Description
Design Principles - Understand the principles of experiment design and analysis
Design Models - Describe the various types of designed experiments and their applications
Experimental Strategies - Outline a strategy for designing and analyzing a statistical experiment
Experimental Effects - Define the various types of experimental effects and how they impact decisions
One-Factor Two Level - Configure and analyze a one-factor two-level statistically based experiment
One-Factor Multi Level - Configure and analyze a one-factor multi-level statistically based experiment
Full Factorials - Understand the nature and underlying logic of full factorial experiments
Two-Factor Two Levels - Configure and analyze a two-factor two-level statistically based experiment
Two-Factor Multi Level - Configure and analyze a two-factor multi-level statistically based experiment
Three-Factor Two Level - Configure and analyze a three-factor two-level statistically based experiment
Planning Experiments - Understand the planning and implementation considerations related to statistical experiments
Fractional Factorials - Understand the nature and underlying logic of fractional factorial experiments
Four-Factor Half-Fraction - Configure and analyze a four-factor half-fraction statistically based experiment
Five-Factor Half-Fraction - Configure and analyze a five-factor half-fraction statistically based experiment
Screening Designs - Understand how to select, implement, and analyze a screening experiment
Robust Designs - Explain the purpose of robust design and define several practical usages
Experiment Simulation - Describe how a DOE can be employed when measurement data is not available
DFSS Methods
Topic Description
QFD Method - Explain how quality function deployment can be used to help identify design specifications
Capability Flow-Down - Describe how a capability flow-down can be used as a risk allocation and abatement tool
Capability Flow-Up - Describe how a capability flow-up can be used to analyze the reproducibility of a design
Tolerance Analysis - Demonstrate how the RSS method can be used to analyze assembly tolerances
Monte-Carlo Simulation - Explain how Monte-Carlo simulation can be used during the process of design
Measurement Analysis
Topic Description
Measurement Uncertainty - Understand the concept of measurement uncertainty
Measurement Components - Describe the components of measurement error and their consequential impact
Measurement Studies - Explain how a measurement systems analysis is designed and conducted
Training Project
Topic Description
Project Introduction - Understand the steps to deploy a Training Project
Recognize Phase - Understand the tools used during the Recognize Phase
Define Phase - Execute the steps needed during the Define Phase
Measure Phase - Understand the tools needed during the Measure Phase
Analyze Phase - Become familiar with the tools used during the Analyze Phase
Improve Phase - Become familiar with the tools needed for improvement
Control Phase - Recognize the usage of tools needed for Process Control
Survey Analysis - Execute the techniques to analyze Survey data
Risk Analysis - Understand the tools needed for a Risk Analysis