ON-CAMPUS CERTIFICATION PROGRAMS

The University of Miami’s Executive Education Center offers all levels of Six Sigma training and certification. A list of the seminars with their length and cost are shown below.

(Location: University of Miami Executive Education Center)

Seminar

Requirements & Duration

Incremental Cost
per Certification Level

Total Cost
per Certification Level

Dates Register

Champion

2 days + Exam

$3,000

$3,000

7/13 & 14

 

Green Belt (DMAIC)

Champion + 2 days + Exam + 1 project

Champion + $1,500

$4,500

7/13 & 14
7/20 & 21

 

Green Belt (DMADV)

Champion + 2 days + Exam + 1 project

Champion + $1,500

$4,500

9/7 & 8
9/14 & 15
Back Up Dates
9/28 & 29

 

Black Belt (DMAIC)

Green Belt + self study for Exam + 1 additional  project

Green Belt + $7,500

$12,000

9/13 & 14
7/20 & 21
+ self study

 

Master Black Belt

Black Belt + self study + Work directly with top management + 8 additional projects + Develop courseware + Teach seminars

 

 

Contact 
Dr. Gitlow

 

 

Lean Thinking

Champion + 2 days + Exam + 1 project

Champion + $1,500

$4,500

Coming in 2008

 

Note: Above on-campus seminars include textbooks, Power Point slides, and DVDs. However, the above rates do NOT include project mentoring. Project mentoring fees are: Dr. Gitlow at $600/hour or an Associate at $250/hour. If you wish, we will assist you in selecting the most appropriate and least expensive option for your particular circumstance.

 

CHAMPION

Champion. A Six Sigma Champion is the most basic form of Six Sigma certification. A Champion understands the theory of Six Sigma management, but does not yet have the quantitative skills to function as an active Six Sigma project team member. 
You must successful pass a certification examination to be awarded the Six Sigma Champion certification.  

INTRODUCTION TO QUALITY MANAGEMENT

Seminar Description:  Participants in this seminar will be introduced to the major elements of Dr. Deming's theory of management, as well as “Six Sigma” theory, tools and methods.  These tools and methods have been adopted with great success by many of the largest organizations in the world, for example, Motorola, General Electric, Johnson & Johnson, Allied Signal, Dupont, American Express, J.P. Morgan, HSBC Bank, University of Miami, to name a few. 

Textbook: Gitlow, H. and Levine, D., Six Sigma for Green Belts and Champions: Foundations,
DMAIC, Tools and Methods, Cases and Certification, Prentice-Hall Publishers (Saddle River,
NJ), 2004.

Champion Certification: “Introduction to Quality Management” is required to sit for the
“Six Sigma” Champion certification exam.

Seminar Outline:

Introduction

Macro Model (Dashboards)

Micro Model (Projects)

Management Model (System of Profound Knowledge)

Chapter 1: Overview of Six Sigma Management

Successful Applications of “Six Sigma” Management

Timeline of Six Sigma Management

Key Ingredients for Success with “Six Sigma” Management

Benefits “Six Sigma” Management

Process Basics

Definitions of Quality

Definitions of “Six Sigma” Management

What Is New About “Six Sigma” Management?

Chapter 2: Six Sigma Roles, Responsibilities and Terminology

Roles and Responsibilities in Six Sigma Management

Technical Terminology of Six Sigma Management

Beginning Six Sigma Management

Non-Manufacturing Industries

Chapter 3 Macro Model (Dashboards)

Structure of a dashboard

Components of a dashboard

Example of a dashboard

Managing with a dashboard

Prioritization of Six Sigma projects

Management decides if a project team is necessary

Chapter 4: Define Phase

Activate the Six Sigma project team

Structure of the define phase

Prepare the project charter

Conduct a SIPOC analysis

Perform a “Voice of the Customer” analysis

Revise the project objective

Project approval process (tollgates)

Chapter 5: Measure Phase

Constructing Operational Definitions For CTQs

Establishing The Validity Of The Measurement System For Each CTQ

Establishing the Baseline Capabilities for CTQs

Chapter 6: Analyze Phase

Identify the Xs for the Process Under Study

Identify the Xs Related to Each CTQ

Identify the High Risk Xs for Each CTQ

Develop Operational Definitions for High Risk Xs

Establish Measurement System for High Risk Xs

Establish Baseline Process Capabilities for Xs

Stabilize High Risk Xs

Consider Major Nuisance Variables

Use Screening Designs to Reduce the Number of High Risk Xs

Develop Hypotheses about the Relationships between the High Risk Xs and the CTQs

The Analyze Phase for Processes with a Well Established Dashboard

Chapter 7: Improve Phase

Purpose of Designed Experiments

Level of Process Knowledge

Some Flawed Experimental Designs

Two Factor Factorial Designs

Example of a Designed Experiment

Avoid Potential problems in the X’s

Conduct a Pilot Test

Example of a Pilot Study

Identify Actions Needed To Implement Optimized Process

Champion and Process Owner Review the Project

Chapter 8: Control Phase

Reduce the Effects of Collateral Damage to Related Processes

Standardize Improvements (International Standards Organization [ISO])

Maintain Control of the Xs

Develop a Control Plan for the Process Owner

Identify and Document Benefits and Costs of Project

Input Project into Six Sigma Database

Diffuse the Improvements throughout the Organization

Champion and Process Owner Review Project

Chapter 16: Paper Organizers International Case Study

Chapter 17: A Paper Helicopter Case Study

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Green Belt (DMAIC)

   

Green Belt. A Six Sigma Green Belt is an individual who works on projects part-time (25%), either as a team member for complex projects, or as a project leader for simpler projects. Green belts are the “work horses” of Six Sigma projects.

You must successful pass a certification examination and complete a successful Six Sigma project to be awarded the Six Sigma Green Belt certification.  

 

Introduction to Statistics for Decision Making

Course Description: Participants in this seminar will be introduced to the methods, tools and techniques of basic statistical analysis.

Prerequisite: Participants in this seminar must have achieved Six Sigma Champion certification.  

Textbook: Gitlow, H. and Levine, D., Six Sigma for Green Belts and Champions: Foundations, DMAIC, Tools and Methods, Cases and Certification, Prentice-Hall Publishers (Saddle River, NJ), 2004.

Champion Certification: “Introduction to Statistics for Decision Making” is required to sit for the “Six Sigma” Green Belt certification exam.

Seminar Outline:

Chapter 9: Basics of Statistical Studies

Introduction to Statistics

Enumerative and Analytic Studies

Types of Sampling

Types of Variables

Operational Definitions

Introduction to Graphics

Graphing Attribute Data

Graphing Measurement Data

Measures of Central Tendency

Measures of Variation

The Shape of Distributions

Chapter 10: Probability and Probability Distributions

Introduction to Probability

Some Rules of Probability

Probability Distribution

Binomial Distribution

Poisson Distribution

Normal Distribution

Normal Probability Plot

Chapter 11: Sampling Distributions and Interval Estimation

Sampling Distributions

Basic Concepts of Confidence Intervals

Confidence Interval Estimate for the Mean (s unknown)

Prediction Interval Estimate for a Future Individual Value

Confidence Interval Estimation for the Proportion

Chapter 12: Hypothesis Testing

Fundamental Concepts of Hypothesis Testing

Testing for the Difference Between Two Proportions

Testing for the Difference Between the Means of Two Independent Groups

Testing for the Differences Between Two Variances

One-Way ANOVA

Chapter 13: Design of Experiments

Design of Experiments: Background and Rationale

Two-Factor Factorial Designs

2k Factorial Designs

Fractional Factorial Designs

Chapter 14: Control Charts for Six Sigma Management

Basic Concepts of Control Charts

Funnel Experiment

Control Limits and Patterns

Rules for Determining Out-Of-Control Points

p-Chart

c-Chart

u-Chart

Control Charts for the Mean and Range

Control Charts for the Mean and the Standard Deviation

Individual Value and Moving Range Charts

 

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Green Belt (DMADV)

Design for Six Sigma Management

Course Description: Participants in this seminar will be introduced to the major elements of Design for Six Sigma management (DFSS). DFSS is the Six Sigma model for creating major new features of existing products, services or process, or creating entirely new products, services or processes.

Prerequisites: Participants in this seminar must have achieved Six Sigma Champion certification.

Textbook: Gitlow, H., Levine, D., and Popovich, E. (2006), Design for Six Sigma for Green Belts and Champions: Foundations, DMADV, Tools and Methods, Cases and Certification, Prentice-Hall Publishers (Saddle River, NJ).

Champion Certification: “Design for Six Sigma Management” is required to sit for the Design for Six Sigma Green Belt certification examination.

Seminar Outline:

Chapter 4: Define Phase

Steps of the Define Phase

Inputs to the Define Phase

Develop the Business Case

Prepare the Opportunity Statement

Develop the Initial Project Objective

Develop the Project Scope (including a Multi Generational Product Plan [MGPP])

Develop the Project Plan

Develop the Document Control System

Assess the Benefits of the Six Sigma Project

Assess the Risks to the Project’s Success

Activate the DFSS Development Team (DT)

Finalize the Project Objective

Conduct Tollgate Review

Define Phase Tollgate Review Check Sheet

Key Outputs of the Define Phase

 
Chapter 5: Measure Phase

Steps of the Measure Phase

Inputs to the Measure Phase

Market Segmentation

Finding Cognitive Images with Kano Surveys

Convert Cognitive Images into CTQs with Quality Function Deployment

Select Final Set of CTQs

Develop and Validate a Measurement System for the CTQs

Develop a Design Scorecard

Review Intellectual Property Issues

Plan to Manage the Risk

Revise the Project Objective If Necessary

Update the Multi-Generational Product Plan (MGPP)

Conduct Tollgate Review (Check Sheet)

Outputs of the Measure Phase

 
Chapter 6: Analyze Phase

Steps of the Analyze Phase

Inputs of the Analyze Phase

Generate High Level Design Concepts for Critical Parameters

Investigate Alternative Design Concepts for Each Critical Parameter

Create a Limited Set of Potential Design Concepts

Assessing the Risks of the “Best” Design Concept

Optimize the Total Life Cycle Cost of the Design

Develop a Process Model for the Best Design

Transfer High Level Design to Process Owner with Design Scorecards

Outputs from the Analyze Phase

Summary


Chapter 7: Design Phase

Steps of the Design Phase

Inputs of the Design Phase

Constructing a Detailed Design

Developing Detailed CTPs for Each of the CTQs and High Level CTPs

Creating a Comprehensive Set of Detailed CTPs

Operationally Defining Each Detailed CTP

Validating the Measurement System for Each Detailed CTP

Establishing Baseline Capabilities for Each CTQ and CTP

Conducting a Capacity Analysis

Performing a FMEA of the Detailed CTPs

Constructing Detailed Design Scorecards

Performing Accounting Analysis

Preparing a Control and Verification Plan

Conducting Tollgate Design Phase Review (Checklist)

Outputs of the Design Phase

Chapter 8 Verify/Validate Phase

Steps of the Verify Phase

Inputs to the Verify / Validate Phase

Build a Prototype of the Detailed Design

Pilot Test the Prototype of the Detailed Design

Conduct Design Reviews Using Design Scorecards

Decide Whether or Not to Scale-Up the Design to the Full-Scale Process 

Build and Operate Full-Scale Process

Decide if the Full Scale Process Is Meeting Business Objectives

Build and Operate the Full-Scale Process

Decide if the Full Scale Process is Meeting Business Objectives

Conduct a Verify / Validate Tollgate Review (Check List)

Close the DMADV Project

Transfer the Lessons Learned from the Project

Outputs of the Verify Phase

Chapter 14: Articulating the Voice of the Stakeholder

Market Segmentation

Kano Surveys

Chapter 15: Enhancing Creativity to Develop Alternative Designs

Using de Bono’s Thinking Habits and Tools to Generate Alternative Design Concepts

Using TRIZ to Generate Alternative Design Concepts

Using Benchmarking to Generate Alternative Design Concepts

Chapter 17: Six Sigma DMADV Case Studies

Background

Define Phase

Measure Phase

Analyze Phase

Design Phase

Verify/Validate Phase  

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Black Belt (DMAIC)

Black Belt. A Six Sigma Black Belt is a full-time change agent and improvement leader who may not be an expert in the process under study.

You must successful pass a certification examination and complete a total of two successful Six Sigma project to be awarded the Six Sigma Black Belt certification.

Statistical Process Control for Business Decision Making

Seminar Description: This course introduces the fundamental concepts of statistical process control and reliability in the context of Quality Management. The course focuses on control charts and other process improvement tools, including several tools and techniques of reliability theory.  All the tools and techniques discussed are used by Quality Management systems such as Total Quality Management (TQM) and Six Sigma Management (6σ) to monitor and improve processes in service and manufacturing organizations, educational institutions, governments, and healthcare organizations. Many real life case studies will be examined to enhance the student’s learning experience.

Prerequisites: Participants in this seminar must have achieved Six Sigma Yellow Belt certification.

Six Sigma Certification: Statistical Process Control is required to sit for the Six Sigma Black Belt examination.

Textbook: Gitlow, H., Oppenheim, A., Oppenheim, R., and Levine, D., Quality Management: Tools and Methods for Improvement, 3nd edition, McGraw-Hill-Irwin, Publisher (Burr Hill, IL).  

Statistical Software: Minitab 14 (www.minitab.com)

Seminar Outline:

Chapter 20: Review of Six Sigma Management

Relationship Between the Voice of the Customer and the Voice of the Process

The DMAIC Model

Benefits and Costs of Six Sigma Management

Six Sigma Roles and Responsibilities

Six Sigma Terminology

A Six Sigma Case Study

Chapters 3: Fundamentals of Statistical Studies

Purpose and Definition of Statistics

Types of Statistical Studies

Enumerative Studies

Analytic Studies

Distinction Between Enumerative and Analytic Studies

Chapter 5: Review of Basic Probability and Statistics

Probability Defined

Types of Data

Characteristics of Data

Visually Describing Data

Numerically Describing Data

Chapter 6: Stabilizing and Improving a Process with Control Charts

Process Variation

The Structure of Control Charts

Stabilizing a Process with Control Charts

Advantages of a Stable Process

Improving a Process with Control Charts

Causes of Variation Out of the Control of the Process Owner

Two Possible Mistakes in Using Control Charts

Some Out-of-Control Evidence

Quality Consciousness and Types of Control Charts

Three Uses of Control Charts

Chapter 7: Attribute Control Charts

Types of Attribute Control Charts

Classification Charts

The p Chart for Constant Subgroup Sizes

The p Chart for Variable Subgroup Sizes

Count Charts

c Charts

u Charts  

Limitations of Attribute Control Charts

Chapter 8: Measurement (Variables) Control Charts

Variables Charts and the PDSA Cycle

Subgroup Size and Frequency

 and R Charts

and s Charts 

Individuals and Moving Range Charts

Revising Control Limits for Variables Control Charts  

Collecting Data: Rational Sub-grouping

Chapter 9: Out of Control Patterns

Between and Within Group Variation

Types of Control Chart Patterns

Out-of-Control Patterns and the Rules of Thumb

Chapter 10: Diagnosing a Process

Brainstorming

Affinity diagram

Cause and Effect Diagram

Interrelationship Diagraph

Check Sheet

Pareto Diagram

Stratification

Systematic diagram

Matrix diagram

Program Decision Process Charts (PDPC analyses)

70 Change Concepts

Chapter 11: Process Capability and Improvement Studies

Specifications (Voice of the Customer)

Process Capability Studies

Process Improvement Studies

Applied Regression Analysis for Business Decision Making

Seminar Description: This course aims to familiarize the student with statistical prediction. It covers simple and multiple regression methods as well as time series and forecasting models in business. Instead of theoretical development, the course emphasizes the application of these methods in business systems analysis and improvement.

Prerequisites: Participants in this seminar must have achieved Six Sigma Yellow Belt certification.

Six Sigma Certification:  Applied Regression Analysis for Business Decision Making is required to sit for the Six Sigma Black Belt examination.

Textbook: Montgomery, D.C., Peck, E. A., Vining, G. G., Introduction to Linear Regression Analysis, 3rd Edition, Wiley and Sons.

Statistical Software:  Minitab 14

Seminar Outline:

Chapter 1: Introduction

Regression and Model Building

Data Collection

Uses of Regression

Chapter 2: Simple Linear Regression:

Simple Linear Regression Model

Least Squares Estimation of Parameters

Hypothesis testing on the Slope and Intercept

Interval Estimation in Simple Linear Regression

Prediction of New Observations

Coefficient of Determination

Considerations

Regression Through the Origin

Estimation by Maximum Likelihood

Cases Were the Regressor is Random

Chapter 3: Multiple Linear Regression

Multiple Regression Models

Estimation of Model parameters

Hypothesis testing in Multiple Linear Regression

Confidence in Multiple Regression

Prediction of New Observations

Hidden Extrapolation in Multiple Regression

Standardized Regression Coefficients

Multicollinearity

Why Do Regression Coefficients Have the Wrong Sign?

Chapter 4: Model Adequacy Checking

Residual Analysis

PRESS Statistic

Detection and treatment of Outliers

Lack of Fit of the Regression Model

Chapter 5: Transformations and Weighting to Correct Inaccuracies

Variance Stabilizing Transformations

Transformations to Linearize the Model

Analytical Methods for Selecting a Transformation

Generalized and Weighted least Squares

Chapter 6: Diagnostics for Leverage and Influence

Importance of Detecting Influential Observations

Leverage

Measures of Influence (Cook’s D)

Measures of Influence (DFFITS and DFBETAS)

Measure of Model performance

Detecting Groups of Influential Observations

Treatment of Influential Observations

Chapter 7: Polynomial Regression

Polynomial Models in One variable

Nonparametric Regression

Polynomial Models in Two or More variable

Orthogonal Polynomials

Chapter 8: Indicator Variables

General Concept of an Indicator Variable

Comments on the Use of Indicator Variables

Regression Approach to Analysis of Variance

Chapter 9: Variable Selection and Model Building

Model Building

Computational Techniques for Variable Selection

Chapter 10: Multicollinearity

Sources

Effects

Diagnostics

Methods

Chapter 11: Robust Regression

Need for Robust Regression

M-Estimators

Properties of Robust Estimators

Other Robust Estimators

Chapter 12: Non-Linear Regression

Linear and Non-Linear Models

Non-Linear Least Squares

Transformation to a Linear Model

Parameter Estimation

Statistical Inference

Chapter 13: Generalized Least Squares

Logistics Regression Models

Poisson Regression Models

Generalized Linear Model

Chapter 14: Other Topics in Regression Analysis

Regression Models with Autocorrelation Errors

Effect of Measurement Errors in the Regressors

Inverse Estimation

Bootstrapping

Classification and Regression Trees

Neural Networks

Designed Experiments for Regression

Chapter 15: Validation of Regression Models

Validation Techniques

Data from Planned Experiments

Design of Experiments for Business Decision Making

Seminar Description: This course will present tools and methodology useful in conducting experiments that provide valid answers to questions of interest to the experimenter.  The course will discuss an overall approach to obtaining and analyzing experimental data, the advantages of using structured multifactor experiments to screen for important factors, ways of minimizing the amount of data points needed to obtain desired information, and how to identify values of experimental factors that optimize the value of measured responses.  Factorial designs, fractional factorial designs, and response surface designs will be presented.  Emphasis will be on the knowledge required for proper application of these methods through many examples in business and quality management.

Prerequisites: Participants in this seminar must have achieved Six Sigma Yellow Belt certification.

Six Sigma Certification: Design of Experiments for Business Decision Making is required to sit for the Six Sigma Black Belt examination.

Text:  Paul Mathews, “Design of Experiments with Minitab,” American Society for Quality, ASQ Quality Press, WI: Milwaukee, 2005. The book comes with a supplementary CD containing Minitab files.

Statistical Software: Minitab 14

Seminar Outline:

Chapter 1: Graphical Presentation of Data

Types of Data

Histograms

Dot Plots

Scatter Plots

Multi-vari Charts

Chapter 2: Descriptive Statistics

Selection of Samples

Measures of Location

Measures of Variation

The Normal Distribution

Chapter 3: Inferential Statistics

Distribution of Sample Means (Sigma Known)

Confidence for the Population Mean (Sigma Known)

Hypothesis Test for One Sample Mean (Sigma Known)

Distribution of Sample Means (Sigma Unknown)

Hypothesis tests fro Two means (sigma Known and Unknown)

Inferences About One Variance

Hypothesis Tests for Two Sample Variances

Testing for Normality

Sample Size Calculation

Chapter 4: DOE Language and Concepts

Definition, Scope, and Motivation

Experiment Defined

Identification of Variables and Responses

Types of Variables

Types of Responses

Interactions

Types of Experiments

Types of Models

Selection of Variable level

Nested Variables

Covariates

Definition of Design in Design of Experiments

Types of Designs

Randomization

Replication and Repetition

Blocking

Confounding

Data Integrity and Ethics

Experiment Documentation

Why Experiments Go Bad

Chapter 5: Experiments for One-Way Classifications

Analysis by Comparison of All Possible Pairs Means

Graphical Approach to ANOVE

Introduction to ANOVA

Sum of Squares Approach to ANOVA Calculations

Calculating Forms for Sum of Squares

ANOVA for Unbalanced Experiments

After ANOVA: Comparing treatment Means

Completely Randomized Designs

Analysis of Means

Response Transformations

Sample Size for One-Way ANOVA

Design Considerations for One Way Classification Experiments

Chapter 6: Experiments for Multi-Way Classifications

Rationale for Two-Way ANOVA  

Sum of Squares Approach to Two- Way ANOVA (One Replicate)

Interactions

Interpretation of Two Way Experiments

Factorial Designs

Multi-Way Classification Designs

Chapter 9: Two-Level (2k ) Factorial Designs

22 Factorial Design

23 Factorial Design

Addition of Center Cells to the 2k Factorial Design

General procedures for the Analysis of 2k Factorial Design

Extra and Missing Values

Propagation of Error

Sample Size and Power

Chapter 10: Fractional Factorial Designs

25-1 Half Fractional Factorial Design

Other Fractional Factorial Designs

Design Resolution

Consequences of Confounding

Interpretation of Fractional Factorial Designs

Plackett-Burman Designs

Sample Size Calculations

Design Considerations

Chapter 11: Response Surface Designs

Terms in Quadratic Models

2k Designs with Centers

3k Factorial Designs

Box-Behnken Designs

Central Composite Designs

Comparison of Response Surface Designs

Sample Size Calculations

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Master Black Belt

Master Black Belt. A Master Black Belt takes on a leadership roles as keeper of the Six Sigma process, advisor to executives or business unit managers, and leverage, his/her skills with projects that are led by black belts and green belts. Frequently, master black belts report directly to senior executives or business unit managers. He or she is a proven change agent, leader, facilitator, and technical expert in Six Sigma management. 

      You must be able to work directly with top management to transform an organization’s management style into a Six
      Sigma management style, be a Black Belt, complete a total of ten successful Six Sigma projects, develop
      courseware, and teach seminars to be awarded the Six Sigma Master Black Belt certification.

 

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Lean Thinking

  INTRODUCTION TO Lean / Six Sigma MANAGEMENT

Seminar Description: Participants in this seminar will be introduced to the major elements of Lean thinking and methods. Lean thinking was popularized at Toyota and has resulted in enormous success for the company. The following topics will be discussed: Value Streams and Values stream mapping, Supermarket Pull Systems (Kanban Systems), Complex Value Streams (Multiple product Families), Total Productive Maintenance (TPM), Quick Changeovers (SMED), and Mistake Proofing Methods (Poka-Yoke Devices).

Prerequisites: Participants in this seminar must have achieved Six Sigma Champion certification.

Champion Certification: “Introduction to Lean / Six Sigma Management” is required to sit for the “Lean / Six Sigma” Green Belt certification examination.

Textbook: Gitlow, H. and Widener, S. (in press), Lean / Six Sigma for Green Belts and Champions: Foundations, Tools and Methods, Cases and Certification, Prentice-Hall Publishers (Saddle River, NJ).

Seminar Outline:

Chapter 1: Overview of Lean/Six Sigma Management

Key Ingredients for Success with Lean/Six Sigma Management

Benefits of Lean/Six Sigma Management

Process Basics (Voice of the Process)

Definition of Quality (Voice of the Customer)

Definitions of Six Sigma Management

What is New about Six Sigma Management?

Definition of Lean Management

What is New about Lean Management?

Definition of Lean/Six Sigma Management

What is New about Lean/Six Sigma Management?

Lean/Six Sigma Management and Transactional Processes

Chapter 2: Lean/Six Sigma Roles, Responsibilities, and Terminology

Roles and Responsibilities in Lean/Six Sigma Management

Technical Terminology of Six Sigma Management

Technical Terminology of Lean Management

Beginning Lean/Six Sigma Management

Lean/Six Sigma in Non-manufacturing Industries

Chapter 3: Macro Model of LEAN/Six Sigma Management (Dashboards)

Structure of a Dashboard

Components of a Dashboard

Some Examples of Lean/Six Sigma Measurement Indicators

Net Present Value (NPV)

First-time yield (FTY)

Rolled Throughput Yield (RTY)

Process Cycle Efficiency (PCE)

Dock-to-dock (DTD)

On-time-delivery (OTD)

Order-fulfillment lead time (OFLT)

Inventory turnover ratio

Build to schedule (BTS)

Overall equipment effectiveness (OEE)

Example of a Dashboard

Managing with a Dashboard

Prioritization of Lean/Six Sigma Projects

Management Decides Whether a Project Team Is Necessary

Chapter 4: Define Phase of the DMAIC Model

Activating a Lean/Six Sigma Project Team

Structure of the Define Phase

Prepare the Project Charter

Perform a Product Flow Analysis

Conduct a SIPOC Analysis

Perform a “Voice of the Customer” Analysis  

Create a Current-State Value Stream Map

Revise the Project Objective

Project Approval process (Tollgates)

Define Phase Tollgate Checklist 

Chapter 5: Measure Phase of the DMAIC Model

Construct Operational Definitions for CTQs 

Conduct an Operator Analysis

Establishing the Validity of the Measurement System for Each CTQ

Establishing the Baseline Capabilities for CTQs 

Measure Phase Tollgate Review Checklist

Chapter 6: Analyze Phase of the DMAIC Model

Identify the Xs for the Process Under Study

Identify the Xs Related to Each CTQ

Identify the High-Risk Xs for each CTQ

Develop Operational Definitions for High-Risk Xs

Establish Measurement System for High-Risk Xs

Establish Baseline Process Capabilities for Xs

Stabilize High-Risk Xs

Consider Major Nuisance Variables

Using Screening Designs to Reduce the Number of High-Risk Xs

Develop Hypotheses about the Relationships Between the High-Risk Xs and the CTQs

Analyze Phase Tollgate Review Checklist

The Analyze Phase for Processes with a Well-Established Dashboards

Chapter 7: Improve Phase of the DMAIC Model

Purpose of Designed Experiments

Level of Process Knowledge

Some Flawed Experimental Designs

Two-Factor Factorial Designs

Example of a Designed Experiment

Conduct a Pilot Study

Example of a Pilot Study

Identify Actions Needed to Implement Optimized Process

Improve Phase Tollgate Review Checklist

Chapter 8: Control Phase of the Dmaic Model

Reduce Risk Using Mistake Proofing (Poka-Yoke) Devices

Reduce the Effects of Collateral Damage to Related Processes

Standardize Improvements (International Standards Organization [ISO])

Maintain Control of the Xs

Develop a Control Plan for the Process Owner

Identify and Document Benefits and Costs of a Project

Input Project into Six Sigma Database

Diffuse the Improvements throughout the Organization

Champion and Process Owner Review Project

Presidential Tollgate Review Process

Chapter 13: Lean tools and methods

Value Streams

Identifying a Value Stream in Need of a Lean/Six Sigma Project

Creating a Current-State Value Stream Map for a Simple Value Stream

Drawing the Current State Value Stream Map for a Simple Value Stream

Example of a Current-State Value Stream Map for a Simple Value Stream

Overproduction / Batch Thinking

Supermarket Pull Systems (Kanban Systems)

Drawing the Future State Value Stream Map for a Simple Value Stream

Achieving the Future-State Value Stream

Example of Future-State Value Stream Map

Service Example of a VSM

Complex Value Streams (Multiple product Families)

Total Productive Maintenance (TPM)

Definition

Types of maintenance

TPM Dashboard

Components of TPM

Conclusion

Quick Changeovers (SMED)

Mistake Proofing Methods (Poka-Yoke Devices)

Background

Types of Inspection

Deming’s kp rule

Source Inspection and the Poka-Yoke System

Chapter 15: A lean/Six Sigma Case Study

Background

Define Phase

Measure Phase

Analyze Phase

Improve Phase

Control Phase

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